Generation scheduling decision-making of power systems with renewable energy and energy storage (ES) is a multistage stochastic programming problem in nature, in which unit commitment (UC) decisions have to be made one day ahead before uncertainties are revealed, and hourly economic dispatch (ED) decisions are successively determined when real uncertainty realizations are observed gradually (i.e., nonanticipativity). To this end, inappropriate ED decisions at current hour may cause infeasibility of future ED decisions (i.e., robustness). Thus, how to properly schedule thermal unit outputs and ES charging/ discharging power against uncertainties becomes an important and urgent issue. In this paper, two mixed-integer linear programming (MILP) methods are proposed to solve the scheduling problem of thermal units and ESs with uncertainties while ensuring solution robustness and nonanticipativity: explicit and implicit decision methods. Specifically, explicit decision method directly assumes affine policies between decision variables and uncertainty realizations; implicit decision method explores safe ranges of thermal unit outputs and ES state-of-charge (SOC) levels to guarantees feasibility of future ED solutions. Both methods can guarantee the nonanticipativity and robustness of multistage solutions. Numerical tests illustrate effectiveness of the proposed methods.

中文翻译：

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具有可再生能源和储能的多级输电约束单位承诺：隐式和显式决策方法

具有可再生能源和能量存储（ES）的电力系统的发电调度决策本质上是一个多阶段随机规划问题，其中必须在揭示不确定性和每小时进行一次经济调度之前提前一天做出单位承诺（UC）决策（ED）决策是在逐渐观察到实际不确定性实现时（即，非预期性）相继确定的。为此，当前时间的不适当的ED决策可能导致将来的ED决策不可行（即，健壮性）。因此，如何适当地调度热单元输出和ES充/放电功率以克服不确定性成为重要而紧迫的问题。在本文中，提出了两种混合整数线性规划（MILP）方法来解决具有不确定性的热单元和ES的调度问题，同时确保解决方案的鲁棒性和非预期性：显式和隐式决策方法。具体而言，显式决策方法直接在决策变量和不确定性实现之间采用仿射策略。隐式决策方法探讨了热单元输出的安全范围和ES荷电状态（SOC）级别，以保证未来ED解决方案的可行性。两种方法都可以保证多阶段解的非预期性和鲁棒性。数值测试表明了所提出方法的有效性。显式决策方法直接在决策变量和不确定性实现之间采用仿射策略。隐式决策方法探讨了热单元输出的安全范围和ES荷电状态（SOC）级别，以保证未来ED解决方案的可行性。两种方法都可以保证多阶段解的非预期性和鲁棒性。数值测试表明了所提出方法的有效性。显式决策方法直接在决策变量和不确定性实现之间采用仿射策略。隐式决策方法探讨了热单元输出的安全范围和ES荷电状态（SOC）级别，以保证未来ED解决方案的可行性。两种方法都可以保证多阶段解的非预期性和鲁棒性。数值测试表明了所提出方法的有效性。