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计及不确定性的区域综合能源系统双层优化配置规划模型
仇知1, 王蓓蓓1, 贲树俊2, 胡楠2
1.东南大学 江苏省智能电网技术与装备重点实验室,江苏 南京 210096;2.国网南通供电公司,江苏 南通 226500
摘要:
针对综合能源系统规划运行时缺乏对负荷、可再生能源预测误差和购能价格波动不确定性的考虑,构建了基于粒子群优化-区间线性规划的双层优化模型,用于求解计及不确定性的综合能源系统规划问题。为了说明所提优化配置模型能够显著提高系统运行的灵活性,给出了评价系统参与需求响应项目的潜力指标,量化分析了系统在响应电网削负荷指标和应对购能价格变化方面的优势。算例结果不仅验证了所提模型的有效性和可行性,还表明了在能源互联替代的背景下,天然气价格和电负荷的波动直接影响能源服务公司的收益区间,可通过所提模型优化配置各类储能设备以提高能源利用率、抑制系统运营收益的波动。
关键词:  综合能源系统  能量枢纽  规划  不确定性  能源服务公司  区间线性规划  双层优化  模型
DOI:10.16081/j.epae.201908005
分类号:TM715
基金项目:江苏省智能电网技术与装备重点实验室课题项目(广义需求侧资源与电网互动推演仿真平台研究)
Bi-level optimal configuration planning model of regional integrated energy system considering uncertainties
QIU Zhi1, WANG Beibei1, BEN Shujun2, HU Nan2
1.Jiangsu Key Laboratory of Intelligent Power Grid Technology and Equipment, Southeast University, Nanjing 210096, China;2.State Grid Nantong Power Supply Company, Nantong 226500, China
Abstract:
Aiming at the lack of consideration of the uncertainties of load, prediction error of renewable ener-gy and energy purchase price fluctuations, a bi-level optimization model based on particle swarm optimization and interval linear programming is proposed to solve the planning problem of integrated energy system with uncertainties. In order to show that the proposed optimal configuration model can significantly improve the flexibility of system operation, the potential indicators for evaluating the system participating in the demand response projects are given, and the advantages of system in responding to the load reduction targets and energy price changes are quantitatively analyzed. The results of numerical example not only validate the validity and feasibility of the proposed model, but also show that under the background of energy interconnection and substitution, the fluctuations of natural gas price and power load directly affect the income range of energy service companies, and the proposed model can optimize the allocation of various energy storage equipment to improve the energy utilization efficiency and suppress the system operation income fluctuations.
Key words:  integrated energy system  energy hub  planning  uncertainty  ESCO  interval linear programming  bi-level optimization  models

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