Coordinated operation of various energy sources has drawn the attention of many power producers worldwide. In this paper, a Concentrating Solar Power Plant (CSPP) along with a wind power station, a Compressed Air Energy Storage (CAES) unit, and a Demand Response Provider (DRP) constitute the considered Hybrid Power Producer (HPP). In this regard, this paper deals with the optimal participation of the mentioned HPP in the Day-Ahead (DA), and intraday electricity markets by benefiting from the joint configuration of all accessible resources. To attain risk-averse strategies in the suggested model, Conditional Value-at-Risk (CVaR) based on the $\epsilon$ -constraint technique is employed, while its efficiency is validated compared to the previously applied method to such problems. On the whole, the main contributions of this work lie in: 1) proposing a novel model for optimal behavior of a CSPP-based HPP in DA, and intraday markets using a three-stage decision-making architecture, and 2) developing a bi-objective optimization framework to improve the functioning of the risk-constrained algorithm. Simulation results reveal that taking advantage of the CSPP in the intraday market, and coordinated operation of all resources not only enhance the profitability of the system but also lessen the associated risk compared to the previous models.

中文翻译：

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日前和盘中市场中混合动力生产商的最优行为：基于双目标CVaR的方法

各种能源的协调运行已引起全球许多电力生产商的关注。在本文中，集中式太阳能发电厂（CSPP）以及风力发电站，压缩空气储能（CAES）单元和需求响应提供者（DRP）构成了被认为是混合动力生产商（HPP）。在这方面，本文通过受益于所有可访问资源的联合配置，探讨了上述HPP在日前（DA）和日内电力市场中的最佳参与。为了在建议的模型中获得规避风险的策略，基于风险的条件风险价值（CVaR）$ \ epsilon $ 使用了约束技术，而与以前针对此类问题的方法相比，它的效率得到了验证。总体而言，这项工作的主要贡献在于：1）提出了一种基于CSPP的HPP在DA中的最佳行为的新颖模型，并使用三阶段决策架构来提出当日市场，以及2）开发了一个双向模型。目标优化框架，以改善风险受限算法的功能。仿真结果表明，与以前的模型相比，在日间市场中利用CSPP的优势，并协调所有资源的运作，不仅可以提高系统的盈利能力，而且可以降低相关的风险。