Optimal control of power cost and consumer satisfaction using smart grid intelligent energy management system

This paper investigates the trade off between consumer satisfaction and the electricity cost. Due to forecast error in day ahead low price energy procurement and random realization of real time renewable dc power, it is difficult for an Intelligent Energy Management (IEM) operator to guarantee a satisfaction level to its users. The problem is more complex in the context of hybrid AC/DC smart grid, where AC to DC and DC to AC conversions result in converter losses. Moreover, during peak hours, increased power is required to serve increased load demands which is purchased at higher market rates by the utilities. We demonstrate the optimization problem of minimizing the time average cost of electricity, under the constraints of providing consumers with high satisfaction level. The solution is proposed by introducing load scheduling and hybrid switching control (LSHS) algorithm based on Lyapunov optimization, which is responsible for delivering cost efficient electricity and serving shiftable loads within certain time bound. Our algorithm requires only electricity price values and works without any prior or future knowledge of supply and demand statistics of power.