Energy Scheduling of Residential Appliances by a Pigeon-Inspired Algorithm under a Load Shaping Demand Response Program

In this paper, an energy management system (EMS) is modelled in a novel way, for the scheduling of interruptible and uninterruptible appliances of a residential consumer. It is considered that the local renewable energy is generated by the rooftop PV panels installed at the home, to convert a consumer into a prosumer. An energy controlling unit (ECU) schedules the home appliances according to the price signals received from the utility company within the user preferred durations so that the cost of electricity consumption could be minimized. A novel delay factor is also modelled to maintain the comfort level of the consumer. It is assumed that the consumer participates in a demand response (DR) program, based on real time price combined with inclined block rate (RTP-IBR) pricing scheme. Due to this, the peak to average ratio (PAR) of power is decreased and maintained within the satisfactory limits. Finally, for the optimization of the formulated objective function, a pigeon-inspired optimization (PIO) algorithm is used, due to its effectiveness and fast convergence rate over the other similar algorithms. At the end, the results of energy scheduling have been compared and verified against the results achieved by the particle swarm optimization (PSO) algorithm.