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首页> 外文期刊>International journal of hydrogen energy >Risk-constrained probabilistic optimal scheduling of FCPP-CHP based energy hub considering demand-side resources
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Risk-constrained probabilistic optimal scheduling of FCPP-CHP based energy hub considering demand-side resources

机译：考虑需求侧资源的基于FCPP-CHP能量中心的风险约束概率最佳调度

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摘要

Renewable energy sources (RES) with sharing a large percentage of future energy generation capacities play an essential role in the decarbonization of the future electricity and thermal networks as well as transportation sectors. However, the uncertainties in their outputs make some difficulties in making operational decisions. Hydrogen energy plays a considerable role in this concept. Besides, energy hubs (EHs) provide an efficient and reliable framework for gathering multi-type energy carriers. This paper optimally schedules the operating of the EH and decreases the emission cost, considering the electrical and thermal demand response (DR) program in a probabilistic environment. Besides plug-in electric vehicles (PEVs) and a complete model of hydrogen-based renewable energy sources are presented in the EH. Taking into account uncertainties of electrical/thermal energy markets real-time prices, customers' energy demand, and energy production of RESs into account, various scenarios are generated using the Monte Carlo simulation technique. Next, an efficient method is used to reduce the number of the scenario to make the optimization problem computable and fast. In order to reduce the risk of encountering high operating costs, the conditional value at risk (CVaR) technique is used to manage the associated risk. Simulation results show the efficiency of the proposed method in decreasing the operational cost and managing the risk of encountering unfavorable states. (C) 2020 Hydrogen Energy Publications LLC. Published by Elsevier Ltd. All rights reserved.
机译：可再生能源（RES）共享未来的能源生成能力的较大百分比在未来电力和热网络的脱碳中起重要作用以及运输部门。但是，其产出中的不确定性在制定业务决策时会产生一些困难。氢能在这一概念中起着相当大的作用。此外，能量集线器（EHS）为收集多型能量载体提供了一种有效可靠的框架。本文最佳地调度EH的操作，并考虑概率环境中的电气和热需求响应（DR）程序，降低发射成本。除了插入式电动车（PEVS）和eH的完整氢气可再生能源的完整模型外。考虑到电气/热能市场的不确定性，实时价格，客户的能源需求和RESS的能源生产考虑，使用Monte Carlo仿真技术产生了各种场景。接下来，使用有效的方法来减少方案的数量，以使优化问题可计算和快速。为了降低遇到高运行成本的风险，风险（CVAR）技术的条件值用于管理相关的风险。仿真结果表明，提出的方法在减少运营成本和管理遇到不利国家的风险时的效率。 （c）2020氢能源出版物LLC。 elsevier有限公司出版。保留所有权利。

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