Uncertainty locational marginal price formulation based on robust optimization
| Autor: | Ershun Du, Xichen Fang, Jiajia Yang, Kedi Zheng, Qixin Chen |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
Mathematical optimization
Optimization problem Computer science business.industry media_common.quotation_subject Robust optimization Rationality Payment Electronic Optical and Magnetic Materials Renewable energy Electric power system symbols.namesake General Energy Transmission (telecommunications) Lagrange multiplier symbols Electrical and Electronic Engineering business media_common |
| Zdroj: | CSEE Journal of Power and Energy Systems. |
| ISSN: | 2096-0042 |
| DOI: | 10.17775/cseejpes.2020.03210 |
| Popis: | With the increasing penetration of renewables, power systems have to operate in a more flexible way 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 at the 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 examples are conducted on the modified IEEE 5-bus and 118-bus systems to demonstrate the merits and applicability of the proposed mechanism. |
| Databáze: | OpenAIRE |
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