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Multi-Time Scale Control of Demand Flexibility in Smart Distribution Networks

机译:智能配电网络中需求灵活性的多时间尺度控制

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摘要

This paper presents a multi-timescale control strategy to deploy electric vehicle (EV) demand flexibility for simultaneously providing power balancing, grid congestion management, and economic benefits to participating actors. First, an EV charging problem is investigated from consumer, aggregator, and distribution system operator’s perspectives. A hierarchical control architecture (HCA) comprising scheduling, coordinative, and adaptive layers is then designed to realize their coordinative goal. This is realized by integrating multi-time scale controls that work from a day-ahead scheduling up to real-time adaptive control. The performance of the developed method is investigated with high EV penetration in a typical residential distribution grid. The simulation results demonstrate that HCA efficiently utilizes demand flexibility stemming from EVs to solve grid unbalancing and congestions with simultaneous maximization of economic benefits to the participating actors. This is ensured by enabling EV participation in day-ahead, balancing, and regulation markets. For the given network configuration and pricing structure, HCA ensures the EV owners to get paid up to five times the cost they were paying without control.
机译:本文提出了一种多时间尺度的控制策略,以部署电动汽车(EV)的需求灵活性,以同时向参与方提供电力平衡,电网拥堵管理和经济利益。首先,从消费者,聚合商和配电系统运营商的角度研究电动汽车充电问题。然后设计包括调度,协调和自适应层的分层控制体系结构(HCA),以实现其协调目标。这是通过集成从提前计划到实时自适应控制的多时间比例控制来实现的。在典型的住宅配电网中,以高EV渗透率研究了该开发方法的性能。仿真结果表明,HCA有效地利用了电动汽车带来的需求灵活性,以解决电网不平衡和交通拥挤的问题,同时最大程度地提高了参与参与者的经济利益。通过使电动汽车参与提前,平衡和监管市场,可以确保这一点。对于给定的网络配置和定价结构,HCA确保电动车所有者在不受控制的情况下获得的费用最多是其支付费用的五倍。

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