基于需求侧调峰的农村电采暖设备负荷优化控制策略

随着中国北方地区农村清洁能源供暖项目的大力推广,冬季燃煤取暖污染问题得到了极大的改善。但是大规模煤改电设备的使用,对低压配电网供电可靠性提出了新的挑战。挖掘电采暖负荷的需求响应潜力,激励用户主动参与电网调峰,是实现资源优化配置和提高配电网供电质量的有效措施之一。该文为了激励用户主动参与调峰,实现负荷削峰填谷,提出了基于需求侧调峰的农村电采暖设备负荷优化控制策略,设计了第三方公司代理"煤改电"用户参与调峰市场的市场交易模式,在此交易模式下建立了考虑调峰需求和用户舒适度的负荷优化控制模型,并在模型中引入用户分类补偿机制,提高用户参与调峰的主动性。以北京平谷区电采暖用户负荷数据为例进行仿真分析,结果表明,该文所提方法可以在满足用户室温需求的情况下,实现负荷削峰填谷的作用,分类补偿机制对用户主动参与调峰起到了激励作用,使用户和代理公司均获得收益。

Optimal load control strategy of rural electric heating equipments based on demand side peak load regulation

With the implementation of clean energy heating project in rural areas of northern China,the pollution of coal-fired heating in winter has been greatly improved.However,the use of large-scale electric heating equipment put forward new challenges to the power supply reliability of low-voltage distribution network.Especially in rural power grid,the load is heavy in winter and low in other seasons.It is one of the effective measures to achieve optimal resource allocation and improve the power supply quality of the distribution grid to exploit the demand response potentialities of electric heating loads,and motivate electric heating loads to actively respond to demand response programs(DRP)for peak-load shifting.Therefore,a load optimal control strategy for rural electric heating equipments based on demand side peak load regulation was proposed in this paper.A market transaction model was designed for third-party agency companies to represent coal-to-electricity users in the peak shaving market.The agency company made the centrally control strategies of electric heating users’equipment according to the peak shaving volume and corresponding price obtained from the peak shaving market bidding.The electric heating users were classified based on the controllability of each user by the agency company.Each kinds of users could get different compensation price to encourage them to participate in the demand response programs for peak-load shifting.In this market model,a multi-objective optimization model was established to control the users’air source heat pump.The goals of the optimization model were to meet the user's temperature demands to the maximum extent and to maximize the benefit of the agent company.Meanwhile,user's comfort requirements for indoor temperature were considered in this model,and the user classification compensation mechanism was introduced to improve the user's initiative to participate in peak load regulation.Taking the load data of electric heating users in Pinggu District of Beijing as an example,the simulation analysis was carried out.The results show that the total load reduction of all electric heating equipment was 159.773 kWh,there was no over-control for anyone user,the load reduction of each user fluctuated around average reduction of 7.989 kWh,the peak valley of the user's power consumption curve was changed,the optimal control strategy proposed in this paper played the role of peak load reduction and valley filling,which can relieve the pressure of the upper power grid during peak load period.The indoor temperature of the users was(18±1)℃,which meet the demand of comfortable temperature for heating in winter.Compared with the target of not considering the benefit,the one-day compensation cost of the agency company was saved 31.9%,and the users with the highest degree of control got the most compensation income,the peak load regulation strategy could encourage the users to participate in the peak load regulation actively.