| 引用本文: | 程前,张雪霞.计及状态量平均超限比的综合能源系统动态能量流双层优化[J].电力自动化设备,2025,45(1):76-83 |
| CHENG Qian,ZHANG Xuexia.Two-layer optimization of dynamic energy flow in integrated energy system considering average overlimit ratio of state variable[J].Electric Power Automation Equipment,2025,45(1):76-83 |
|
| 摘要: |
| 综合能源系统(IES)的最优动态能量流能够最大限度地减少系统运行成本。针对IES能量流优化过程中状态量的越限现象，引入状态量平均超限比，统一刻画状态变量的超限程度，并建立计及状态量平均超限比的电-气-热IES多目标动态时序能量流模型，以解决状态量超限惩罚代价系数选取不当所导致的优化结果偏离可行最优解的问题。为了防止蜜獾算法(HBA)对能量流的优化陷入局部极小值，建立一种基于多目标差分进化(MODE)算法的双层动态能量流优化模型，上层稳态能量流模型以IES运行成本和状态量平均超限比为优化目标，采用MODE算法求解全局空间内的Pareto非支配解集；下层动态能量流模型以IES运行成本和状态量平均超限惩罚成本的加权和为优化目标，基于Pareto解集生成HBA的初始种群决策量，通过HBA加快求解IES全局最优动态能量流的速度。通过算例仿真验证了所提模型和优化方法的有效性。 |
| 关键词: 综合能源系统 状态量平均超限比 动态能量流 双层优化模型 蜜獾算法 多目标差分进化算法 |
| DOI：10.16081/j.epae.202409028 |
| 分类号:TM73;TK01 |
| 基金项目: |
|
| Two-layer optimization of dynamic energy flow in integrated energy system considering average overlimit ratio of state variable |
|
CHENG Qian, ZHANG Xuexia
|
|
School of Electrical Engineering, Southwest Jiaotong University, Chengdu 611756, China
|
| Abstract: |
| The optimal dynamic energy flow of integrated energy system(IES) can minimize system opera-ting costs. Aiming at the phenomenon of state variables exceeding limit in the optimization process of IES energy flow, the average overlimit ratio of state variable is introduced to describe the overlimit degree of state variables uniformly, and the multi-objective dynamic time-series energy flow model of electricity-gas-thermal IES, which takes the average overlimit ratio of state variables into account, is established to solve the problem that the optimization results deviate from the feasible optimal solutions due to improper selection of the penalty cost coefficient of state variable overlimit. In order to prevent the optimization of energy flow by honey badger algorithm(HBA) from falling into local minimum, a two-layer optimization model of dynamic energy flow based on multi-objective differential evolution(MODE) algorithm is established. The upper steady-state energy flow model takes the IES operating cost and the average overlimit ratio of state variables of as optimization objectives and adopts the MODE algorithm to solve the Pareto non-dominated solution set in the global space. The lower dynamic energy flow model takes the weighted sum of the IES operating cost and the average overlimit penalty cost of state variables as the optimization objective, gene-rates the initial population decision quantity of HBA based on Pareto solution set, and speeds up the solution of IES global optimal dynamic energy flow by HBA. The effectiveness of the proposed model and optimization method is verified by numerical simulation. |
| Key words: integrated energy system average overlimit ratio of state variable dynamic energy flow two-layer optimization model honey badger algorithm multi-objective differential evolution algorithm |
