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Impact of electric vehicles as interruptible load on economic dispatch incorporating wind power

机译:电动车辆作为中断负荷对经济派遣的可中断负荷

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Since electric vehicles (EVs) can operate in two modes, charging and regeneration, the idle EVs can support the system as a reserve resource through vehicle-to-grid (V2G) technology. Suppose, an ideal aggregator who has a great number of EVs joins the grid, and its idle EVs can supply aggregator itself partial power demand. The grid makes a contract for the interruptible loads (ILs) with the aggregator, they agree on the time and capacity that the grid can reduce the aggregator's power supply, meanwhile the aggregator could manage its idle EVs to supply its demand and get the compensation from the grid. Here the grid charge the working and idle EVs during off-peak. The wind speed profile follows a Weibull distribution. Based on 24-hour load forecast curve, an optimal model, whose objective is to minimize the total cost including generating cost, reserve cost, emission cost, loss of load cost and penalty cost for not using the available wind power capacity, is proposed. This model is applied to IEEE 30-bus system. The real load fluctuations, the wind power output and the fault outage of generators are simulated hourly. Then the optimal allocation of generators and minimum total cost are obtained by particle swarm optimization (PSO). Finally, based on Monte Carlo simulation, previous steps are repeated for 1000 times to achieve the final cost and its relationship curves with both the IL capacity and compensational price.
机译:由于电动车辆(EVS)可以用两种模式操作,充电和再生,空闲EV可以通过车辆到网格(V2G)技术来支持该系统作为储备资源。假设,具有大量EV的理想聚合器加入电网,其空闲EVS可以为聚合器本身提供部分电源需求。该网格对中断负载(ILS)的合同与聚合器一致,同意电网可以减少聚合器的电源的时间和容量,同时聚合器可以管理其空闲EV,以提供其需求并从中提供需求并获得补偿网格。这里,网格在非峰值期间充电工作和空闲EV。风速型材遵循Weibull分布。基于24小时负载预测曲线,最佳模型,其目的是最大限度地减少总成本,包括产生成本,储备成本,发射成本,不使用可用风力发电能力的损失和罚金成本。该模型应用于IEEE 30-Bus系统。每小时模拟真正的负荷波动,风力输出和发电机的故障中断。然后通过粒子群优化(PSO)获得发电机和最小总成本的最佳分配。最后,基于Monte Carlo仿真,重复先前的步骤1000次以实现最终成本及其关系曲线,具有IL容量和补偿价格。

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