A Credibility Theory-Based Robust Optimization Model to Hedge Price Uncertainty of DSO with Multiple Transactions

This paper addresses the deregulated electricity market arising in a distribution system with an electricity transaction. Under such an environment, the distribution system operator (DSO) with a distributed generator faces the challenge of electricity price uncertainty in a spot market. In this cont...

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Main Authors: Li-Peng Shao, Jia-Jia Chen, Lu-Wen Pan, Zi-Juan Yang
Format: Article
Language:English
Published: MDPI AG 2022-11-01
Series:Mathematics
Subjects:
Online Access:https://www.mdpi.com/2227-7390/10/23/4420
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author Li-Peng Shao
Jia-Jia Chen
Lu-Wen Pan
Zi-Juan Yang
author_facet Li-Peng Shao
Jia-Jia Chen
Lu-Wen Pan
Zi-Juan Yang
author_sort Li-Peng Shao
collection DOAJ
description This paper addresses the deregulated electricity market arising in a distribution system with an electricity transaction. Under such an environment, the distribution system operator (DSO) with a distributed generator faces the challenge of electricity price uncertainty in a spot market. In this context, a credibility theory-based robust optimization model with multiple transactions is established to hedge the uncertain spot price of the DSO. Firstly, on the basis of credibility theory, the spot price is taken as a fuzzy variable and a risk aversion-based fuzzy opportunity constraint is proposed. Then, to exploit the resiliency of multiple transactions on hedging against uncertain spot price, the spot market, option contract and bilateral contract integrating power flow constraints are studied, because it is imperative for DSO to consider the operational constraints of the local network in the electricity market. Finally, the clear equivalence class is adopted to transform the risk aversion constraint into a deterministic robust optimization one. Under the premise of considering the expected cost of the DSO, the optimal electricity transaction strategy that maximizes resistance to uncertain spot price is pursued. The rationality and effectiveness of the model are verified with a modified 15-node network. The results show that the introduction of option contracts and bilateral contracts reduces the electricity transaction cost of DSO by USD 28.5. In addition, under the same risk aversion factor, the cost of the proposed model is reduced by USD 195.18 compared with robust optimization, which avoids the over-conservatism of traditional robust optimization.
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spelling doaj.art-82d8d2a6d15c403f99e9293a2a0fe09f2023-11-24T11:33:13ZengMDPI AGMathematics2227-73902022-11-011023442010.3390/math10234420A Credibility Theory-Based Robust Optimization Model to Hedge Price Uncertainty of DSO with Multiple TransactionsLi-Peng Shao0Jia-Jia Chen1Lu-Wen Pan2Zi-Juan Yang3School of Electrical and Electronic Engineering, Shandong University of Technology, Zibo 255000, ChinaSchool of Electrical and Electronic Engineering, Shandong University of Technology, Zibo 255000, ChinaSchool of Electrical and Electronic Engineering, Shandong University of Technology, Zibo 255000, ChinaSchool of Electrical and Electronic Engineering, Shandong University of Technology, Zibo 255000, ChinaThis paper addresses the deregulated electricity market arising in a distribution system with an electricity transaction. Under such an environment, the distribution system operator (DSO) with a distributed generator faces the challenge of electricity price uncertainty in a spot market. In this context, a credibility theory-based robust optimization model with multiple transactions is established to hedge the uncertain spot price of the DSO. Firstly, on the basis of credibility theory, the spot price is taken as a fuzzy variable and a risk aversion-based fuzzy opportunity constraint is proposed. Then, to exploit the resiliency of multiple transactions on hedging against uncertain spot price, the spot market, option contract and bilateral contract integrating power flow constraints are studied, because it is imperative for DSO to consider the operational constraints of the local network in the electricity market. Finally, the clear equivalence class is adopted to transform the risk aversion constraint into a deterministic robust optimization one. Under the premise of considering the expected cost of the DSO, the optimal electricity transaction strategy that maximizes resistance to uncertain spot price is pursued. The rationality and effectiveness of the model are verified with a modified 15-node network. The results show that the introduction of option contracts and bilateral contracts reduces the electricity transaction cost of DSO by USD 28.5. In addition, under the same risk aversion factor, the cost of the proposed model is reduced by USD 195.18 compared with robust optimization, which avoids the over-conservatism of traditional robust optimization.https://www.mdpi.com/2227-7390/10/23/4420price uncertaintyDSOcredibility theoryfuzzy chance constraintrobust optimization
spellingShingle Li-Peng Shao
Jia-Jia Chen
Lu-Wen Pan
Zi-Juan Yang
A Credibility Theory-Based Robust Optimization Model to Hedge Price Uncertainty of DSO with Multiple Transactions
Mathematics
price uncertainty
DSO
credibility theory
fuzzy chance constraint
robust optimization
title A Credibility Theory-Based Robust Optimization Model to Hedge Price Uncertainty of DSO with Multiple Transactions
title_full A Credibility Theory-Based Robust Optimization Model to Hedge Price Uncertainty of DSO with Multiple Transactions
title_fullStr A Credibility Theory-Based Robust Optimization Model to Hedge Price Uncertainty of DSO with Multiple Transactions
title_full_unstemmed A Credibility Theory-Based Robust Optimization Model to Hedge Price Uncertainty of DSO with Multiple Transactions
title_short A Credibility Theory-Based Robust Optimization Model to Hedge Price Uncertainty of DSO with Multiple Transactions
title_sort credibility theory based robust optimization model to hedge price uncertainty of dso with multiple transactions
topic price uncertainty
DSO
credibility theory
fuzzy chance constraint
robust optimization
url https://www.mdpi.com/2227-7390/10/23/4420
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