A CVaR-robust-based multi-objective optimization model and three-stage solution algorithm for a virtual power plant considering uncertainties and carbon emission allowances. (May 2019)

• Record Type: Journal Article
• Authors: Ju, Liwei; Tan, Qinliang; Lu, Yan; Tan, Zhongfu; Zhang, Yuxie; Tan, Qingkun
• Is Part Of: International journal of electrical power & energy systems. Volume 107(2019)
• Page Start: 628
• Page End: 643
• Publication Date: 2019-05
• Subjects: Virtual power plant -- Multi-objective -- CVaR -- Robust optimization; 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.2018.12.012
• Languages: English
• ISSNs: 0142-0615

Abstract

Highlights: Our research focuses on Virtual Power Plant (VPP). A CVaR-robust-based risk aversion model for VPP is proposed. A three-stage solution algorithm for the multi-objective model is construct. The influence of carbon emission allowances on VPP operation is analyzed. Different risk attitudes of decision makers are comparatively discussed. Abstract: In order to make full use of distribute energy resources and decrease the abandoned energy of clean energy, the paper aggregates wind power plant (WPP), photovoltaic power generation (PV), biomass power generation (BPG), energy storage system (ESS), conventional gas turbines (CGT) and flexible load into a virtual power plant (VPP). Firstly, the basic structure and uncertainty factors of VPP operation are analyzed, and the output model of power sources is proposed. Then, a multi-objective optimization model is proposed with three objective functions, namely, the maximum operation revenue, the minimum operation risk and the minimum carbon emissions. Furthermore, the robust optimization theory is applied to construct a risk aversion model by converting the constraint conditions into stochastic constraint conditions with uncertainty factors. Thirdly, a three-stage solution algorithm is put forward for the proposed multi-objective model including payoff table establishment, fuzzy linearization and objective weight calculation. Finally, the modified IEEE30 node system is chosen as simulation system. The results show:(1) VPP could utilize the complementary nature of different distributed energy sources to balance the revenue, risk and carbon emission.(2) Robust optimization theory and conditional value at risk could describe the uncertainty risk, and, the prediction accuracy needs to be improved for controlling the operation risk.(3) The risk attitude of decision makers would affect VPP scheduling scheme, the less uncertainty lead to greater risk when confidence degree ≤0.85 and robust coefficient ≥0.95 (risk extreme aversion).(3) Price-based demand response (PBDR) could smooth load demand curve and the maximum total emission allowances (MTEA) can highlight the environmentally friendly characteristics, which could improve more grid-connected space of clean energy and achieve the optimal VPP operation. Therefore, the proposed multi-objective model could obtain higher economic benefit and achieve lower carbon emissions while rationally controlling risks, which could be taken as an reliable decision support for decision makers.