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Two-stage stochastic demand response in smart grid considering random appliance usage patterns

机译:考虑随机设备使用模式的智能电网中的两阶段随机需求响应

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摘要

By effectively adjusting the appliance usage patterns of customers, demand response (DR) is expected to bring significant economic and environmental benefits to the future smart grid. Two kinds of appliances should be considered for DR, i.e. shiftable appliances such as dishwashers and laundry machines, and non-shiftable appliances such as lights and stoves. Although the shiftable appliances can be well controlled by energy management systems, the random usage patterns of non-shiftable appliances will result in uncertainties to electrical demands and thus, affect the efficiency and reliability of smart grid operation. A two-stage stochastic programming problem is formulated, for which the distribution system operation cost is minimised in the first stage, by considering various distribution system operation constraints. The scheduling of shiftable appliances is optimised in the second stage, by considering the random usage patterns of non-shiftable appliances. To reduce the computational complexity caused by a large number of home appliances in distribution systems, scenario reduction technique is applied to reduce the number of possible scenarios while still retaining the essential features of the original scenario set. Extensive simulations are performed to evaluate the proposed DR scheme in IEEE 33-bus and 119-bus test distribution systems based on real appliance usage pattern data.
机译:通过有效地调整客户的设备使用模式,需求响应(DR)有望为未来的智能电网带来巨大的经济和环境效益。对于灾难恢复,应考虑两种设备,即洗碗机和洗衣机之类的可移动设备,以及电灯和火炉之类的不可移动设备。尽管可移动设备可以通过能源管理系统很好地控制,但是不可移动设备的随机使用模式将导致电力需求的不确定性,从而影响智能电网运行的效率和可靠性。提出了一个两阶段随机规划问题,通过考虑各种配电系统的运行约束,在第一阶段将配电系统的运行成本降至最低。通过考虑不可移动设备的随机使用模式,在第二阶段优化可移动设备的调度。为了减少分配系统中大量家用电器引起的计算复杂性,应用了场景缩减技术来减少可能场景的数量,同时仍保留原始场景集的基本特征。基于真实的设备使用模式数据,进行了广泛的仿真,以评估IEEE 33总线和119总线测试分配系统中的拟议DR方案。

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