| 引用本文: | 李政洁,撖奥洋,周生奇,等.计及综合需求响应的综合能源系统优化调度[J].电力系统保护与控制,2021,49(21):36-43. |
| LI Zhengjie,HAN Aoyang,ZHOU Shengqi,et al.Optimization of an integrated energy system considering integrated demand response[J].Power System Protection and Control,2021,49(21):36-43 |
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| 摘要: |
| 为提高系统运行的可靠性和经济性，在综合能源系统优化调度的基础上引入综合需求响应，利用不同形式能源间的相互转化关系，实现削峰填谷，提高能源利用效率。计及综合需求响应策略,建立了基于电价的电力负荷需求响应和基于激励的热负荷需求响应模型。并以运行成本最小为目标函数，提出了综合考虑供需平衡和供储能设备约束的综合能源系统调度模型。采用改进二阶振荡粒子群算法对模型进行求解。该算法在常规粒子群算法的基础上对速度迭代公式进行更新，克服了常规粒子群算法易陷入局部最优的问题。通过实际算例仿真，验证了所提出模型和求解算法的有效性。 |
| 关键词: 综合能源系统 综合需求响应 多元负荷 分时电价 优化调度 二阶振荡粒子群算法 |
| DOI：DOI: 10.19783/j.cnki.pspc.210028 |
| 分类号: |
| 基金项目:国家自然科学基金项目资助(52077108) |
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| Optimization of an integrated energy system considering integrated demand response |
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LI Zhengjie1, HAN Aoyang2, ZHOU Shengqi2, CHEN Zixuan3, ZHANG Zhisheng1
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(1. College of Electric Engineering, Qingdao University, Qingdao 266071, China; 2. State Grid Qingdao
Power Supply Company, Qingdao 266002, China; 3. School of Electrical and Electronic
Engineering, North China Electric Power University, Baoding 071003, China)
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| Abstract: |
| To improve the reliability and economy of system operation, this paper introduces an integrated demand response on the basis of the optimal scheduling of an integrated energy system. It also uses the mutual transformation relationship between different forms of energy to realize peak shaving and valley filling and improve energy use efficiency. An integrated demand response strategy is considered. A power load demand response model based on electricity price and a heat load demand response model based on incentive are established. Taking the minimum operation cost as the objective function, an integrated energy system scheduling model considering the balance of supply and demand and the constraints of energy supply and storage equipment is proposed. The improved second-order oscillatory particle swarm optimization algorithm is used to analyze the model. The algorithm updates the velocity iteration formula based on a conventional particle swarm optimization algorithm. This overcomes the problem that a conventional particle swarm optimization algorithm easily falls into a local optimum. The effectiveness of the proposed model and algorithm is verified by the simulation of an actual example.
This work is supported by the National Natural Science Foundation of China (No. 52077108). |
| Key words: integrated energy system integrated demand response multiple load TOU price optimal dispatch second order oscillatory particle swarm |
