Competitive Energy Storage and the Duck Curve

Schmalensee, Richard

doi:10.5547/01956574.43.2.rsch

Cited by 18 publications

(9 citation statements)

References 24 publications

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“…As a result, electricity storage can significantly increase an electric grid's cost efficiency, particularly in the context of integrating intermittent renewable technologies. Schmalensee (2022) assesses investment in storage, thermal generation (e.g., nuclear and natural-gas-fired) and renewables generation. Renewable generation is positive only in the daytime period, while thermal generation can be employed in the daytime and nighttime periods.…”

Section: Literature Reviewmentioning

confidence: 99%

Carbon-free Electricity Supply in a Cournot Wholesale Market: Israel

Milstein,

Tishler,

Woo

2024

The Energy Journal

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We develop a two-stage model to analyze a Cournot wholesale electricity market in which competing firms use photovoltaics augmented with batteries (PVB) or combined cycle gas turbines (CCGTs) to meet time-varying demands. Capturing the complex interactions of output and investment decisions made by multiple profit-maximizing PVB and CCGT firms, our model yields the market’s long-run equilibrium of capacity mix and short-run equilibrium of electricity generation and price levels. Accounting for the sun’s irradiation that determines solar generation level, our model computes the battery cost reduction necessary for batteries entering the optimal capacity mix. Using Israel as a case study, we show how declining battery cost may cause PVB firms to displace CCGT firms, resulting in carbon-free electricity supply as a market-based outcome. The battery cost threshold initiating this outcome is ~24% of CCGT’s capacity cost, implying that natural gas is a transitional fuel in Israel’s pathway to deep decarbonization.

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Section: Literature Reviewmentioning

confidence: 99%

Carbon-free Electricity Supply in a Cournot Wholesale Market: Israel

Milstein,

Tishler,

Woo

2024

The Energy Journal

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“…For about a half-century now, the California Independent System Operator (CAISO) has been monitoring the Duck Curve and its future expectations, and their biggest finding has been the widening gap between morning and evening prices [34]. In a Boiteux-Turvey-style model, the long-run equilibrium value of storage capacity minimizes the expected system cost conditional on generation capacities solving the duck curve problems [35]. A duck chart was used to examine how much photovoltaic generation and wind power might need to be cut off if additional grid flexibility operations are not considered.…”

Section: Solar Energy Generation and Predictionmentioning

confidence: 99%

A Review for Green Energy Machine Learning and AI Services

Mehta,

Xu,

Lim

et al. 2023

Energies

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There is a growing demand for Green AI (Artificial Intelligence) technologies in the market and society, as it emerges as a promising technology. Green AI technologies are used to create sustainable solutions and reduce the environmental impact of AI. This paper focuses on describing the services of Green AI and the challenges associated with it at the community level. This article also highlights the accuracy levels of machine learning algorithms for various time periods. The process of choosing the appropriate input parameters for weather, locations, and complexity is outlined in this paper to examine the ML algorithms. For correcting the algorithm performance parameters, metrics like RMSE (root mean square error), MSE (mean square error), MAE (mean absolute error), and MPE (mean percentage error) are considered. Considering the performance and results of this review, the LSTM (long short-term memory) performed well in most cases. This paper concludes that highly advanced techniques have dramatically improved forecasting accuracy. Finally, some guidelines are added for further studies, needs, and challenges. However, there is still a need for more solutions to the challenges, mainly in the area of electricity storage.

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“…For more details see ( [44], [45], [46]). In our work we assume that the VOLL was set at 30$ per KW and the cost of overestimation was set at 0.15$ per KW.…”

Section: Examplementioning

confidence: 99%

“…This depends on several factors, including the type of customer, regional economic and demographic conditions, the timing and duration of power outages, and others [43]. For more details, see [44][45][46]. In our work, we assumed that the VOLL was set at USD 30 per KW and the cost of overestimation was set at USD 0.15 per KW.…”

Section: The Economic Cost Measurementioning

confidence: 99%

Probabilistic Peak Demand Estimation Using Members of the Clayton Generalized Gamma Copula Family

2022

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Climate change impacts many aspects of life and requires innovative thinking on various issues. The electricity sector is affected in several ways, including changes in the production components and consumption patterns. One of the most important issues for Independent System Operators, a state-controlled organization responsible for ensuring the reliability, availability, and quality of electricity delivery in the country, is the response to climate change. This is reflected in the appropriate design of production units to cope with the increase in demand due to extreme heat and cold events and the development of models aimed at predicting the probability of such events. In our work, we address this challenge by proposing a novel probability model for peak demand as a function of wet temperature (henceforth simply temperature), which is a weighting of temperature and humidity. We study the relationship between peak demand and temperature using a new Archimedean copula family, shown to be effective for this purpose. This family, the Clayton generalized Gamma, is a multi-parameter copula function that comprises several members. Two new measures of fit, an economic measure and a conditional coverage measure, were introduced to select the most appropriate family member based on the empirical data of daily peak demand and minimum temperature in the winter. The Clayton Gamma copula showed the lowest cost measure and the best conditional coverage and was, therefore, proven to be the most appropriate member of the family.

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Competitive Energy Storage and the Duck Curve

Cited by 18 publications

References 24 publications

Carbon-free Electricity Supply in a Cournot Wholesale Market: Israel

Carbon-free Electricity Supply in a Cournot Wholesale Market: Israel

A Review for Green Energy Machine Learning and AI Services

Probabilistic Peak Demand Estimation Using Members of the Clayton Generalized Gamma Copula Family

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