A novel multitype-users welfare equilibrium based real-time pricing in smart grid

In this paper, we propose a Multitype-users Welfare Equilibrium based Real-Time Pricing scheme to determine effective electricity prices in smart grid to achieve welfare equilibrium between the utility company and customers, in which three types of customers (i.e., residential-users, commercial-users and industrial-users) are considered. Via introducing value functions related to energy consumption, optimization problems on welfare equilibrium between customers and the utility company are formalized. In addition, a greedy-based task scheduling mechanism is proposed for industrial-users to reduce electricity cost and improve the efficiency of industrial production. Due to the welfare contradictions between customers and the utility company and to achieve welfare equilibrium and determine effective real-time electricity prices, an optimal energy consumption mechanism is proposed for customers to determine the optimal energy consumption and a quantum-behaved particle swarm optimization (QPSO)-based solution is proposed for the utility company to determine the effective electricity prices. Through extensive performance evaluation, our data shows that the QPSO-based solution can determine the real-time electricity price faster than existing solutions and our proposed real-time pricing scheme can reduce load fluctuation, achieve load balance, improve welfare of customers, as well as achieve welfare equilibrium between customers and the utility company. Additionally, our proposed pricing scheme can also achieve greater welfare for both customers and the utility company in comparison with other pricing schemes.