Fang, Xichen, Du, Ershun, Zheng, Kedi, Yang, Jiajia, and Chen, Qixin (2020) Locational Pricing of Uncertainty Based on Robust Optimization. CSEE Journal of Power and Energy Systems, 7 (6). pp. 1345-1356.

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Abstract

With the increasing penetration of renewables, power systems have to operate with greater flexibility to address the uncertainties of renewable output. This paper develops an uncertainty locational marginal price (ULMP) mechanism to price these uncertainties. They are denoted as box deviation intervals as suggested by the market participants. The ULMP model solves a robust optimal power flow (OPF) problem to clear market bids, aiming to minimize the system cost as a prerequisite that the reserve margin can address all the relevant uncertainties. The ULMP can be obtained as a by-product of the optimization problem from the Lagrange multipliers. Under the ULMP mechanism, renewables and consumers with uncertainty will make extra payments, and the thermals and financial transmission right (FTR) holders will be compensated. It is further shown that the proposed mechanism has preferable properties, such as social efficiency, budget balance and individual rationality. Numerical tests are conducted on the modified IEEE 5-bus and 118-bus systems to demonstrate the merits and applicability of the proposed mechanism.

Item ID:	78142
Item Type:	Article (Research - C1)
ISSN:	2096-0042
Copyright Information:	© 2020 CSEE.
Date Deposited:	12 Apr 2023 03:48
FoR Codes:	40 ENGINEERING > 4008 Electrical engineering > 400803 Electrical energy generation (incl. renewables, excl. photovoltaics) @ 100%
SEO Codes:	17 ENERGY > 1703 Energy storage, distribution and supply > 170305 Energy systems and analysis @ 100%
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