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Open AccessArticle

A Two-Stage Optimal Scheduling Model of Microgrid Based on Chance-Constrained Programming in Spot Markets

1
School of Economics and Management, North China Electric Power University, Beijing 102206, China
2
Power Generation Department, Fujian Yongfu Power Engineering Co., Ltd., Fuzhou 350108, Fujian, China
3
School of Economics and Management, Yan’an University, Yan’an 716000, Shanxi, China
*
Author to whom correspondence should be addressed.
Processes 2020, 8(1), 107; https://doi.org/10.3390/pr8010107
Received: 26 November 2019 / Revised: 30 December 2019 / Accepted: 10 January 2020 / Published: 14 January 2020
(This article belongs to the Special Issue Advances in Sustainable Supply Chains)
Aimed at the coordination control problem of each unit caused by microgrid participation in the spot market and considering the randomness of wind and solar output and the uncertainty of spot market prices, a day-ahead real-time two-stage optimal scheduling model for microgrid was established by using the chance-constrained programming theory. On this basis, an improved particle swarm optimization (PSO) algorithm based on stochastic simulation technology was used to solve the problem and the effect of demand side management and confidence level on scheduling results is discussed. The example results verified the correctness and effectiveness of the proposed model, which can provide a theoretical basis in terms of reasonably coordinating the output of each unit in the microgrid in the spot market. View Full-Text
Keywords: microgrid; spot markets; chance-constrained programming; demand side management microgrid; spot markets; chance-constrained programming; demand side management
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Li, J.; Tan, C.; Ren, Z.; Yang, J.; Yu, X.; Tan, Z. A Two-Stage Optimal Scheduling Model of Microgrid Based on Chance-Constrained Programming in Spot Markets. Processes 2020, 8, 107.

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