In this paper, a robust scheduling model is proposed for combined heat and power (CHP)-based microgrids using information gap decision theory (IGDT). The microgrid under study consists of conventional power generation as well as boiler units, fuel cells, CHPs, wind turbines, solar PVs, heat storage units, and battery energy storage systems (BESS) as the set of distributed energy resources (DERs). Additionally, a demand response program (DRP) model is considered which has a successful performance in the microgrid hourly scheduling. One of the goals of CHP-based microgrid scheduling is to provide both thermal and electrical energy demands of the consumers. Additionally, the other objective is to benefit from the revenues obtained by selling the surplus electricity to the main grid during the high energy price intervals or purchasing it from the grid when the price of electricity is low at the electric market. Hence, in this paper, a robust scheduling approach is developed with the aim of maximizing the total profit of different energy suppliers in the entire scheduling horizon. The employed IGDT technique aims to handle the impact of uncertainties in the power output of wind and solar PV units on the overall profit.

中文翻译：

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存在不确定分布式能源的热电联产微电网的风险规避调度

在本文中，使用信息间隙决策理论（IGDT）为基于热电联产（CHP）的微电网提出了一种鲁棒的调度模型。正在研究的微电网包括常规发电以及锅炉装置、燃料电池、CHP、风力涡轮机、太阳能光伏、蓄热装置和作为分布式能源 (DER) 的电池储能系统 (BESS)。此外，还考虑了在微电网每小时调度中具有成功性能的需求响应程序（DRP）模型。基于 CHP 的微电网调度的目标之一是提供消费者的热能和电能需求。此外，另一个目标是受益于通过在高能源价格区间向主电网出售剩余电力或在电力市场电价低时从电网购买而获得的收入。因此，在本文中，开发了一种稳健的调度方法，目的是在整个调度范围内最大化不同能源供应商的总利润。采用的 IGDT 技术旨在处理风能和太阳能光伏机组输出功率的不确定性对整体利润的影响。