高比例可再生能源不断并入电力系统带来了波动性和不确定的问题，为了维持电力系统的稳定可靠运行，电力辅助服务起到了关键的作用。区域综合能源系统耦合了冷/热/电能，内部有冷热电三联供（CCHP），储能系统，以及可再生能源等一系列资源。在维持内部供能平衡的基础上，区域综合能源系统如何向上级电网提供辅助成为了一个值得研究的问题。 首先，本文完成了区域综合能源系统物理和数学模型的构建，介绍了电力市场结构和盈利机制。对基于绩效的调频机制进行了详细研究，完成了对调频信号的基本处理，得到了相应的参数。 其次，本文提出了考虑备用服务收入和负荷不确定性的区域综合能源系统的鲁棒优化日前经济调度模型。除了满足区域综合能源系统的内部冷/热/电负荷要求外，CCHP还为上级电网提供额外的备用服务以获利。同时，用区间法表示热负荷和冷负荷的不确定性，并通过鲁棒优化求解问题。 最后，本文提出提供多种辅助服务的区域综合能源系统随机优化日前经济调度模型。风力发电机组和光伏机组参与区域综合能源系统的内部供应平衡，CCHP参与冷/热/电供需平衡。在此基础上，三者同时向上级电网提供额外的备用服务以获利。同时，储能系统负责区域综合能源系统内部的能源供应平衡和削峰填谷，并为上层电网提供调频辅助服务以赚取利润。热负荷和冷负荷服从正态分布，由蒙特卡罗模拟法生成了200个场景，并通过随机优化求解问题。 综上所述，本文的目的在于对区域综合能源系统向上级电网提供辅助服务的能力展开研究，同时将系统内部的冷/热负荷的不确定性纳入考虑范围，所建立的区域综合能源系统鲁棒优化和随机优化日前经济调度模型的有效性和可行性得到了验证。该研究对维持电力系统的可靠运行意义深远。

The high proportion of renewable energy integrated into the power system brings the problem of volatility and uncertainty, and the power ancillary services play a key role in maintaining the stable operation of the entire power system with reliability. Regional integrated energy system (RIES) couples cold/heat/electricity, and contains a series of resources such as Combined Cooling, Heating Power (CCHP), energy storage system (ESS), and renewable energy. On the basis of maintaining the internal energy supply balance, how can RIES provide ancillary services to the upper grid has become a problem worth studying.Firstly, this dissertation completes the construction of the physical and mathematical model of the RIES, and introduces the structure and profit mechanism of the electricity market. The performance-based regulation mechanism is studied in detail, the basic processing of the regulation signal is completed, and the corresponding indexes are obtained for the further work in chapter 3 and 4.Secondly, this dissertation proposes a robust optimization day-ahead economic dispatch model for RIES considering the reserve revenue and load uncertainties. In addition to meeting the internal cold/heat/electricity load requirements of RIES, CCHP provides additional reserve service to the upper grid for profit. At the same time, the interval method is used to express the uncertainty of heating/cooling load, and the problem is solved by robust optimization (RO).Finally, this dissertation establishes a stochastic optimization day-ahead economic dispatch model for RIES that provides multiple ancillary services. Wind turbines and PV participate in the internal supply balance of the RIES. CCHP participates in the cooling/heating/electricity supply and demand balance. On this basis, all three equipment simultaneously provide reserve service to the upper grid for profit. At the same time, the ESS is responsible for energy supply balancing and peak shaving and valley filling within the RIES, and provides frequency regulation services for the upper grid to earn profits. The heating/cooling load follows a normal distribution. 200 scenarios are generated by Monte Carlo simulation and solved by stochastic optimization (SO).In summary, the purpose of this dissertation is to study the ability of the RIES to provide ancillary services to the upper grid. Meanwhile, the cooling/heating load uncertainty within the system is taken into account. The validity and feasibility of the established robust optimization and stochastic optimization day-ahead economic scheduling model of the RIES is verified. The research has far-reaching implications for maintaining the reliable operation of the power system.