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Energy trading between microgrids towards individual cost and social welfare optimization

机译:微电网与个人成本和社会福利优化之间的能量交易

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High penetration of renewable energy source makes microgrid (MGs) be environment friendly. However, the stochastic input from renewable energy resource brings difficulty in balancing the energy supply and demand. Purchasing extra energy from macrogrid to deal with energy shortage will increase MG energy cost. To mitigate intermittent nature of renewable energy, energy trading and energy storage which can exploit diversity of renewable energy generation across space and time are efficient and cost-effective methods. But a storage with large capacity will incur additional cost. In addition, due to MG participating energy trading as prosumer, it calls for an efficient trading mechanism. Therefore, this paper focuses on the problem of MG energy management and trading. Energy trading problem is formulated as a stochastic optimization one with both individual profit and social welfare maximization. Firstly a Lyapunov optimization based algorithm is developed to solve the stochastic problem. Secondly the double-auction based mechanism is provided to attract MGs' truthful bidding for buying and selling energy. Through theoretical analysis, we demonstrate that individual MG can achieve a time average energy cost close to offline optimum with tradeoff between storage capacity and energy trading cost. Meanwhile the social welfare is also asymptotically maximized under double auction. Simulation results based on real world data show the effectiveness of our algorithm.
机译:可再生能源的高渗透使微电网(MGS)为环境友好。然而,可再生能源资源的随机输入带来了平衡能量供应和需求的困难。从宏格栅购买额外的能量以处理能源短缺将增加MG能源成本。为了减轻可再生能源的间歇性,能源交易和能量存储,可以利用空间和时间的可再生能源产生的多样性是有效且具有成本效益的方法。但具有大容量的存储将产生额外的成本。此外,由于MG参与能源交易作为Prosumer,它可以呼吁有效的交易机制。因此,本文侧重于MG能源管理和交易问题。能源交易问题被制定为随机优化,具有个人利润和社会福利最大化。首先,开发了基于Lyapunov优化的算法来解决随机问题。其次,提供了基于双拍卖的机制,以吸引MGS的竞标购买和销售能源。通过理论分析,我们证明各个MG可以在储存能力和能量交易成本之间的权衡中实现接近离线的时间平均能源成本。与此同时,社会福利在双重拍卖中也是渐近最大化的。基于真实世界数据的仿真结果显示了我们算法的有效性。

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