Real-time pricing in a Smart Grid scenario allows consumers to move their time-insensitive loads to off-peak hours and maintains the power balance between the demand side and supply side. This scheme has a strong impact on customer behaviour, network operations, and overall control of the power grids. In this proposed work, Real coded Genetic Algorithm (RGA) is used to develop a Day Ahead Real-Time electricity-Pricing (DARTP) model. The established scheme maximizes the benefit of the energy provider without reducing the minimum daily consumption rate, the consumer response to the reported electricity prices, and the constraints of distribution networks. The RGA results demonstrate that the calculated optimal prices bring higher benefits for consumers and energy providers than the posting of market prices directly to consumers on the day ahead. The proposed setup is tested with a 32-node distribution bus system. Simulation results reveal that the deployed methodology will help the participants to shift the peak load time to base load time by receiving optimal DARTP, thereby reducing excessive consumption made during the instance of peak load. The obtained DARTP will be sent to the consumers through the deployment of an Advanced Metering System.

智能电网方案中的实时定价使消费者可以将对时间不敏感的负载转移到非高峰时段，并保持需求侧和供电侧之间的电力平衡。该方案对客户的行为，网络运营以及对电网的总体控制有很大的影响。在这项拟议的工作中，实数编码遗传算法（RGA）用于开发日前实时实时电价（DARTP）模型。既定的方案可在不降低最低每日耗电率，消费者对所报告电价的响应以及配电网络约束的前提下，最大限度地提高能源供应商的利益。RGA结果表明，与在前一天直接向消费​​者发布市场价格相比，计算出的最优价格为消费者和能源供应商带来了更高的收益。建议的设置已通过32节点配电总线系统进行了测试。仿真结果表明，所部署的方法将通过接收最佳DARTP来帮助参与者将峰值负载时间转换为基本负载时间，从而减少峰值负载情况下的过度消耗。获得的DARTP将通过部署高级计量系统发送给消费者。