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Multi-Energy Simulation of a Smart Grid with Optimal Local Demand and Supply Management

机译:具有最佳本地需求和供应管理的智能电网的多能量仿真

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A simulation approach of a smart grid by cooperative bargaining is presented in this paper. Each participant of the smart grid determines its optimal schedule to meet its power and heating demand at minimal costs employing solar panels, fuel cells and batteries. This is done by solving a quadratic optimisation problem which takes the energy prices and the available devices into account. The energy prices are related to the demand and supply in the smart grid, so that a lower demand yields lower prices. The cooperative bargaining game is used to tune the participants’ optimal solution to obtain a Nash equilibrium. The computed solutions of the participants are validated against the capacities and structure of the smart grid by solving a multi-commodity flow problem. The presented model features multiple types of energy, so that they may be substituted to meet the participants’ demand. Furthermore, the participants may also act as supplier and not only as consumer, which allows decentralised generation of energy. The approach is validated in several experiments where effects like negative energy prices if generated energy exceeds the smart grid’s total demand and peak-shaving with even small-capacity batteries are exhibited.
机译:提出了一种通过协同谈判对智能电网进行仿真的方法。智能电网的每个参与者都通过使用太阳能电池板,燃料电池和电池,以最低的成本确定其最佳计划,以满足其电力和供热需求。这是通过解决二次优化问题来完成的,该问题考虑了能源价格和可用设备。能源价格与智能电网中的需求和供应有关,因此较低的需求会产生较低的价格。合作讨价还价博弈用于调整参与者的最优解,以获得纳什均衡。通过解决多商品流问题,针对智能电网的容量和结构验证了参与者的计算出的解决方案。提出的模型具有多种能量类型,因此可以替代它们以满足参与者的需求。此外,参与者还可以充当供应商,而不仅是消费者,这可以分散发电。该方法已在多个实验中得到了验证,其中,如果产生的能量超过智能电网的总需求,并且即使使用小容量电池,也会表现出峰值削峰等负面能量价格的影响。

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