Optimization model for time-varying settlement of renewable energy consumption considering accommodation difficulty and supply–demand interaction

Li, Chunyan; Yao, Yiming; Zhao, Rongsheng; Xie, Kaigui

doi:10.1016/j.ijepes.2020.106469

Cited by 11 publications

(6 citation statements)

References 13 publications

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“…6 shows that the wholesale prices of both bundled renewable energy and nonbundled energy are positively correlated with the green certificate price, which is consistent with the results obtained from the above Eqs. (39) and (40). This is attributed to the wholesale price of nonbundled energy, as well as the purchase cost of conventional energy, also including the cost of purchasing green certificates corresponding to conventional energy in the green certificate market, which is considerably affected by the cost of green certificates.…”

Section: Analysis Of Transaction Results Under Risk Aversion Coeffici...mentioning

confidence: 99%

“…However, the VaR method cannot appropriately measure all risk situations. Considering the volatility of unit renewable energy consumption settlement, Li et al [39] constructed a time-varying settlement optimization model for renewable energy consumption. Jiang et al [40] adopted the behavioral portfolio theory to consider the risks and risk-free strategies of power retailers.…”

Section: Research Status Based On Rps With Uncertainty Risksmentioning

confidence: 99%

“…The optimal wholesale prices of the power retailers can be expressed, as shown in Eqs. (39) and (40).…”

Section: Conflicts Of Interestmentioning

confidence: 99%

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Optimal Decision-Making of Trans-Provincial Electricity Market Subjects with Risks under Renewable Portfolio Standards

Wang¹,

Chen²,

Wu³

et al. 2022

Energy Engineering

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The randomness and uncertainty of renewable energy generation are expected to significantly change the optimal decision-making of trans-provincial electricity market subjects. Therefore, it is beneficial to optimize the interests of each of these subjects, considering the unpredictable risks of renewable energy under the renewable portfolio standards (RPS) and researching their effects on the optimal decision-making of transprovincial electricity market multi-subjects. First, we develop a trans-provincial trading market mechanism for renewable energy and clarify the electricity supply and demand relation and the green certificates supply and demand relation of trans-provincial electricity market multi-subjects. Then, under the RPS, we construct a multi-subject game model of the power supply chain that recognizes the risks, and adopt the reverse induction method to discuss the optimum risk-taking judgment of each subject in the trans-provincial electricity market. Finally, we use MATLAB to verify the viability and efficacy of the proposed game model, and obtain a certain reference value for the optimal decision-making of trans-provincial electricity market subjects. In summary, we consider the uncertainty risks of renewable energy under RPS, study the effects of the green certificate price and risk aversion coefficient in the RPS mechanism on the optimal decisionmaking of trans-provincial electricity market subjects, and obtain the changing trends of two different power products and those of different electricity market subjects under the influence of the green certificate price and risk aversion coefficient, which have a certain reference value for studying the factors affecting the optimal decision-making of trans-provincial electricity market subjects.

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Section: Analysis Of Transaction Results Under Risk Aversion Coeffici...mentioning

confidence: 99%

Section: Research Status Based On Rps With Uncertainty Risksmentioning

confidence: 99%

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Optimal Decision-Making of Trans-Provincial Electricity Market Subjects with Risks under Renewable Portfolio Standards

Wang¹,

Chen²,

Wu³

et al. 2022

Energy Engineering

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“…The case study is run for a representative day (24 h at hourly intervals) of the winter and summer seasons, where the one-day total energy consumption is assumed to be highest and lowest, respectively. 2 Note that demand for electricity in the town of Ohakune peaks in winter with the highest daily electricity consumption occurring during the evening peak period, between 5 p.m. to 10 p.m. [68].…”

Section: Case Study: Ohakune New Zealandmentioning

confidence: 99%

“…Smart electrification with renewables is set to play a pivotal role in accelerating the transition to the low-carbon economy [1]. However, renewable energy sources (RESs) are collectively plagued by unpredictability and variability of supply [2], [3]. This is especially problematic during daily peak times when demand is highest [4].…”

Section: Introductionmentioning

confidence: 99%

Modelling utility-aggregator-customer interactions in interruptible load programmes using non-cooperative game theory

Mohseni

Brent

Kelly

et al. 2021

International Journal of Electrical Power & Energy Systems

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Aggregator-activated demand response (DR) is widely recognised as a viable means for increasing the flexibility of renewable and sustainable energy systems (RSESs) necessary to accommodate a high penetration of variable renewables. To this end, by acting as DR aggregators and offering energy trading capabilities to smaller customers, energy retailers unlock additional sources of demand-side flexibility to ensure the cost-optimal operation of RSESs. Accordingly, a growing body of literature has highlighted the ways in which non-cooperative game theory could be used to reduce the gaps between modelled and real-world results for aggregator-mediated DR schemes. This paper aims to contribute to the trends of giving a realistic grounding to research on distributed DR-integrated energy scheduling by using insights from non-cooperative game theory to determine: (1) the optimal trade-off between importing electricity and utilising DR capacity in grid-tied RSESs, (2) the impact of the price elasticity of DR supply of different customer classes -especially, new sources of electricity demand, such as e-mobilityon the system-level dispatch of DR resources, and (3) the financial implications of harnessing the flexibility potential of a large number of end-consumers across different sectors. Accordingly, the principal goal of the paper is to develop an operational planning optimisation model that can be directly applied to real-world aggregatormediated, market-based demand-side flexibility provisioning domains. To this end, this paper presents the first DR elasticity-aware, non-cooperative game-theoretic DR scheduling model that: (1) yields the best compromise solution between imported power and dispatched DR resources from the utility's perspective, (2) characterises the utility-aggregator-customer interactions during the market-based DR trade process with several customer categories involved, and (3) disaggregates the total sectoral load on the system to individual end-consumers, which has potential implications for pre-feasibility and business case assessments. The application of the model to a conceptual micro-grid for the town of Ohakune, in New Zealand, demonstrates its effectiveness in reducing the daily system operational cost by ~66% and ~47% on a representative summer and winter day, respectively. Importantly, the paper provides statistically significant evidence supporting that activating the flexibility potential of small-to medium-scale end-consumers through specifically defined third-party aggregators in a market-based approach -that is aware of strategic interactions among instrumentally rational economic agents involved in the dispatch and delivery of DR resources -plays a significant role in the cost-optimal transition to 100%-renewable electricity generation systems within the smart grid paradigm.

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Optimal RPS Implementation Strategy Considering Both Power Suppliers and Users

2024

Sustainable Hybrid Energy Systems

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Optimization model for time-varying settlement of renewable energy consumption considering accommodation difficulty and supply–demand interaction

Cited by 11 publications

References 13 publications

Optimal Decision-Making of Trans-Provincial Electricity Market Subjects with Risks under Renewable Portfolio Standards

Optimal Decision-Making of Trans-Provincial Electricity Market Subjects with Risks under Renewable Portfolio Standards

Modelling utility-aggregator-customer interactions in interruptible load programmes using non-cooperative game theory

Optimal RPS Implementation Strategy Considering Both Power Suppliers and Users

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