| Darkwah A.B.; Shaffer B.; Hastings‐Simon S. | Layering incentives: The impact of local top-ups on solar adoption and welfare | Energy Policy | 2026-10-01 | Examines whether a local top-up to Alberta’s existing solar rebate program increases solar adoption and generates public welfare benefits. It finds that the top-up is fully passed through to consumers, increases solar installation rates by 72%, and produces societal benefits that exceed its public costs. |
| Chia L.E.; Cornaggia J.; Haushalter D.; Wang Q. | Capital without Labor: Data Centers and the Local Economy | SSRN Electronic Journal | 2026-09-04 | The paper studies the local economic consequences of data center development by comparing U.S. counties with operational data centers to near-miss counties that attracted proposals but no facilities. It finds that data center investment raises local government borrowing costs, particularly for water and school bonds, while producing little improvement in fiscal capacity, employment, or business formation, suggesting that it strains public infrastructure without generating broad local economic gains. |
| Huang K.; Huang S.; Wang H.; Wang Z.; Jiang Q.; Jin Z.; Gates I.D.; Li K.; Jiang G. | Electric heating-assisted SAGD and VHSD for heavy oil: Mechanisms, optimization, and carbon emission reduction | Geoenergy Science and Engineering | 2026-09-01 | The paper develops analytical and numerical models to evaluate how downhole electric heating affects productivity and carbon intensity in SAGD and VHSD heavy-oil recovery. It finds that optimized injector and producer heating can improve early-stage productivity and thermal performance while reducing CO₂ emissions by about 32%, demonstrating the potential of renewable-electricity-powered heating for lower-carbon heavy-oil extraction. |
| Johnston S.; Liu Y.; Yang C. | Grid connection costs as a barrier to new generation: Evidence from PJM and implications for transmission policy | Energy Economics | 2026-09-01 | The paper studies the determinants of electricity generator grid connection costs by linking connection costs to geographic patterns in transmission spending. It finds that connection costs, particularly network upgrade costs, are highly unpredictable, increase the likelihood of generator cancellation, and are lower where the grid operator has previously invested more in transmission capacity. |
| Huang Y.; Deb N.; Zareipour H. | Artificial Intelligence Data Centers and Power System Sustainability: Understanding the Sustainability Implications of AI-Driven Data Centers on Power Systems | IEEE Energy Sustainability Magazine | 2026-07-29 | Examines the impact of AI data centers on the sustainability of electric power systems, examining both the risks and opportunities presented by their rapid growth. The primary result is an overview of the mechanisms through which data centers affect power system sustainability, including characterizing load behavior, analyzing sustainability impacts, and evaluating corporate sustainability pathways. |
| Bharadwaj B.; Smart S.; Ashworth P.; Doyle R.; Gates I. | Investigating the merits of co-locating renewable energy with steel production to decarbonize the iron industry | Cell Reports Sustainability | 2026-06-26 | The paper evaluates the energy, land, and water requirements of scaled up renewable hydrogen, using direct reduced iron hydrogen (DRI-H) and electric arc furnace production to process global iron ore exports. It finds that co-locating DRI-H facilities with solar photovoltaic farms can cut energy and land requirements by 50% and water demand by 39% compared with supplying hydrogen via imported ammonia to existing steelmaking facilities. |
| Liang Z. | Inference as Flexibility: Ramp Management for Transmission-Connected AI Data Centres | arXiv | 2026-06-20 | The paper studies using flexible large language model inference serving within AI data centres to mitigate rapid power ramps from AI training, using software-defined batch-size control with battery energy storage systems (BESS). The coordinated batch-size and BESS strategy reduces BESS discharge energy by 71% and peak discharge power by 51% while maintaining near-complete compliance with a 10 MW/min ramp limit. |
| Armantalab O.; Ghosh R.; Hawkins J. | Potential for electric vehicle adoption in Midwest US States: A stated preference and two-stage MRP study | Journal of Choice Modelling | 2026-06-01 | The paper investigates vehicle choice and fleet electrification in the U.S. Midwest using a stated-preference survey that explicitly incorporates pickup-truck attributes and an multi-level regression with poststratification-based forecasting approach. It finds that battery-electric pickups have the lowest and least variable market share with charging time the strongest preference factor, indicating that substantial improvements in charging time and incentives would be needed for significant electric vehicle adoption. |
| Parvar S.S.; Amjady N.; Zareipour H. | Behaviorally Aware Pricing of Energy Storage as a Service Platform: A Prospect Theory-Based Bi-Level Framework | Energies | 2026-06-01 | Examines the underutilization of small-scale energy storage systems due to fragmented ownership and regulatory constraints, and proposes an enhanced energy storage as a service (ESaaS) framework to address these challenges. Incorporating behavioral decision making dynamics using prospect theory significantly influences pricing strategies and the overall profitability of both the ESaaS platform and the participating energy storage system owners. |
| Chung J.W.; Liang Z.; Mao Y.; Chen J.; Chowdhury M.; Dvorkin V. | OpenG2G: A Simulation Platform for AI Datacenter-Grid Runtime Coordination | arXiv | 2026-05-06 | The paper introduces OpenG2G, a simulation platform for studying runtime coordination between AI data centers and the electricity grid using realistic AI workloads and high-fidelity grid simulations. OpenG2G enables flexible evaluation and comparison of control strategies while quantifying how AI model and deployment choices affect data center power flexibility and grid coordination. |
| Fry N.; Khajehdehi O.; Hastings‐Simon S.; Shor R.; Mwesigye A. | Geothermal energy network transition dynamics for the existing building stock - A case study for New York | Energy Strategy Reviews | 2026-05-01 | This study develops a system dynamics model to examine geothermal energy networks transition dynamics in New York. Over a 45-year horizon, the modeled transition yields approximately 2097 GWh of additional electricity consumption, 7639 GWh of avoided methane gas use, and 14% avoided CO2-equivalent emissions relative to an initial-state static baseline, under present-day grid conditions. |
| Chia L.E.; Hu S.; Wang Q.; Fan M. | The Spatial Incidence of Hyperscale Data Centers | SSRN Electronic Journal | 2026-04-06 | The paper studies how data center openings affect nearby U.S. housing prices, using a stacked difference-in-differences design and nationwide housing transaction data. It finds that hyperscale data centers (those owned and operated by large cloud/AI firms) reduce nearby house prices by 6.8%, with effects concentrated within 14 km and varying by power capacity and prior local exposure, while large non-hyperscale facilities show little effect. |
| Vykhodtsev A.V.; ShakeriHosseinabad F.; Jang D.; Wang Q.; Rosehart W.; Zareipour H. | Artificial intelligence-assisted physics-based model of lithium-ion battery for power systems operation research | Journal of Energy Storage | 2026-03-20 | The paper develops a lithium-ion battery energy storage model that integrates neural-network representations of battery operation and degradation into a mixed-integer linear optimization framework. It finds that the proposed model enables feasible dispatch, extends battery lifespan, and produces higher revenue estimates for long-term energy arbitrage than conventional energy-throughput degradation models. |
| Cao S.L.C.; Nock D.; Davis A. | An analysis of machine learning approaches for enhancing decision-making in complex discrete choice tasks | Decision Analytics Journal | 2026-03-01 | Evaluates the performance of four machine learning models in estimating individual discrete choice rules under individual heterogeneity, using Monte Carlo experiments and a case study with real energy policy preference data. This work demonstrated the viability and limitations of semi-parametric and non-parametric models in the context of policy-centric discrete choice modeling and showed how the choice task context should drive model selection |
| Grant M.J.; Jayaraman E.; Atkinson C.; Al-Kaisi M.; Faseela F.; Wang H.Y.; Wilfinger C.; Cabanetos C.; Turkovic V.; Madsen M.; Welch G.C. | An Ammonium-Amino-Functionalized N-Annulated Perylene Diimide as a High-Performance Interlayer for Organic Photovoltaics | ACS Applied Materials and Interfaces | 2026-02-04 | Examines the synthesis and characterization of a new N-annulated perylene diimide conjugated molecule, PDIN-A, and its application in organic photovoltaic devices. PDIN-A exhibits higher stability and enables the fabrication of organic photovoltaic devices with a maximum power conversion efficiency of 16.17%. |
| Liang Z.; Chung J.W.; Chowdhury M.; Chen J.; Dvorkin V. | GPU-to-Grid: Voltage Regulation via GPU Utilization Control | arXiv | 2026-02-04 | The paper develops a GPU-to-Grid framework that couples device-level GPU control with power system objectives. The key insight is that reducing GPU power alleviates lower-voltage violations, while increasing GPU power mitigates upper-voltage violations; this challenges the common belief that minimizing GPU power is always beneficial to power grids. |
| Brown D.P.; Olmstead D.; Shaffer B. | Electricity market design with increasing renewable generation: Lessons from Alberta | Electricity Journal | 2026-02-01 | The paper examines Alberta’s electricity market design and the challenges posed by increasing wind and solar generation. It finds that integrated market designs incorporating the physical realities of the power system can improve grid reliability and cost-effectiveness as renewable energy expands. |
| Al-Shafei A.; Amjady N.; Zareipour H.; Cao Y. | Power System Transition Planning: A Planner-Oriented Optimization Model | Energies | 2026-02-01 | Presents a comprehensive power system transition-planning model that integrates detailed network constraints, adaptive long-term uncertainty, and a broad set of grid-enhancing transition technologies within a single optimization framework. The primary result is the development of a mixed-integer multi-stage stochastic program that enables concurrent investment decisions across various transition technologies, demonstrating the feasibility of highly detailed, transition-oriented electrical system planning models. |
| Doshi G.; Johnston S. | Market structure and technology adoption in renewable energy | Energy Economics | 2026-02-01 | The paper examines how electricity market structure affects technology adoption in the U.S. solar and wind power industries. It finds that projects in restructured, competitive markets are less likely to adopt frontier technologies, largely because of higher financing costs. |
| ShakeriHosseinabad F.; Far B.H.; Zareipour H. | Digital Twin-AI Framework for a Battery Management System | TechRxiv | 2026-01-06 | Examines a closed-loop digital-twin-AI framework for battery management systems that combines physics-informed neural networks, high-fidelity digital twins, and reinforcement learning to estimate internal battery states and regulate current safely. The framework demonstrates stable AI-driven state of charge regulation across different C rates and scalable extension from cell-to pack-level monitoring. |
| Johnston S. | Distributed Backup Power and the Changing Economics of Grid Reliability | Energy Journal | 2026-01-01 | Investigates the increasing adoption of residential battery backup systems, the accompanying decline in U.S. grid reliability, and how these distributed resources influence reliability planning and cost allocation policies. It finds that backup systems reduce the economically efficient level of grid reliability, which can lower electricity bills for households that do not adopt them. |
| Jose Volpato Filho C.; Fang G.; Pinarello Scalcon F.; Knight A.M.; Padilha Vieira R. | Multisegment Adaptive Current Control of Switched Reluctance Motors | IEEE Transactions on Transportation Electrification | 2026-01-01 | Investigates high‑performance current tracking for switched reluctance motor (SRM) drives and proposes a multisegment adaptive current controller to mitigate the inherent nonlinearities of SRMs. Experimental validation on a four-phase 8/6 SRM demonstrates the effectiveness of the controller across different operating points, confirming its suitability for high-performance SRM drives. |
| Zeng J.Z.; Duran S.; Karacaoglu N.; Sunar N. | Algorithmic Nudging for Energy Savings and Environment: Evidence from an IoT Platform | SSRN Electronic Journal | 2026-01-01 | Investigates how real‑time algorithmic alerts delivered through an energy platform influence electricity use in commercial retail stores where managers have no direct financial incentive to conserve energy. It finds that a single alert reduces a store’s consumption by about 16 % in the following hour, but additional alerts initially lower use but eventually lead to higher consumption, indicating that excessive nudging can diminish overall energy‑saving benefits. |
| Armantalab O.; Afzal H.; Hawkins J. | Who is more likely to buy an EV? A descriptive and integrated choice model analysis in the US Midwest | Transport Policy | 2026-01-01 | The paper examines vehicle ownership and future vehicle preferences in the US Midwest using integrated revealed and stated preference models that incorporate latent attitudes. The results show that greater awareness of electric vehicle (EV) attributes and environmental benefits can increase adoption, while charging-time concerns deter it, with purchase price and driving range being the most influential factors in EV choice. |
| Farrokhabadi M.; Sohail I. | Estimating the Impact of Wildfire Smoke on Distributed Solar PV Performance | SSRN Electronic Journal | 2026-01-01 | Examines the impact of wildfire smoke on distributed solar photovoltaic (PV) generation, specifically in urban areas where solar irradiance is reduced by transported wildfire smoke. Wildfire smoke can cause energy losses exceeding 50% of potential generation during extreme smoke events, as demonstrated by a case study in Calgary, Alberta. |
| Vithana S.; Sezer D.; Hastings‐Simon S.; Iwazian S. | A Static Mean Field Game for Optimal Renewable Energy Investment | SSRN Electronic Journal | 2026-01-01 | Examines the strategic behavior of wind farm developers in Alberta, Canada, using Mean Field Game theory to model their decentralized investment decisions in competitive electricity markets. The study highlights a trade-off between regulatory land-use objectives and economic efficiency in the use of renewable energy resources, providing quantitative insights into how policy design shapes the spatial distribution and financial performance of wind investments. |
| Rapson D.J.; Shaffer B. | Smooth Operator? Managing Electric Vehicle Integration in Constrained Distribution Networks | Federal Reserve Bank of Dallas, Working Papers | 2025-12-01 | Examines the challenges that electric vehicle adoption poses for the distribution grid, particularly the strain on local distribution capacity due to reduced load diversity at small aggregations. Demand-based tariffs and managed charging programs can be effective alternatives to costly infrastructure expansion, but consumer participation remains a barrier that economists can help address through rate structure design. |
| Atkinson C.; Welch G.C. | New benzo-9-crown-3 functionalized aryl imides for the capture and release of lithium ions from solution | Canadian Journal of Chemistry | 2025-12-01 | Examines the development of new conjugated imide compounds functionalized with the crown ether benzo-9-crown-3 for the selective extraction of lithium ions from aqueous sources. The three new compounds exhibit the formation of Li-ion sandwich complexes and near identical Li-ion extraction efficiencies, distribution coefficients, and selectivity under acidic conditions. |
| Alobaid O.; Ezekiel C.J.; Daniilidis A.; Finkbeiner T.; Mai P.M. | Groundwater-induced advective heat transfer in U-shaped closed-loop geothermal system: application for a Red Sea rift sedimentary basin | Geothermal Energy | 2025-12-01 | Investigates the thermal performance of closed-loop advanced geothermal systems in deep sedimentary formations, specifically evaluating the effects of groundwater flow on heat transport and extraction. Advective heat transfer induced by groundwater flow significantly enhances system efficiency, increasing thermal power output by up to 27% over a 40-year operational period. |
| Khajehdehi O.; Kahou M.E.; Hastings A.; Hastings‐Simon S. | Modelling the 'S curve': transition dynamics in EV adoption | Environmental Research Communications | 2025-12-01 | Investigates the transition from internal combustion engine vehicles to electric vehicles (EV), examining the dynamics that drive this shift and the factors influencing adoption rates. Affordability alone does not drive the transition, with factors like EV model availability and consumer trust in battery technology playing crucial roles in accelerating adoption. |
| Bailey M.R.; Brown D.P.; Myers E.; Shaffer B.; Wolak F.A. | Electric Vehicles and the Energy Transition: Unintended Consequences of Time-of-Use Pricing | American Economic Review Insights | 2025-11-25 | Examines the impact of time-of-use pricing and managed charging on electric vehicle (EV) charging behavior via a field experiment. While time-of-use pricing can shift EV charging to off-peak hours, it may inadvertently create new peak charging periods, whereas centrally managed charging can more effectively reduce peak demand and alleviate strain on local capacity. |
| Afzal H.; Armantalab O.; Hawkins J. | Mapping Vehicle Diffusion Dynamics in the United States | Transportation Research Record | 2025-11-01 | Examines the factors influencing household vehicle fleet composition in the US, specifically examining the role of spatial and social proximity in the diffusion of new vehicle powertrains and models. Spatial proximity and demographic variables play a significant role in the adoption of plugin electric vehicles, hybrid electric vehicles, and US brand vehicles, with larger county populations and elevated state grid CO2 intensity associated with higher adoption rates. |
| Baghkarvasef M.; Bidram A.; Farrokhabadi M.; Sohail I.; Khargonekar P.P.; Zareipour H.; Parvania M. | Leveraging Artificial Intelligence for Enhancing Power Grid Resilience to Extreme Weather Events: Applications and Challenges | IEEE Energy Sustainability Magazine | 2025-11-01 | This article discusses the data management practices required by electric power utilities to improve grid resilience and elaborates the applications of AI for the enhanced resilience of electric power grids. The data management and AI applications are discussed from the perspective of preventive and mitigative actions on different power grid sectors, like generation, transmission, and distribution. |
| Xu J.F.; Green A.; Jain S.; Chan D.; Billington S.L. | Impact of sustainable retrofitting on resident wellbeing: A critical review | Building and Environment | 2025-10-01 | The paper reviews 71 peer-reviewed studies on how sustainable residential building retrofits affect resident wellbeing across different demographics and regions. The review shows that indoor comfort is the most frequently assessed and consistently improved wellbeing outcome, while social wellbeing and other categories remain less explored, highlighting the need for more longitudinal, resident-centered evaluations that combine subjective and objective wellbeing measures with building performance metrics. |
| López M.Z.; Zareipour H. | Modeling the Duration of Electricity Price Spikes Using Survival Analysis | Energies | 2025-10-01 | Examines the duration of electricity price spikes, focusing on quantifying the time these high prices persist in the power system. The primary result is the development of a simple yet informative model, referred to as the price spike duration model, which uses the Kaplan–Meier estimator to evaluate the survival (duration) of price spikes over time. |
| López M.Z.; Ioannou Y.; Zareipour H. | Forecasting electricity prices with deep learning and dynamic sparse training | Sustainable Energy Grids and Networks | 2025-09-01 | The paper investigates the use of Dynamic Sparse Training (DST) techniques for deep-learning-based electricity price forecasting, comparing sparse models with their dense counterparts. The results show that DST-based sparse models can achieve state-of-the-art and competitive predictive performance while their sparsity may help capture nonlinear patterns and inductive biases specific to electricity market data. |
| Jia T.; Sezer D. | Improving short-term wind speed forecasts using regime-switching spatio-temporal covariance models | Journal of Renewable and Sustainable Energy | 2025-09-01 | Examines a methodology for forecasting short-term wind speed over a broad geographical area using regime-switching covariance models that incorporate prevailing wind dynamics. Incorporating prevailing wind speed and direction improves forecasts in areas with consistent wind patterns, while a symmetric model performs better in regions with more complex wind dynamics. |
| Scalcon F.P.; Prestes G.X.; Fang G.; Filho C.J.V.; Gründling H.; Vieira R.P.; Knight A.M. | A Fast Firing Angle Optimization Approach for Current-Controlled Switched Reluctance Generators in Wind Power Applications | Eletrônica de Potência | 2025-08-27 | Examines the optimization of switched reluctance generators operating in the current controlled region, below base speed, to achieve high performance operation. When compared to a conventional exhaustive search algorithm, the proposed particle swarm optimization algorithm-based procedure is capable of locating equivalent or better optimal firing angles, while reducing computational burden by approximately 90.27%. |
| Zougheib S.; Hoecherl M.; Alqahtani H.; Mai P.M.; Hoteit H.A.; Vahrenkamp V.C.; Ezekiel C.J.; Finkbeiner T. | Towards SDG 13: Turning CO2 From a Problem to a Solution Using the Earth’s Natural Heat | Frontiers for Young Minds | 2025-08-07 | The paper studies a technology that captures CO₂, injects it into underground rocks, and uses it to generate electricity. The main takeaway is that captured CO₂ could potentially be stored underground while also being used to produce energy, helping reduce emissions. |
| Ahmadi A.; Zareipour H.; Leung H. | Globalization for Scalable Short-term Load Forecasting | arXiv | 2025-07-15 | Examines global load forecasting in power transmission networks, focusing on the impact of data drifts, modeling techniques, and data heterogeneity. Global target-transforming models consistently outperform local counterparts, especially when enriched with global features and clustering techniques, while global feature-transforming models require additional techniques to manage data heterogeneity effectively. |
| Houde S.; Myers E. | Heterogeneous (Mis)Perceptions of Energy Costs: Implications for Measurement and Policy Design | Journal of Political Economy Microeconomics | 2025-06-17 | The paper studies how heterogeneity in consumers’ misperceptions of product costs affects the welfare consequences of taxes versus standards for regulating externalities from energy-using durable goods. In the US appliance market, minimum efficiency standards generally outperform taxes because they reduce allocative inefficiencies by lowering the variance of misperceived attributes. |
| Bahman S.; Zareipour H. | Long-Term Multi-Resolution Probabilistic Load Forecasting Using Temporal Hierarchies | Energies | 2025-06-01 | Proposes a multi-resolution probabilistic load forecasting framework that integrates climate and economic indicators to generate coherent forecasts at various time scales, including hourly, daily, monthly, and yearly levels. The proposed approach improves the accuracy of deterministic forecasts and enhances the reliability of probabilistic forecasts, particularly when using the Ordinary Least Squares reconciliation method. |
| Kim S.Y.; Sawangwong P.; Atkinson C.; Welch G.C.; Doumon N.Y. | Chemical structure and processing solvent of cathode interlayer materials affect organic solar cells performance | Journal of Materials Chemistry C | 2025-05-20 | Examines the stability of organic solar cells by comparing the performance of recently synthesized perylene diimide (PDI) CIL material, F-PDIN-EH, in different solvents to the well-established PDINO. F-PDIN-EH yields comparable efficiency to PDINO-based devices but are consistently less stable, irrespective of the solvent. |
| Bailey M.R.; Brown D.P.; Shaffer B.; Wolak F.A. | Show Me the Money! A Field Experiment on Electric Vehicle Charge Timing | American Economic Journal Economic Policy | 2025-05-01 | Investigates the effectiveness of financial incentives in shifting the timing of electric vehicle charging, comparing it to a prosocial information treatment. Financial incentives can significantly reduce peak-hour charging by 49 percent, but this effect is reversed when the incentives are removed. |
| Sackey C.V.H.; Cao S.L.C.; Nock D.; Armanios D.; Davis A. | Infrastructure Decision Preferences and the Influence of Social Justice Education | INFORMS Transactions on Education | 2025-02-24 | The paper examines whether social justice education influences students’ preferences for equality when planning electricity infrastructure in sub-Saharan Africa. An interactive education module increased equality preferences by 22% among non-U.S.-citizen students and by 18% on average among students with initially low equality preferences, leading to more equitable resource allocation. |
| Palandri J.; Rahmanifard H.; Layzell D.B.; Hastings‐Simon S. | Blue vs. Green: A comparative analysis of ammonia production and export in Western Canada and Australia | Renewable Energy | 2025-02-01 | The paper compares the economic costs of producing and transporting ammonia produced with low emissions from Canada and Australia to Japan in 2020, 2030, and 2050. Canada is substantially more cost-effective in 2020 and 2030 due to cheaper natural gas based hydrogen production, while costs converge by 2050 as Australia’s green ammonia becomes more competitive. |
| Ahmadi A.; Zareipour H.; Leung H. | Similarity-Based Clustering for Identification and Segmentation of Responsive Electricity Customers | IEEE Access | 2025-01-01 | Investigates the identification and segmentation of responsive electricity customers using a binary time series clustering approach to capture consumers' reactions to demand response signals. The key result is the effectiveness of the proposed similarity-based non-linear time series clustering approach in identifying responsive consumers with different responsive levels, as demonstrated by analyzing consumption data from the Low Carbon London project. |
| Egharevba G.; Dankers A.G.; Zareipour H. | Forecasting Transmission Line Loss Using a Cluster-Based Refinement Framework and Scheduled Outage Data | IEEE Access | 2025-01-01 | Investigates the development of a new framework for transmission line loss forecasting that incorporates qualitative operational data, such as scheduled outages, to enhance forecasting accuracy. The proposed framework outperforms existing state-of-the-art transmission loss forecasting models by integrating scheduled outage reports with a two-stage cluster-based refinement solution. |
| Bhattacharjee S.; Sioshansi R.; Zareipour H. | Comparing Participation Models in Electricity Markets for Hybrid Energy-Storage Resources | IEEE Transactions on Power Systems | 2025-01-01 | Investigates the strategic behavior of hybrid resources consisting of solar and energy storage under two proposed market-participation models in wholesale electricity markets. Co-located hybrid resources yield slight increases in hybrid-resource and generator profits, but at the cost of social-welfare losses, compared to integrated hybrid resources. |
| Wolfe K.M.; Alam S.; Gardner Z.T.; Pal B.; Harrison A.; Laquai F.; Risko C.; Welch G.C. | A green solvent processable, self-doped N-annulated perylene butyl tetraester applied as a solar cell cathode interlayer | Polymer International | 2025-01-01 | Investigates the synthesis and characterization of a new amino-bay-substituted, N-annulated perylene butyl tetraester (NH2-PTEN-H) and its application as a cathode interlayer in organic photovoltaic devices. NH2-PTEN-H delivers power conversion efficiencies comparable to those using the benchmark cathode interlayer material PFN-Br in conventional organic photovoltaic devices. |
| Hussain S.; Farrokhabadi M.; Zareipour H. | A Hybrid Imitation–Reinforcement Learning Framework for Optimal Operation of Soft Open Points in Unbalanced Distribution Networks | IEEE Transactions on Smart Grid | 2025-01-01 | Investigates a hybrid actor-critic framework for the optimal operation of phase-changing soft open points (PCSOPs) in unbalanced distribution networks, combining reinforcement learning and imitation learning. The proposed framework outperforms conventional methods, including nonlinear AC optimal power flow, in optimizing PCSOP operation on modified IEEE test feeders. |
| Karimi H.; Zareipour H.; Rosehart W. | Transition to Electric Commercial Fleet: Harnessing Grid Integration Opportunities for Accelerated Adoption | IEEE Transactions on Transportation Electrification | 2025-01-01 | Proposes a multistage investment planning framework for fleet transition, focusing on the revenue-generating potential of an electric fleet's aggregated battery through self-use or third-party electricity energy services. Ancillary energy services can lower the total cost of ownership for fleet owners and accelerate the transition to electric fleets. |
| Sharma S.; Yao H.; Farrokhabadi M.; Zareipour H.; Musı́lek P. | A Dynamic Retail Market Model to Investigate Sustainability of Retail Contracts in DERs-Penetrated Markets | IEEE Open Access Journal of Power and Energy | 2025-01-01 | Investigates the impact of behind-the-meter distributed energy resources (DERs) on the electricity grid and the need for innovative retailer business models to ensure long-term financial sustainability in the era of increasing DERs. Proposed subscription-based retailer business models can successfully mitigate the adverse financial effects of widespread DERs adoption and ensure long-term system stability. |
| Qu J.; Sun Q.; Qian Z.; Zareipour H.; Dong Z.Y. | A Transferable Framework of PV Power Forecasting for Cross-Regional Distributed PV Systems Using Domain Adversarial Temporal Network | IEEE Transactions on Industrial Informatics | 2025-01-01 | Investigates the development of a domain adversarial temporal network (DATN) based transfer learning framework to improve the accuracy of output power forecasting in distributed photovoltaic systems, particularly for newly built sites with limited historical data. The proposed DATN framework consistently performs best in four cross-regional transfer experiments, outperforming other domain adaptation methods and transfer strategies. |
| Tapia T.; Liang Z.; Konstantinou C.; Dvorkin Y. | Electricity Market-Clearing With Extreme Events | IEEE Transactions on Energy Markets Policy and Regulation | 2025-01-01 | Investigates the development of a new market design to efficiently maintain the reliability of renewable-dominant power systems during extreme weather events by co-optimizing system resources and managing associated uncertainties. The key result is the proposal of an extreme reserve service, which can be procured by co-optimized with energy and regular reserve through a large deviation theory chance-constrained model or a large deviation weighted chance-constrained model to mitigate costs while ensuring cost recovery and a competitive equilibrium. |
| Tavakolian M.; Zareipour H. | Weather Feature Selection for Robust and Optimized Energy Load Prediction | Journal of Engineering Advances and Technologies for Sustainable Applications | 2025-01-01 | The primary objective of this study was to identify the critical weather features required to construct a robust model for energy load prediction. The findings revealed that relying solely on temperature is inadequate for accurate load forecasting. Instead, the inclusion of additional weather features significantly improves prediction accuracy, with the specific features required varying by geographical location. |
| Lai M.H.; Knight A.; Lewis L.H.; Takorabet N.; Hirohata A.; Hsieh M.F. | Magnetics for Future Transportation: From Memory to Motors | IEEE Magnetics Letters | 2025-01-01 | Investigates the advancements in magnetics technology and its applications in enhancing the performance, safety, and cost-effectiveness of various modes of transportation, particularly electric vehicles. The key result of this review is the identification of five key technologies that are driving innovation in magnetics for transportation: automotive-ready memory solutions, innovative motor design, magnetic sensing, soft magnetic materials, and magnetic materials for efficient transportation. |
| Matthey M.A.; Hollis A.; Brandi C.; Kobiela G.; Roth B.; Silberberger M. | Climate impact auctions: an underused tool for green subsidies in the Global South | Climate Policy | 2025-01-01 | Investigates the effectiveness of using results-based subsidies, allocated through reverse auctions, to support emissions reductions in Low- and Middle-Income Countries. Results-based subsidies could be an attractive option for specific projects that can be competitive, have measurable results, and currently face socially suboptimal investment, but they may increase capital costs and reallocate risks from donors to project proponents. |
| Bailey M.; Brown D.P.; Shaffer B.; Wolak F.A. | Take the Load Off: Time and Technology as Determinants of Electricity Demand Response | SSRN Electronic Journal | 2025-01-01 | The paper studies how different demand-response technologies and levels of required household effort affect electricity consumption during individually randomized peak events. It finds that fully automated responses reduced consumption about five times more than responses requiring any active effort, suggesting that time and effort costs—not technological limitations—are the main barrier to demand flexibility. |
| Egharevba G.; Dankers A.G.; Zareipour H. | Behind-the-Fence Generation Forecasting: A Batched Decomposition Framework | IEEE Access | 2025-01-01 | Investigates behind-the-fence generation forecasting using a novel decomposition framework called batched decomposition framework, framing it as a structuring of the behind-the-meter problem. The proposed batched decomposition framework demonstrates high forecasting accuracy, comparable to traditional methods, while avoiding information leakage and outperforming state-of-the-art benchmarks for 24-hour ahead BTF forecasting in Alberta and Quebec. |
| Ezekiel C.J.; Vahrenkamp V.C.; Hoteit H.A.; Finkbeiner T.; Mai P.M. | Techno-economic assessment of large-scale sedimentary basin stored–CO2 geothermal power generation | Applied Energy | 2024-12-15 | The paper studies the techno-economic feasibility of using geologically stored supercritical CO₂ from blue hydrogen production to extract geothermal energy from deep sedimentary formations. The optimized system with horizontal production wells produces an average 164 MW of net electricity at an levelized cost of electricity of $77/MWh and an net present value of $480 million, whereas vertical wells are economically unviable. |
| Nazari M.; Cieplechowicz E.; Welch G.C. | Air processed, high open-circuit voltage indoor organic photovoltaic cells based on side chain modified N-annulated perylene diimides | Canadian Journal of Chemical Engineering | 2024-12-01 | Investigates the development of organic photoactive materials for high-performance indoor organic photovoltaics by modifying non-fullerene acceptors (NFAs) with varying side chains to improve their optical absorption and minimize energy losses. Overall, this work provides a sidechain engineering method to create NFAs for efficient indoor OPV devices. |
| Laventure A.; Brixi S.; Welch G.C.; Lessard B.H. | Stability assessment of PTB7-Th and a quinoxaline-based polymer in both organic thin film transistors and in organic photovoltaic devices | Canadian Journal of Chemical Engineering | 2024-12-01 | Investigates the impact of thermal annealing on the stability and performance of two conjugated polymers, PTB7-Th and QX1, used as electron donor polymers in organic photovoltaic devices. Results contribute to identify which molecular structures and which post-treatments are ideal to promote the stability of the active layers in the context of OPV devices. |
| Farrokhabadi M. | Occam's Razor in Residential PV-Battery Systems: Theoretical Interpretation, Practical Implications, and Possible Improvements | arXiv | 2024-11-28 | Investigates the theoretical interpretation and possible improvements of a widely adopted rule-based control method, known as Occam's control, for residential solar photovoltaics paired with battery storage systems. An alternative algorithm devised based on the theoretical insight outperforms Occam's control, with potential consequences including improved economics for residential PV-BSS systems and mitigation of distribution systems' operational challenges. |
| Benson A.L.L.; Clarkson C.R.; Zeinabady D. | Analysis of enhanced geothermal system flowback and circulation test data for fracture and reservoir characterization | Geoenergy Science and Engineering | 2024-11-16 | The paper develops and validates semi-analytical and analytical models for characterizing reservoir and hydraulic-fracture properties in enhanced geothermal systems using temperature, production, pressure, and flowback data. The models matched simulated cases within ±5% error and, when applied to the Utah Frontier Observatory for Research in Geothermal Energy site, estimated increasing fracture heights across three stimulation stages consistent with microseismic observations. |
| Jacqz I.; Johnston S. | Electric Vehicle Subsidies and Urban Air Pollution Disparities | Journal of the Association of Environmental and Resource Economists | 2024-11-01 | The paper studies how electric vehicle subsidy design affects adoption, subsidy receipt, and the spatial distribution of vehicle emissions across neighborhoods in seven U.S. metropolitan areas, using a structural model of vehicle demand and on-road emissions for Chicago. Income-targeted subsidies produce smaller overall carbon-emission reductions but greater reductions in NOx and PM2.5 pollution in lower-income neighborhoods. |
| Brehm P.A.; Johnston S.; Milton R. | Backup Power: Public Implications of Private Substitutes for Electric Grid Reliability | Journal of the Association of Environmental and Resource Economists | 2024-11-01 | Investigates the adoption and distributional implications of private substitutes for electric grid reliability. The existence of substitutes increases aggregate welfare and reduces the efficient level of reliability spending. |
| Brown D.P.; Muehlenbachs L. | The value of electricity reliability: Evidence from battery adoption | Journal of Public Economics | 2024-11-01 | The paper examines how California’s wildfire-prevention power outages affected household demand for electricity reliability, using adoption of rooftop solar-plus-battery systems to estimate willingness to pay for avoiding outages. The revealed-preference estimate of the willingness to pay for electricity reliability, the Value of Lost Load, was estimated to average around $4,980/MWh, implying that wildfire-related outages caused approximately $406 million in losses from foregone residential electricity consumption. |
| Rastgoo R.; Amjady N.; Zareipour H. | A deep generative model for selecting representative periods in renewable energy-integrated power systems | Applied Soft Computing | 2024-11-01 | In this paper, a new deep learning-based time aggregation method is proposed for selecting representative periods for renewable energy-integrated power system datasets where multiple variable energy resources are present. Results obtained on these two real-world test cases confirm the superiority of the proposed model with respect to the state-of-the-art conventional and deep learning-based models. |
| Parker D.P.; Johnston S.; Leonard B.; Stewart D.; Winikoff J.B. | Economic potential of wind and solar in American Indian communities | Nature Energy | 2024-11-01 | The paper examines whether renewable energy development on Indigenous American communities could reduce poverty by comparing wind and solar resources, reservation characteristics, and utility-scale renewable energy projects. It finds that reservations—particularly those with lower-income populations—often have strong renewable energy potential but host far fewer projects than comparable lands, potentially costing tribes more than $19 billion in lease and tax revenues by 2050. |
| Afzal H.; Hawkins J. | Electric vehicle and supply equipment adoption dynamics in the United States | Energy Policy | 2024-10-01 | The paper examines the dynamic and causal relationship between plug-in electric vehicle (PEV) adoption and charging station deployment across U.S. counties from 2012 to 2021. It finds a significant feedback relationship in which PEV adoption drives demand for charging infrastructure while greater charging availability encourages further PEV adoption, supporting policies that combine charging investments with subsidies for low-income households. |
| Collins G.; Dahl C.; Fleming M.; Tanner M.; Martin W.C.; Nadkarni K.; Hastings‐Simon S.; Bazilian M. | Projecting demand for mineral-based critical materials in the energy transition for electricity | Mineral Economics | 2024-06-01 | The paper develops a transparent model estimating demand for 33 materials through 2050 by coupling the IEA’s Beyond Two Degrees electricity-transition projections and Bloomberg’s electric-vehicle outlook with material intensities and recycling rates. It finds that total material demand for the transition could rise 294% from 2021 to 2050, with substantial variation across materials, including nearly 1300% growth for lithium and major increases in demand and sales value for steel, aluminum, and nickel. |
| Fried A.; Shaffer B.; Hastings‐Simon S. | Sufficiency of level 1 charging to meet electric vehicle charging requirements | Environmental Research Infrastructure and Sustainability | 2024-06-01 | Investigates the feasibility of meeting the energy needs of battery electric vehicles through home-based level 1 charging using real-world driving and charging data from 129 vehicles in Calgary, Canada. 29% of vehicles can be fully charged with level 1 charging, and a further 53% require only occasional supplementary level 3 charges, challenging the assumption that level 2 charging access is necessary for convenient operation. |
| Askarian I.; Pahlevani M.; Knight A.M. | A Hybrid Digital Control System for Totem-Pole Isolated AC/DC Converters Used in Electric Vehicles | IEEE Transactions on Transportation Electrification | 2024-06-01 | Explores a new digital control system for totem-pole isolated AC/DC converters operating in discontinuous conduction mode. Experiment results demonstrate the superior performance of the proposed hybrid control method. |
| Christensen P.; Francisco P.; Myers E.; Shao H.; Souza M. | Energy efficiency can deliver for climate policy: Evidence from machine learning-based targeting | Journal of Public Economics | 2024-06-01 | This paper demonstrate that a data-driven approach to predicting retrofit impacts based on previously realized outcomes is more accurate than the status quo engineering models. Targeting high-return interventions based on these predictions dramatically increases net social benefits, from $0.93 to $1.23 per dollar invested. |
| Li Q.; Liang Z.; Bernstein A.; Dvorkin Y. | Revealing Decision Conservativeness Through Inverse Distributionally Robust Optimization | arXiv | 2024-05-06 | This paper introduces Inverse Distributionally Robust Optimization (I-DRO) as a method to infer the conservativeness level of a decision-maker, represented by the size of a Wasserstein metric-based ambiguity set, from the optimal decisions made using Forward Distributionally Robust Optimization (F-DRO). Numerical experiments based on an IEEE 5-bus system and a realistic NYISO 11-zone system demonstrate I-DRO performance in both normal and extreme scenarios. |
| Sarajpoor N.; Rakai L.; Amjady N.; Zareipour H. | Generalizing Time Aggregation to Out-of-Sample Data Using Minimum Bipartite Graph Matching for Power Systems Studies | IEEE Transactions on Power Systems | 2024-05-01 | Explores a novel four-stage time aggregation method for extracting the underlying structure of historical renewable energy data, focusing on capturing inter-annual relationships between observations. The proposed method effectively generalizes clusters to out-of-sample data, as demonstrated by its effective performance in replicating annual operational costs, wind energy curtailment, and energy throughput in a unit commitment problem. |
| Calero I.; Canizares C.A.; Farrokhabadi M.; Bhattacharya K. | Machine Learning-Based Control of Electric Vehicle Charging for Practical Distribution Systems with Solar Generation | IEEE Transactions on Smart Grid | 2024-05-01 | Explores the development of a data-driven smart controller for electric vehicle (EV) charging in distribution systems, aiming to efficiently manage EV and solar photovoltaic resources to mitigate grid operation issues. The principal result is the proposal of a two-level Deep Reinforcement Learning agent that effectively coordinates EV charging rates to provide demand response services and maximize EV state of charge while avoiding distribution transformer overloading. |
| Duran S.; Hrenyk J.; Sahinyazan F.G.; Salmon E. | Re-righting renewable energy research with Indigenous communities in Canada | Journal of Cleaner Production | 2024-03-15 | This paper presents a multi-method, inductive examination of gaps between the expressed needs and rights of Indigenous communities in Canada and the questions investigated by researchers and policymakers in energy transition research. Recommendations include designing equitable research practices, understanding community worldviews, developing holistic research goals, respecting Indigenous data sovereignty, and sharing or co-developing knowledge with communities to align with community priorities closely. |
| Ginesi R.E.; Niazi M.R.; Welch G.C.; Draper E.R. | All slot-die coated organic solar cells using an amine processed cathode interlayer based upon an amino acid functionalised perylene bisimide | Rsc Applied Interfaces | 2024-03-12 | This paper investigates tyrosine-appended perylene bisimide (PBI-Y) as a solvent-resistant electron transport and passivating interlayer for SnO₂ in green, solution-processed PM6/Y6C12 organic photovoltaic cells. PBI-Y improves SnO₂ conductivity and enables air-processed devices with power conversion efficiency of 13% by spin coating and 10% by fully slot-die coating, demonstrating a scalable and more environmentally sustainable route to high-performance OPVs. |
| Ferrando R.; Pagnier L.; Mieth R.; Liang Z.; Dvorkin Y.; Bienstock D.; Chertkov M. | Physics-Informed Machine Learning for Electricity Markets: A NYISO Case Study | IEEE Transactions on Energy Markets Policy and Regulation | 2024-03-01 | Explores the development of an efficient solution to the optimal power flow problem in real-time electricity markets, leveraging physical constraints and market properties to ensure feasible market-clearing outcomes. The proposed solution, Physics-Informed Market-Aware Active Set learning Optimal Power Flow, can efficiently recover exact solutions to the optimal power flow problem by reducing the original market-clearing optimization to a system of linear equations. |
| López M.Z.; Zareipour H.; Quashie M. | Forecasting the Occurrence of Electricity Price Spikes: A Statistical-Economic Investigation Study | Forecasting | 2024-03-01 | Explores the application of machine learning and statistical models for short-term electricity price spike forecasting in Alberta's electricity market. Complementing statistical performance with economic assessment is significant in electricity price spike forecasting, as highlighted by the numerical results. |
| Alam S.; Aldosari H.; Petoukhoff C.E.; Váry T.; Althobaiti W.; Alqurashi M.; Tang H.; Khan J.I.; Nádaždy V.; Müller-Buschbaum P.; Welch G.C.; Laquai F. | Thermally-Induced Degradation in PM6:Y6-Based Bulk Heterojunction Organic Solar Cells | Advanced Functional Materials | 2024-02-05 | Explores the thermally-induced degradation of state-of-the-art organic photovoltaic devices, specifically PBDB-T-2F (PM6):BTP (Y6) bulk heterojunction solar cells, at different temperatures to understand the origin of thermal device instability. Thermally degraded devices exhibit a higher energy barrier for charge-transfer state to charge-separated state conversion and that significant bimolecular recombination limits device performance. |
| Anchustegui I.H.; Tscherning R. | Offshore oil and gas infrastructure electrification and offshore wind: a legal exploration | Journal of World Energy Law and Business | 2024-02-01 | Examines the electrification of offshore oil and gas production platforms using offshore wind energy, analyzing regulatory and legal issues and case studies in Norway and Atlantic Canada. It concludes that forward‑looking legal and regulatory reforms are required to clarify the governance of combined wind and hydrocarbon infrastructure and to enable coordinated co‑development of offshore energy projects. |
| Iyapazham Vaigunda Suba P.; Shoaib M.; Hoang Nguyen O.; Karan K.; Larter S.R.; Thangadurai V. | All-gel Proton-conducting Batteries with BiOCl and VOSO4 as Active Materials | Batteries and Supercaps | 2024-02-01 | Explores a modified redox flow battery design that utilizes a Bi/BiOCl and V4+/V5+ reaction-based redox couple in a gel-based architecture to overcome the limitations of traditional ion-selective membranes. This proof-of-concept battery can deliver a volumetric energy density of 22.14 Wh/L without the need for a traditional membrane or separator. |
| Qu J.; Sun Q.; Qian Z.; Wei L.; Zareipour H. | Fault diagnosis for PV arrays considering dust impact based on transformed graphical features of characteristic curves and convolutional neural network with CBAM modules | Applied Energy | 2024-02-01 | The paper studies a dust-aware fault-diagnosis method for photovoltaic arrays to identify complex faults across different blocking-diode configurations. The proposed method achieves high fault-diagnosis accuracy and reliability under varying operating conditions, outperforming alternative graphical feature transformations and convolutional neural network-based approaches in the case studies. |
| Habibi A.H.; Josse P.; Labrunie A.; Gohier F.; Welch G.C.; Blanchard P.; Cabanetos C. | Effect of Length of Ethylene Glycol Sigma-Linkers on Triphenylamine-Based Dimers Used as Molecular Donors for Organic Solar Cells | Chemistryselect | 2024-01-12 | This paper contains a direct comparison of two push-pull based dimers prepared in only three steps from commercially and affordable building blocks as molecular donors for organic solar cells. With significant differences from the charge transport, morphology and therefore power conversion efficiencies, results gathered in this study emphasized the potential of such simple yet efficient strategy to fine tune the processability of an active compound. |
| Zeinabady D.; Clarkson C.R. | Reservoir and Fracture Characterization for Enhanced Geothermal Systems: A Case Study Using Multifractured Wells at the Utah Frontier Observatory for Research in Geothermal Energy Site | SPE Journal | 2024-01-10 | The paper develops a methodology for using stage-by-stage post-fracture pressure decay data to estimate fracture and reservoir properties for enhanced geothermal systems. Analysis of three hydraulic fracturing stages at the Utah FORGE site showed that natural fractures caused low fluid efficiency and small hydraulic fractures in the openhole section, whereas perforated casedhole treatments achieved higher efficiency and larger fractures, consistent with imaging and microseismic data. |
| Khanal S.; Graf C.; Liang Z.; Dvorkin Y.; Unel B. | Multi-Objective Transmission Expansion: An Offshore Wind Power Integration Case Study | IEEE Transactions on Energy Markets Policy and Regulation | 2024-01-01 | Explores the development of a multi-objective planning model to facilitate the efficient and resilient adoption of offshore wind power in the U.S. Grid, accounting for negative externalities such as greenhouse gas emissions and air pollution. Accounting for these externalities requires greater upfront investment in clean generation and storage, but is balanced by lower expected operational costs. Optimizing points of interconnection can significantly lower total cost. |
| Tierney M.W.; Zareipour H. | Emissions Response: Efficient Decarbonization using Real-Time Data | IEEE Power and Energy Magazine | 2024-01-01 | Explores the concept of emissions response, which utilizes real-time emissions factors to facilitate a dynamic response in electricity grids for decarbonization and system efficiency. The principal result is the formalization of emissions response as an effective means of encouraging and regulating the energy transition, benefiting both grid systems and individual stakeholders. |
| Sarajpoor N.; Rakai L.; Arteaga J.; Amjady N.; Zareipour H. | Time Aggregation in Presence of Multiple Variable Energy Resources | IEEE Transactions on Power Systems | 2024-01-01 | Explores a new time aggregation method that can effectively capture both the temporal and spatial aspects of data from multiple variable energy resources. The proposed method outperforms existing approaches in preserving the shape of patterns in representative periods, particularly when energy storage is involved, as demonstrated through case studies and evaluation indices. |
| Almozayen M.A.; Knight A.M. | Modeling the Impact of System Disturbances on Grid-Connected DFIG Using Dynamic Phasor FEM | IEEE Transactions on Industry Applications | 2024-01-01 | Explores the performance of a wind-driven Doubly Fed Induction Generator (DFIG) under various power system disturbances, including symmetrical/asymmetrical voltage sags and harmonic pollution in the source voltage. Simulation results of the Dynamic Phasor Finite Element Method (FEM) are compared to traditional time-domain FEM (considering core saturation for both solvers) to prove the validity of the new method for modeling disturbed power systems in an accurate and fast way. |
| Forootani A.; Rastegar M.; Zareipour H. | Transfer Learning-Based Framework Enhanced by Deep Generative Model for Cold-Start Forecasting of Residential EV Charging Behavior | IEEE Transactions on Intelligent Vehicles | 2024-01-01 | Explores the problem of forecasting the charging behavior of new electric vehicle (EV) owners with limited historical charging records, known as the cold-start forecast problem. The proposed transfer learning-based framework, combined with a generative adversarial network (GAN), improves the accuracy of forecasting plug-out hours and required energy by more than 31% and 34%, respectively, compared to alternative machine learning and deep learning algorithms. |
| Vykhodtsev A.V.; Jang D.; Wang Q.; Rosehart W.; Zareipour H. | Physics-Aware Degradation Model of Lithium-ion Battery Energy Storage for Techno-Economic Studies in Power Systems | IEEE Transactions on Sustainable Energy | 2024-01-01 | Explores the development of a hybrid model for lithium-ion battery energy storage systems that combines physics-based and linear energy reservoir models to improve degradation estimates at a reasonable computational cost. The proposed hybrid model can reduce battery degradation by 45% compared to other modeling strategies while maintaining the same level of operation profits. |
| Kharazi S.; Amjady N.; Nejati M.; Zareipour H. | A New Closed-Loop Solar Power Forecasting Method with Sample Selection | IEEE Transactions on Sustainable Energy | 2024-01-01 | Proposes a new short-term solar power forecasting method with a closed-loop structure that iteratively corrects its predictions to enhance accuracy and reliability. The proposed method outperforms several state-of-the-art solar power prediction methods when tested on real-world solar farms. |
| Karimi H.; Zareipour H.; Rosehart W. | Demand Charge Management Based on Battery Aggregation of Commercial and Passenger Electric Fleet Vehicles | IEEE Transactions on Intelligent Vehicles | 2024-01-01 | The paper studies a load management platform that jointly schedules commercial fleet EV logistics, charging/discharging, and passenger EV energy services to assess demand charge management through EV battery aggregation. The results show that the proposed integrated routing and energy management model outperforms a baseline in the case studies. |
| Mansouri M.; Westwick D.T.; Moradi‐Shahrbabak Z.; Mojiri M.; Knight A.M. | A Supplementary Controller to Mitigate Damped Oscillations in Power Systems' Components Based on the Internal Model Principle | IEEE Access | 2024-01-01 | Explores a novel control strategy using the Internal Model Principle to mitigate damped oscillations in power systems, specifically targeting low-frequency electromechanical oscillations. This method effectively eliminates oscillations from the system output, demonstrating straightforwardness, resilience, and real-time deployment capabilities. |
| Mansouri M.; Westwick D.T.; Knight A.M. | The On-Line Estimation of Multi-Mode Electromechanical Oscillations Using the Cascade Structure of Damped-SOGI | IEEE Access | 2024-01-01 | Investigates a measurement-based approach for determining the parameters of multi-mode electromechanical oscillations in interconnected power systems. The proposed method, which operates sequentially and enhances the Damped Second Order Generalized Integrator, boasts several benefits including real-time application, resilience to noise, ability to ascertain the immediate amplitude of oscillations, and is straightforward to design and execute. |
| Robb D.; Billon P.L.; Bakker K. | Landscapes of Recarbonization: Carbon Neutrality, Settler Colonialism, and Cumulative Environmental Effects in the Peace River Region, Canada | Annals of the American Association of Geographers | 2024-01-01 | Investigates how contemporary net‑zero decarbonization strategies overlook and reshape landscapes, introducing the concept of “recarbonization” to describe the sociospatial coupling of new fossil‑fuel investments with purported carbon‑neutral agendas, illustrated through a case study of the Peace River region in western Canada. This article exposes the cumulative environmental effects and ongoing forms of colonial violence of some net-zero decarbonization agendas |
| Iyapazham Vaigunda Suba P.; Gopalakrishnan A.; Radović J.R.; Tutolo B.M.; Larter S.; Karan K.; Thangadurai V. | Electrochemical ocean alkalinity enhancement using a calcium ion battery | International Journal of Greenhouse Gas Control | 2023-12-01 | The paper studies a calcium ion battery approach that enhances alkalinity via electrochemical manipulation of seawater calcium concentrations, using a potassium barium iron cyanide electrode to transfer Ca²⁺ between seawater reservoirs. The method increased seawater alkalinity by 2.75%, enabling uptake of 2.64 mg CO₂ (0.72 mg C) per liter of seawater and demonstrating a potentially scalable, energy-efficient approach to marine carbon dioxide removal. |
| Pearson K.M.E.; Hastings-Simon S. | The mid-transition in the electricity sector: impacts of growing wind and solar electricity on generation costs and natural gas generation in Alberta | Environmental Research Infrastructure and Sustainability | 2023-12-01 | Studies the impact of increasing variable renewable energy generation (VREN) on the Alberta electricity grid, examining how it affects fossil fuel power generation patterns and costs. A high level of VREN (86% of demand) can be achieved at a relatively low cost ($100/MWh), allowing for significant emissions reductions (28.4-28.9 million tonnes CO2eq/year) while still requiring flexible market rules to balance variable renewable generation. |
| Sackey C.V.H.; Nock D.; Cao S.L.C.; Armanios D.; Davis A. | Incorporating Elicited Preferences for Equality into Electricity System Planning Modeling | Sustainability | 2023-11-27 | The paper examines how integrating elicited preferences for equality into an electricity system planning model affects investment decisions regarding technology deployment in sub-Saharan Africa. It finds that stronger preferences for equality increase the deployment of solar-diesel mini-grids, which quadruple the system’s carbon emissions intensity, highlighting a potential divergence between equitable and carbon-minimizing electrification strategies. |
| Pecunia V.; Silva S.R.P.; Phillips J.D.; Artegiani E.; Romeo A.; Shim H.; Park J.; Kim J.H.; Yun J.S.; Welch G.C.; Larson B.W.; Creran M.; Laventure A.; Sasitharan K.; Flores-Diaz N.; Freitag M.; Xu J.; Brown T.M.; ... Talin A.A. | Roadmap on energy harvesting materials | Jphys Materials | 2023-10-01 | Studies the potential of ambient energy harvesting to contribute to sustainable development and address environmental challenges through the conversion of waste energy from various processes and systems into electricity. Innovative materials are needed to efficiently convert ambient energy into electricity, and a roadmap is provided to outline promising directions for future research in this field. |
| Nejati M.; Amjady N.; Zareipour H. | A New Multi-Resolution Closed-Loop Wind Power Forecasting Method | IEEE Transactions on Sustainable Energy | 2023-10-01 | Studies a new multi-resolution closed-loop wind power forecasting method that combines predictions from low and high-resolution models to improve forecasting accuracy. The proposed method outperforms several other widely used wind power forecast methods in terms of accuracy, as demonstrated by its consistent results on two real-world wind farms. |
| Manfre Jaimes D.; Zamudio López M.; Zareipour H.; Quashie M. | A Hybrid Model for Multi-Day-Ahead Electricity Price Forecasting considering Price Spikes | Forecasting | 2023-09-01 | This paper proposes a new hybrid model to forecast electricity market prices up to four days ahead. The components of the proposed model are combined in two dimensions. The proposed methodology is effective in enhancing forecasting accuracy and price spike detection, as demonstrated by numerical results using data from Alberta's electricity market. |
| Nwaneto U.C.; Knight A.M. | Using Dynamic Phasors To Model and Analyze Selective Harmonic Compensated Single-Phase Grid-Forming Inverter Connected to Nonlinear and Resistive Loads | IEEE Transactions on Industry Applications | 2023-09-01 | Studies the development of a dynamic phasor (DP) model for a grid-forming inverter in an islanded microgrid, aiming to accurately capture the converter dynamics and system harmonics while reducing simulation time. The proposed DP model exhibits a high degree of correlation with detailed switching model results, while offering significant savings in computation time, making it a suitable alternative for large-scale system simulations. |
| Brown D.P.; Eckert A.; Shaffer B. | Evaluating the impact of divestitures on competition: Evidence from Alberta's wholesale electricity market | International Journal of Industrial Organization | 2023-07-01 | This paper analyzes market power in Alberta’s wholesale electricity market, where transitional arrangements that virtually divested generation assets from large incumbents were put in place during market restructuring in the early 2000’s and expired at the end of 2020. Subsequently, average peak hour prices rose by 120% the year after their expiry. We demonstrate that nearly two-thirds of this increase can be explained by elevated market power from the large suppliers. |
| Wei L.; Qu J.; Wang L.; Liu F.; Qian Z.; Zareipour H. | Fault Diagnosis of Wind Turbine with Alarms Based on Word Embedding and Siamese Convolutional Neural Network | Applied Sciences Switzerland | 2023-07-01 | Studies a novel fault diagnosis method for wind turbines that collaboratively uses labeled and unlabeled alarms to improve diagnosis accuracy. The main result is a proposed method that uses a Siamese convolutional neural network with an embedding layer model to distinguish different alarm sequences and diagnose fault categories based on similarity scores. The effectiveness of the proposed method is validated using actual alarm data from a wind farm. |
| Calero F.; Canizares C.A.; Bhattacharya K.; Anierobi C.; Calero I.; De Souza M.F.Z.; Farrokhabadi M.; Guzman N.S.; Mendieta W.; Peralta D.; Solanki B.V.; Padmanabhan N.; Violante W. | A Review of Modeling and Applications of Energy Storage Systems in Power Grids | Proceedings of the IEEE | 2023-07-01 | This article reviews several energy storage technologies that are rapidly evolving to address the renewable energy sources integration challenge, particularly compressed air energy storage, flywheels, batteries, and thermal energy storage systems (ESSs), and their modeling and applications in power grids. An overview of these ESSs is provided, focusing on new models and applications in microgrids and distribution and transmission grids for grid operation, markets, stability, and control. |
| Dawson L.; Knight A.M. | Investigating the impact of a dynamic thermal rating on wind farm integration | Iet Generation Transmission and Distribution | 2023-05-01 | Studies the impact of environmental conditions on the thermal ratings and limits of both overhead lines and transformers in power equipment, with a focus on integrating intermittent renewable energy sources into the grid. This analysis serves to provide a method to analyse the risks of using a higher transformer thermal limit, compared to the benefits of increased wind penetration and additional revenue. |
| Liang Z.; Mieth R.; Dvorkin Y. | Inertia Pricing in Stochastic Electricity Markets | IEEE Transactions on Power Systems | 2023-05-01 | Studies the pricing of inertia provision in a stochastic electricity market, where the uncertainty characteristics of renewable energy sources are considered. The proposed pricing mechanism reduces the total operating cost by allowing new virtual inertia providers to contribute to system inertia requirements and internalizing renewable energy source uncertainty. |
| Nwaneto U.C.; Knight A.M. | Dynamic Phasor-Based Modeling and Simulation of a Single-Phase Diode-Bridge Rectifier | IEEE Transactions on Power Electronics | 2023-04-01 | Studies dynamic phasor models of a single-phase diode-bridge rectifier, proposing four different models to accurately represent the rectifier's behavior under various conditions. Single-phase DBRs serve as a primary building block of consumer electronics. The proposed dynamic phasor models significantly reduce simulation time while maintaining accuracy, as validated by both simulation and experimental data. |
| Farahat M.E.; Welch G.C. | N-Annulated Perylene Diimide Non-Fullerene Acceptors for Organic Photovoltaics | Colorants | 2023-03-01 | Studies the development of non-fullerene acceptors based on the N-annulated perylene diimide dye for use in organic photovoltaics, exploring various molecular structures and their applications. The main result is the creation of a series of molecules with improved properties for use as non-fullerene acceptors in organic photovoltaic devices. |
| Li P.; Hoff A.; Gasonoo A.; Niazi M.R.; Nazari M.; Welch G.C. | Layer-by-Layer Processed Organic Photovoltaic Cells Using Slot-Die-Coating Methods and Non-halogenated Solvents under Ambient Conditions with PCE of 10% | Advanced Materials Interfaces | 2023-02-14 | Studies the development of high-performance organic solar cells (OSCs) using a slot-die coating method with non-halogenated solvents in air, which is a more environmentally friendly and scalable approach for large-scale manufacturing. OSCs with a bilayer-processed photoactive film using a specific solvent combination (o-Xylene/o-Xylene) exhibit superior efficiency (10.6%) compared to those using a different solvent combination (o-Xylene/2-MeTHF), but the latter shows better storage stability. |
| Yu T.; Tintori F.; Zhang Y.; He W.; Cieplechowicz E.; Bobba R.S.; Kaswekar P.I.; Jafari M.; Che Y.; Wang Y.; Siaj M.; Izquierdo R.; Perepichka D.F.; Qiao Q.; Welch G.C.; Ma D. | Miscibility driven morphology modulation in ternary solar cells | Journal of Materials Chemistry A | 2023-02-08 | Studies the synthesis and integration of the PDI-EH molecule into ternary organic solar cells (OSCs) to optimize their morphology. This work offers insights into morphology modulation and the resulting local charge carrier dynamic, thereby facilitating the development of OSCs in practical applications. |
| Bezerra Menezes Leite H.; Zareipour H. | Six Days Ahead Forecasting of Energy Production of Small Behind-the-Meter Solar Sites | Energies | 2023-02-01 | Studies the development of a new hybrid methodology for accurate solar energy forecasting at small-scale behind-the-meter photovoltaic sites, incorporating neighboring solar farms' power predictions to boost accuracy. Training the models with historical data and incorporating neighboring solar farms' power predictions can significantly improve the overall forecast accuracy, comparable to the complete-history persistence ensemble model. |
| Aluko A.; Knight A. | A Review on Vanadium Redox Flow Battery Storage Systems for Large-Scale Power Systems Application | IEEE Access | 2023-01-01 | This review presents the current state of the V-RFB technology for power system applications. The basic working operation of the V-RFB system with the principle of operation of its major components, the design considerations, and the limitations of each component are discussed. It presents technical information to improve the overall performance of the V-RFB by considering the materials of the cell components, modeling methods, stack design, flow rate optimization, and shunt current reduction. |
| Arteaga J.; Farrokhabadi M.; Amjady N.; Zareipour H. | Optimal Solar and Energy Storage System Sizing for Behind the Meter Applications | IEEE Transactions on Sustainable Energy | 2023-01-01 | Proposes an optimal sizing model for solar plus energy storage systems behind the meter, using a dynamic optimization algorithm that maximizes net worth while accounting for decreasing technology costs and uncertainties. The proposed algorithm can efficiently optimize the sizing and timing of investment in a PV-ESS system to minimize total project cost. |
| Almozayen M.A.; Knight A.M. | Dynamic Phasor Finite-Element Modeling of a DFIG for Grid Connection Studies | IEEE Open Journal of Industry Applications | 2023-01-01 | Studies the development of a novel cosimulation technique that combines dynamic phasor modeling with the finite-element method (FEM) to accurately model doubly fed induction generators in electric power systems. The proposed dynamic phasor FEM method can produce comparable results to traditional time-domain solvers at a significantly reduced simulation time. |
| Nwaneto U.C.; Knight A.M. | Full-Order and Simplified Dynamic Phasor Models of a Single-Phase Two-Stage Grid-Connected PV System | IEEE Access | 2023-01-01 | Studies the development of efficient simulation models for a single-phase two-stage grid-connected photovoltaic system using the dynamic phasor method. The proposed dynamic phasor models demonstrate good accuracy and computational advantage over detailed switching models, making them suitable for fast-paced transient analysis of distribution grids with high PV penetrations. |
| Nwaneto U.C.; Seif Kashani S.A.; Knight A.M. | Modeling Lyapunov Control-Based Selective Harmonic Compensated Single-Phase Inverter in the Dynamic Phasor Domain | IEEE Open Journal of Industry Applications | 2023-01-01 | Studies the development of a new model for single-phase grid-forming inverters used in uninterruptible power supply systems, focusing on improving simulation efficiency. The main result is a proposed dynamic phasor model that achieves high accuracy and superior computational speed compared to detailed switching models, validated through simulation and experimental test results. |
