Locational Marginal Pricing Mechanism for Uncertainty Management Based on Improved Multi-ellipsoidal Uncertainty Set

The large-scale integration of renewable energy sources (RESs) brings huge challenges to the power system. A cost-effective reserve deployment and uncertainty pricing mechanism are critical to deal with the uncertainty and variability of RES. To this end, this paper proposes a novel locational margi...

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Main Authors: Zongzheng Zhao, Yixin Liu, Li Guo, Linquan Bai, Chengshan Wang
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:Journal of Modern Power Systems and Clean Energy
Subjects:
Online Access:https://ieeexplore.ieee.org/document/9426543/
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spelling doaj-064389e9cf2548e685a62407f2a17d8b2021-07-30T23:01:04ZengIEEEJournal of Modern Power Systems and Clean Energy2196-54202021-01-019473475010.35833/MPCE.2020.0008249426543Locational Marginal Pricing Mechanism for Uncertainty Management Based on Improved Multi-ellipsoidal Uncertainty SetZongzheng Zhao0Yixin Liu1Li Guo2Linquan Bai3Chengshan Wang4Key Laboratory of Smart Grid of Ministry of Education, Tianjin University,Tianjin,China,300072Key Laboratory of Smart Grid of Ministry of Education, Tianjin University,Tianjin,China,300072Key Laboratory of Smart Grid of Ministry of Education, Tianjin University,Tianjin,China,300072University of North Carolina at Charlotte,Department of Systems Engineering and Engineering Management,Charlotte,NC,USA,28223Key Laboratory of Smart Grid of Ministry of Education, Tianjin University,Tianjin,China,300072The large-scale integration of renewable energy sources (RESs) brings huge challenges to the power system. A cost-effective reserve deployment and uncertainty pricing mechanism are critical to deal with the uncertainty and variability of RES. To this end, this paper proposes a novel locational marginal pricing mechanism in day-ahead market for managing uncertainties from RES. Firstly, an improved multi-ellipsoidal uncertainty set (IMEUS) considering the temporal correlation and conditional correlation of wind power forecasting is formulated to better capture the uncertainty of wind power. The dimension of each ellipsoidal subset is optimized based on a comprehensive evaluation index to reduce the invalid region without large loss of modeling accuracy, so as to reduce the conservatism. Then, an IMEUS-based robust unit commitment (RUC) model and a robust economic dispatch (RED) model are established for the day-ahead market clearing. Both the reserve cost and ramping constraints are considered in the overall dispatch process. Furthermore, based on the Langrangian function of the RED model, a new locational marginal pricing mechanism is developed. The uncertainty locational marginal price (ULMP) is introduced to charge the RES for its uncertainties and reward the generators who provide reserve to mitigate uncertainties. The new pricing mechanism can provide effective price signals to incentivize the uncertainty management in the day-ahead market. Finally, the effectiveness of the proposed mechanism is verified via numerous simulations on the PJM 5-bus system and IEEE 118-bus system.https://ieeexplore.ieee.org/document/9426543/Day-ahead marketellipsoidal uncertainty setlocational marginal pricingreserverobust unit commitment
collection DOAJ
language English
format Article
sources DOAJ
author Zongzheng Zhao
Yixin Liu
Li Guo
Linquan Bai
Chengshan Wang
spellingShingle Zongzheng Zhao
Yixin Liu
Li Guo
Linquan Bai
Chengshan Wang
Locational Marginal Pricing Mechanism for Uncertainty Management Based on Improved Multi-ellipsoidal Uncertainty Set
Journal of Modern Power Systems and Clean Energy
Day-ahead market
ellipsoidal uncertainty set
locational marginal pricing
reserve
robust unit commitment
author_facet Zongzheng Zhao
Yixin Liu
Li Guo
Linquan Bai
Chengshan Wang
author_sort Zongzheng Zhao
title Locational Marginal Pricing Mechanism for Uncertainty Management Based on Improved Multi-ellipsoidal Uncertainty Set
title_short Locational Marginal Pricing Mechanism for Uncertainty Management Based on Improved Multi-ellipsoidal Uncertainty Set
title_full Locational Marginal Pricing Mechanism for Uncertainty Management Based on Improved Multi-ellipsoidal Uncertainty Set
title_fullStr Locational Marginal Pricing Mechanism for Uncertainty Management Based on Improved Multi-ellipsoidal Uncertainty Set
title_full_unstemmed Locational Marginal Pricing Mechanism for Uncertainty Management Based on Improved Multi-ellipsoidal Uncertainty Set
title_sort locational marginal pricing mechanism for uncertainty management based on improved multi-ellipsoidal uncertainty set
publisher IEEE
series Journal of Modern Power Systems and Clean Energy
issn 2196-5420
publishDate 2021-01-01
description The large-scale integration of renewable energy sources (RESs) brings huge challenges to the power system. A cost-effective reserve deployment and uncertainty pricing mechanism are critical to deal with the uncertainty and variability of RES. To this end, this paper proposes a novel locational marginal pricing mechanism in day-ahead market for managing uncertainties from RES. Firstly, an improved multi-ellipsoidal uncertainty set (IMEUS) considering the temporal correlation and conditional correlation of wind power forecasting is formulated to better capture the uncertainty of wind power. The dimension of each ellipsoidal subset is optimized based on a comprehensive evaluation index to reduce the invalid region without large loss of modeling accuracy, so as to reduce the conservatism. Then, an IMEUS-based robust unit commitment (RUC) model and a robust economic dispatch (RED) model are established for the day-ahead market clearing. Both the reserve cost and ramping constraints are considered in the overall dispatch process. Furthermore, based on the Langrangian function of the RED model, a new locational marginal pricing mechanism is developed. The uncertainty locational marginal price (ULMP) is introduced to charge the RES for its uncertainties and reward the generators who provide reserve to mitigate uncertainties. The new pricing mechanism can provide effective price signals to incentivize the uncertainty management in the day-ahead market. Finally, the effectiveness of the proposed mechanism is verified via numerous simulations on the PJM 5-bus system and IEEE 118-bus system.
topic Day-ahead market
ellipsoidal uncertainty set
locational marginal pricing
reserve
robust unit commitment
url https://ieeexplore.ieee.org/document/9426543/
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