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Demand management using utility based real time pricing for smart grid with a new cost function

机译：使用基于公用事业的实时定价的需求管理功能，为智能电网提供新的成本功能

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Considering the time-varying power consumption of users and cost of generation over a day, demand side management (DSM) has become essential to meet the excessive need of users with the limited source of power. In this paper, we propose a utility based optimal Real-Time Pricing (RTP) mechanism for the future smart grid communication systems such that the electricity price corresponds to the optimum system welfare. Here, we formulate a distributed algorithm which is based on the two-way communication among users, decision maker, and energy provider through the exchange of control messages, and determine the optimal price maintaining the equality between the total demand and the offered generation. We also propose a novel cost function for energy provider exhibiting how it reduces the impact of the change in user number to electricity price, unlike a previously proposed cost function. Simulation results confirm that the proposed algorithm is favorable for both the users and energy provider in terms of electricity price and generation cost respectively. It is also demonstrated that our new cost function makes the RTP algorithm user-adaptive and offers a better welfare to both the users and the energy provider.
机译：考虑到用户随时间变化的功耗和一天中的发电成本，需求侧管理（DSM）对于满足有限电源用户的过分需求已变得至关重要。在本文中，我们为未来的智能电网通信系统提出了一种基于效用的最优实时定价（RTP）机制，以使电价与最优系统福利相对应。在这里，我们制定了一种分布式算法，该算法基于用户，决策者和能源提供者之间通过控制消息的交换进行双向通信，并确定维持总需求与所提供发电量相等的最优价格。我们还为能源供应商提出了一种新颖的成本函数，与以前提出的成本函数不同，该函数展示了它如何减少用户数量变化对电价的影响。仿真结果表明，该算法无论从电价还是发电成本上都对用户和能源供应商均有利。还证明了我们的新成本函数使RTP算法具有用户适应性，并为用户和能源提供者提供了更好的福利。

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