| 引用本文: | 蔡紫婷,彭敏放,沈美娥.考虑需求侧资源的智能小区综合能源日前优化调度[J].电力自动化设备,2021,41(3): |
| CAI Ziting,PENG Minfang,SHEN Mei'e.Day-ahead optimal scheduling of smart integrated energy communities considering demand-side resources[J].Electric Power Automation Equipment,2021,41(3): |
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| 摘要: |
| 针对化石能源过度消耗和环境污染问题日益严重的情况，将需求侧资源利用纳入考虑范畴，进行供能侧与用户侧相结合的智能小区综合能源日前优化调度研究。在供能侧，建立接入光伏发电和风力发电的冷热电联供系统，考虑多能互补方式并提出一种增大可再生能源就地消纳的控制策略；在用户侧，提出一种较为精细的负荷分类方法，充分考虑家用储能和电动汽车的充放电功能、用电设备频繁启停行为、电动汽车出行计划安排以及关联设备运行时间约束，并对运行时间具有不可控性的冷热负荷进行优化分析。通过引入供能单价，将供能侧和用户侧相结合进行日前优化调度。算例仿真结果表明，所提方法能有效降低双侧成本，减少环境污染和降低电负荷峰谷差。 |
| 关键词: 综合能源 智能小区 冷热电联供 多能互补 需求响应 日前调度 |
| DOI：10.16081/j.epae.202101027 |
| 分类号:TM73;TK01 |
| 基金项目:国家自然科学基金资助项目(61973107,61472128) |
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| Day-ahead optimal scheduling of smart integrated energy communities considering demand-side resources |
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CAI Ziting1, PENG Minfang1, SHEN Mei'e2
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1.School of Electrical and Information Engineering, Hunan University, Changsha 410082, China;2.School of Computer Science, Beijing Information Science & Technology University, Beijing 100192, China
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| Abstract: |
| In view of the excessive consumption of fossil energy and the increasingly severe environmental pollution, the day-ahead optimal scheduling of smart integrated energy communities combined energy supply side and demand side is studied, in which the utilization of demand-side resources are considered. On the supply side, a combined cooling, heating and power system with photovoltaic and wind power generation is demonstrated. A control strategy is proposed to increase the accommodation of local renewable energy considering the multi-energy complementary way. On the demand side, a refined load classification method is proposed, which considers the charging and discharging functions of household energy storages and electric vehicles, the frequent starting and stopping of electric equipment, travel scheme of electric vehicles, and operating time constraints of related equipment. Moreover, the operation decisions are analyzed for cooling and heating demands with uncontrollable running time. By introducing the unit price of energy supply, the supply side and demand side are combined to carry out the day-ahead optimal scheduling. Simulative results demonstrate that the proposed method can effectively reduce the cost of both supply and demand sides, the environmental pollution and the peak-valley difference of electric demands. |
| Key words: integrated energy smart communities combined cooling, heating and power multi-energy complementary demand response day-ahead scheduling |
