可调度发电
可再生能源
CVAR公司
数学优化
帕累托原理
计算机科学
电
电力系统
运筹学
经济
功率(物理)
工程类
风险管理
数学
预期短缺
电气工程
分布式发电
量子力学
物理
管理
作者
Hooman Khaloie,François Vallée,Chun Sing Lai,Jean‐François Toubeau,Nikos Hatziargyriou
出处
期刊:IEEE Transactions on Power Systems
[Institute of Electrical and Electronics Engineers]
日期:2022-01-01
卷期号:37 (1): 701-714
被引量:46
标识
DOI:10.1109/tpwrs.2021.3096815
摘要
Solar energy and bioenergy are two leading renewable forms of energy in the move toward a near-zero-emission electric power industry. Concentrated solar power units coupled with thermal storage and biomass power plant offer dispatchable electricity, raising their ever-growing role in future renewable-dominated networks. This paper proposes a day-ahead and intraday dispatch model for maximizing the profit of an Integrated Biomass-Concentrated Solar (IBCS) system considering the synergies arising from their coupled operation. To sensibly capture uncertainty and decision sequence of real-life electricity markets, a two-stage stochastic structure is proposed, while the solar-related uncertainty is involved using Information Gap Decision Theory (IGDT). The model is complemented with a novel multi-objective architecture based on the compound of IGDT and Conditional Value-at-Risk (CVaR), which allows handling risk exposure to both stochastic and IGDT inputs. The Pareto strategies in the multi-objective model are extracted through an expanded form of the $\epsilon$ -constraint method, whereas a posteriori approach based upon the out-of-sample assessment is applied to derive the optimal dispatch pattern among the generated Pareto strategies. The simulation results demonstrate that: 1) the proposed integrated dispatch model achieves substantial profitability, and 2) the performance of the suggested CVaR-IGDT model is superior to conventional approaches.
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