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1. A First Look at Node-Level Curtailment of Renewable Energy and its Implications

   https://doi.org/10.1145/3679240.3734627  

   Maji, Diptyaroop; Irwin, David; Shenoy, Prashant; Sitaraman, Ramesh K (June 2025, ACM)

   Electricity grids are trying to meet their demand by using more renewable energy as they move towards decarbonization. As the amount of renewables in the grid increases, there are periods when renewable supply exceeds the demand or when excess supply cannot be transmitted to a different location to satisfy the demand due to grid congestion. Consequently, renewable generators often need to be curtailed so that they operate below their maximum capacity. Such curtailment represents unutilized “green” energy that could have replaced energy produced from non-renewable “brown” sources. While prior works have studied curtailment at the grid level, curtailment is a local phenomenon that occurs at the level of a generation node, where each node is a power plant at a specific location feeding the grid. A grid may consist of hundreds of nodes, but curtailment may only occur in some nodes and at some times. Hence, understanding curtailment at the node level is important to evaluate its potential for decarbonization. We study curtailment at the node level for the Texas grid operated by ERCOT, which consists of hundreds of nodes producing wind and solar energy. Using extensive node-level data for the year 2023, we show that curtailment is highly non-uniform and intermittent — 20% of the nodes account for 77% of the total curtailed energy, while 70% of the nodes are curtailed for less than 10% of the year. We find that although wind curtailment is more prevalent, a greater fraction of solar generation is curtailed than wind. We also develop a method to identify the cause of curtailment from the Locational Marginal Price (LMP), showing that 74.3% of the time, curtailment in Texas is due to grid congestion. Overall, our analysis of node-level curtailment implies that while curtailment can potentially be forecasted in only a small fraction of the nodes, a considerable amount of curtailed energy can be utilized by adding demand adjacent to these nodes. 

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2. Advancing convergence research: Renewable energy solutions for off-grid communities

   https://doi.org/10.1073/pnas.2207754119  

   Moran, Emilio F.; Lopez, Maria Claudia; Mourão, Rachel; Brown, Erik; McCright, Aaron M.; Walgren, Judith; Bortoleto, Ana Paula; Mayer, Adam; Johansen, Igor Cavallini; Ramos, Karina Ninni; et al (December 2022, Proceedings of the National Academy of Sciences)

   Millions of people across the world live off-grid not by choice but because they live in rural areas, have low income, and have no political clout. Delivering sustainable energy solutions to such a substantial amount of the world’s population requires more than a technological fix; it requires leveraging the knowledge of underserved populations working together with a transdisciplinary team to find holistically derived solutions. Our original research has resulted in an innovative Convergence Framework integrating the fields of engineering, social sciences, and communication, and is based on working together with communities and other stakeholders to address the challenges posed by delivering clean energy solutions. In this paper, we discuss the evolution of this Framework and illustrate how this Framework is being operationalized in our on-going research project, cocreating hybrid renewable energy systems for off-grid communities in the Brazilian Amazon. The research shows how this Framework can address clean energy transitions, strengthen emerging industries at local level, and foster Global North–South scholarly collaborations. We do so by the integration of social science and engineering and by focusing on community engagement, energy justice, and governance for underserved communities. Further, this solution-driven Framework leads to the emergence of unique approaches that advance scientific knowledge, while at the same time addressing community needs. 

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3. The Potential Impact of Climate Change on the Efficiency and Reliability of Solar, Hydro, and Wind Energy Sources

   https://doi.org/10.3390/land11081275  

   Bhatt, Uma S.; Carreras, Benjamin A.; Barredo, José Miguel; Newman, David E.; Collet, Pere; Gomila, Damiá (August 2022, Land)

   Climate change impacts the electric power system by affecting both the load and generation. It is paramount to understand this impact in the context of renewable energy as their market share has increased and will continue to grow. This study investigates the impact of climate change on the supply of renewable energy through applying novel metrics of intermittency, power production and storage required by the renewable energy plants as a function of historical climate data variability. Here we focus on and compare two disparate locations, Palma de Mallorca in the Balearic Islands and Cordova, Alaska. The main results of this analysis of wind, solar radiation and precipitation over the 1950–2020 period show that climate change impacts both the total supply available and its variability. Importantly, this impact is found to vary significantly with location. This analysis demonstrates the feasibility of a process to evaluate the local optimal mix of renewables, the changing needs for energy storage as well as the ability to evaluate the impact on grid reliability regarding both penetration of the increasing renewable resources and changes in the variability of the resource. This framework can be used to quantify the impact on both transmission grids and microgrids and can guide possible mitigation paths. 

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4. Stochastic Planning of a Mostly-Renewable Power Grid

   https://doi.org/10.1109/CCTA54093.2023.10253007  

   Chen, Sunny; Mathieu, Johanna L.; Seiler, Peter (August 2023, IEEE Conference on Control Technology and Applications (CCTA))

   Power grid resource adequacy can be difficult to ensure with high penetrations of intermittent renewable energy. We explore enhancing resource adequacy by overbuilding renewables while modeling statistical correlations in renewable power at different sites. Overbuilding allows production during times of low power, and exploiting statistical correlations can reduce power variability and, subsequently, reduce needed renewable capacity. In this work, we present a stochastic optimization problem to size renewables and expand transmission while minimizing the expected dispatch cost. Our method uses statistical profiles of renewable production and embeds network constraints using the DC power flow equations. We assess our method’s effects on feasibility, load shedding, locational marginal prices, and generator curtailment. On the IEEE 9-bus system, we found that anti-correlation between generators reduced generation capacity needs with sufficient transmission. On the IEEE 30-bus system, we found that the optimal solution required significant overbuilding and curtailment of renewables regardless of the marginal cost of schedulable generation. 

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5. Quantifying the electricity, CO ₂ emissions, and economic tradeoffs of precooling strategies for a single-family home in Southern California*

   https://doi.org/10.1088/2634-4505/ac5d60  

   Mayes, Stepp; Sanders, Kelly (May 2022, Environmental Research: Infrastructure and Sustainability)

   Abstract High fractions of variable renewable electricity generation have challenged grid management within the balancing authority overseen by the California’s Independent System Operator (CAISO). In the early evening, solar resources tend to diminish as the system approaches peak demand, putting pressure on fast-responding, emissions-intensive natural gas generators. While residential precooling, a strategy intended to shift the timing of air-conditioning usage from peak-demand periods to cheaper off-peak periods, has been touted in the literature as being effective for reducing peak electricity usage and costs, we explore its impact on CO 2 emissions in regional grids like CAISO that have large disparities in their daytime versus nighttime emissions intensities. Here we use EnergyPlus to simulate precooling in a typical U.S. single-family home in California climate zone 9 to quantify the impact of precooling on peak electricity usage, CO 2 emissions, and residential utility costs. We find that replacing a constant-setpoint cooling schedule with a precooling schedule can reduce peak period electricity consumption by 57% and residential electricity costs by nearly 13%, while also reducing CO 2 emissions by 3.5%. These results suggest the traditional benefits of precooling can be achieved with an additional benefit of reducing CO 2 emissions in grids with high daytime renewable energy penetrations. 

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