低回报需求侧管理智能控制器代理的设计

Pegah Yazdkhasti, C. Diduch
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引用次数: 0

摘要

随着风能、太阳能等可再生能源在常规电网中的高度渗透,发电侧的快速波动带来了新的挑战。恒温控制负荷的直接负荷控制在需求侧管理(DSM)中发挥着重要作用,以应对发电的不确定性和可变性。为此,系统运营商(SO)需要一个可靠的需求预测,以及它可以转移多少;为了产生可达到的理想设定值来重塑需求跟随发电方。本文的重点是设计一个智能代理,该智能代理使用基于模型和无模型结构的混合系统来预测可控负荷及其需要重塑的容量,并遵循SO的调度指令,同时最小化控制动作的回报效应并保持客户的舒适性。该系统的主要优点是:1)实时模型创建;因此,不需要历史数据进行训练,2)无模型控制器可以自动适应系统的变化,3)它可以作为一个即插即用组件在DSM程序中使用。为了评估所提出的控制器的性能,开发了一个数值模拟器,并将控制器应用于仿真引擎上以遵循任意期望的功率分布。结果表明,该系统可以在不到5分钟的时间内完成调度指令,稳态误差小于5%,可以忽略不计。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Design of a Smart Controller Agent for Demand-Side Management with Low Payback Effect
With high penetration of renewable resources such as wind and solar into conventional electric grid, new challenges are introduced due to the rapid fluctuation on the generation side. Direct load control of thermostatically controlled loads can play a significant role in demand side management (DSM) to cope with the uncertainties and variabilities of the generation. For this purpose, the system operator (SO) requires a reliable forecast of the demand and how much it can be shifted; in order to produce attainable desirable set points to reshape the demand to follow generation side. The focus of this paper is on designing a smart agent that uses a hybrid system of a model-based and a model-free structure to forecast the controllable load and its capacity to be reshaped, and follow the dispatch instructions of the SO, while minimizing the payback effect of the control actions and maintaining customers’ comfort. The main advantages of the proposed system are: 1) real-time model creation; thus, no need for historical data for training, 2) model free controller can automatically adapt to the changes in the system, 3) it can be used as a plug & play component in a DSM program. To evaluate the performance of the proposed controller, a numerical simulator was developed, and the controller was applied over the simulation engine to follow arbitrary desired power profiles. It was observed that the system can follow the dispatch command in less than 5 minutes with a negligible steady state error (less than 5%).
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