在全球变暖的背景下，提高电力系统中可再生能源占比是降低碳排放、实现碳达峰与碳中和的关键路径。可再生能源的出力具有很强的不确定性，为电力系统的安全稳定运行带来了重大挑战。为此，系统运营商需通过备用市场出清足够的备用资源，以应对电网可能的故障与不确定性。而备用又通过发电机组与输电线路的容量限制与能量市场耦合，因此国内外多采用能量-备用联合出清模式。但已有模型依赖经验性备用需求与分区，可能无法最小化期望运行成本，在备用成本的分摊问题上，也有待进一步研究。针对以上问题，本文提出了基于场景模拟的电能量-备用联合优化模型，并提出了相应的定价结算方法；同时基于所提出的优化模型与市场机制，建立了若干重要的市场性质。本研究可以为我国乃至世界范围内的电力市场与辅助服务市场建设提供参考，主要内容包括：(1)本研究首先建立了单时段下基于场景模拟的电能量-备用联合优化模型，将系统中可能的故障与负荷和可再生能源功率波动建模为一系列非基态场景，并在目标函数中考虑系统在所有场景下总体期望成本，同时考虑所有场景下再调节后的传输容量约束，保证备用的可调用性。(2)进一步的，基于(1)中建立的模型，本研究建立了对应的电能量与备用的定价方法，并建立了分为前瞻(ex-ante)阶段与后顾(ex-post)阶段的市场结算机制，同时对不确定性资源的结算机制进行了重点分析讨论。(3)基于(1)与(2)中所提联合优化模型与市场机制，本研究建立了若干重要市场性质，包括电能量的节点统一定价、备用与再调节的节点统一定价、个体理性、发电机的成本回收以及系统运营商的利润充裕等性质。 (4)此外，本研究建立了多时段下的电能量-备用联合优化模型，作为(1)中所提出的单时段模型的延伸，考虑了多时段下备用与电能量爬坡具有的耦合关系，并分析了多时段模型对应的定价结算机制。综上所述，本文重点研究了电能量与备用的联合优化模型与市场机制的设计问题，所提出的优化模型有效降低了系统成本，降低了系统的备用出清总量，并保证了备用的可调用性；同时，基于所提出的出清模型与市场机制，可以建立若干重要市场性质。

To reduce carbon emission and achieve carbon neutral, it is important to transform the energy structure to more renewable generations. However, the system's secure and reliable operation also faces much risk with the increasing uncertain and intermittent renewable penetrations. To handle this, the system operator will procure reserve from reserve market to protect the system from possible contingencies and loads/renewable power fluctuations. Reserve and energy are strongly coupled both in the generation capacity limits and the transmission capacity limits, therefore the co-optimization of energy and reserve is wildly adopted in worldwide market practice. However, the current deterministic co-optimization model highly relies on the empirical reserve zone divisions and zonal reserve requirements and does not consider possible re-adjustment costs in non-base scenarios. In addition, the allocation principles of reserve procurement cost are not clear. Considering the above problems, this dissertation proposes a scenario-oriented co-optimization model for energy and reserve. In addition, the associated pricing approach and market settlement process are proposed. Moreover, based on the proposed model and the associated market mechanism, some important market properties are established, including locational uniform pricing, individual rationality, cost recovery and revenue adequacy. This dissertation can provide references for the construction of electricity market and ancillary service market in China and other countries. Following are explicit contents: (1) First, a single-period scenario-oriented energy-reserve co-optimization model is formulated, these scenarios will correspond to possible contingencies or load/renewable generation fluctuations, or their combinations. Within the proposed model, the objective function includes the base-case energy and reserve bid-in cost and the expectation of possible re-adjustment costs in all non-base scenarios to minimize the expected system total cost. In addition, reserve cleared from each generator is equal to its biggest generation re-dispatch among all non-base scenarios to optimize the reserve requirement endogenously, and the deliverability of reserve is ensured by considering the transmission capacity limits in all non-base scenarios. (2) In addition, the margin prices of loads, generations and reserve are derived by applying the envelope theorem on load parameters and fixed generation and reserve variables. On top of that, a two-stage market settlement process is also proposed. (3) Moreover, based on the proposed model and the associated market mechanism, some desired market properties are established, including locational uniform pricing for energy and the combination of reserve and re-dispatch, individual rationality, cost recovery for generators, and revenue adequacy for the system operator. (4) Furthermore, a multi-period co-optimization model is formulated as an extension of the single-period model, where the coupling of reserve and ramping in multi-period operation is considered. In addition, the pricing approach and settlement process associated with the multi-period model are also proposed. In conclusion, this dissertation focuses on the joint procurement and pricing of energy and reserve. The co-optimization model for energy and reserve can ensure the deliverability of reserve and minimize the expected system total cost, and some desired market properties can be established based on the proposed pricing approach and settlement process.