Optimal Scheduling of Grid Transactive Home Demand Responsive Appliances Using Polar Bear Optimization Algorithm

The conventional power system has been evolving towards a smart grid system for the past
few decades. An integral step in successful realization of smart grid is to deploy renewable energy resources,
particularly rooftop photovoltaic systems, at smart homes. With demand response opportunities in smart
grid, residential customers can manage the utilization of their demand responsive appliances for getting
economic benefits and incentives in return. In this regard, this paper proposes an effective home energy
management system for residential customer to optimally schedule the demand responsive appliance in the
presence of local photovoltaic and energy storage systems. For efficient home-to-grid energy transactions
in home energy management system, the stochastic nature of photovoltaic power generation is modeled
with the beta probability distribution function for solar irradiance. The main contribution of this paper is
the application of polar bear optimization (PBO) method for optimally solving the scheduling problem of
demand responsive appliances in home energy management system to minimize electricity consumption
cost as well as peak-to-average ratio. The effectiveness of the proposed metaheuristic optimization
technique is proven by performing different case studies for a residential consumer with different base
load, uninterruptible deferrable, and interruptible deferrable appliances under a real-time energy price
program. Comparative results with different metaheuristic techniques available in the literature show that
the electricity consumption cost and peak-to-average ratio are effectively optimized using the proposed PBO
algorithm.