A dynamic decision-making method for energy transaction price of CCHP microgrids considering multiple uncertainties. (May 2021)

• Record Type: Journal Article
• Authors: Zhao, Huiru; Wang, Xuejie; Wang, Yuwei; Li, Bingkang; Lu, Hao
• Is Part Of: International journal of electrical power & energy systems. Volume 127(2021)
• Publication Date: 2021-05
• Subjects: Combined cooling, heating and power microgrid -- Load service entity -- Robust optimization -- Dynamic transaction price decision; Electrical engineering -- Periodicals; Electric power systems -- Periodicals; Électrotechnique -- Périodiques; Réseaux électriques (Énergie) -- Périodiques; Electric power systems; Electrical engineering; Periodicals; 621.3
• DOI: 10.1016/j.ijepes.2020.106592
• Languages: English
• ISSNs: 0142-0615

Abstract

Highlights: Scheduling of CCHP microgrid and LSE based on Robust Optimization. Using Salp Swarm Algorithm (SSA) to search the optimal transaction price. The price decision method can effectively reduce the operating cost. Renewable energy can be maximally consumed through this method. Abstract: Combined cooling, heating and power microgrid (CCHP microgrid) system, which has the characteristics of clean production and multi-energy comprehensive supply, has attracted great attention. Through the integration of renewable energy, etc., the electricity retailer can form a load service entity (LSE) to provide services. Transactions can be made between CCHP microgrid and LSE. However, how to determine the transaction price between them is still a problem. In addition, both the CCHP microgrid and LSE contain renewable energy with uncertain output, which affects the normal operation of the system. In this paper, we propose a dynamic decision-making method for the energy transaction price considering multiple uncertainties. According to the random output of renewable energy, the uncertainty set is constructed. Furthermore, a robust optimal dispatching model is established. According to the dispatching results, the optimal transaction price is searched by using the salp swarm algorithm (SSA). It can be seen from the simulation results: 1) This price decision method can effectively reduce the operating cost of the system; 2) The LSE acts as an energy exchange center in the entire system; 3) Using robust optimization for energy dispatching can maximize the consumption of renewable energy.