Abstract
Smart grid technology enables active participation of the consumers to reschedule their energy consumption through demand response (DR). The price-based program in demand response indirectly induces consumers to dynamically vary their energy use patterns following different electricity prices. In this paper, a real-time price (RTP)-based demand response scheme is proposed for thermostatically controllable loads (TCLs) that contribute to a large portion of residential loads, such as air conditioners, refrigerators and heaters. Wind turbine generator (WTG) systems, solar thermal power systems (STPSs), diesel engine generators (DEGs), fuel cells (FCs) and aqua electrolyzers (AEs) are employed in a hybrid microgrid system to investigate the contribution of price-based demand response (PBDR) in frequency control. Simulation results show that the load frequency control scheme with dynamic PBDR improves the system’s stability and encourages economic operation of the system at both the consumer and generation level. Performance comparison of the genetic algorithm (GA) and salp swarm algorithm (SSA)-based controllers (proportional-integral (PI) or proportional integral derivative (PID)) is performed, and the hybrid energy system model with demand response shows the supremacy of SSA in terms of minimization of peak load and enhanced frequency stabilization of the system.
Highlights
The demand for electricity consumption is growing day by day, in line with consumer activities.The expansion of generation capacity with traditional energy sources leads to negative effects on the environment and, subsequently, increases the operational cost
In order to overcome the frequency fluctuation due to uncertain energy sources, such as Wind turbine generator (WTG) and solar thermal power systems (STPSs) [4,5], some energy storage units have been introduced to the hybrid energy system model, such as hydrogen aqua electrolyzers (AEs) and fuel cells (FCs), which are capable of reducing these fluctuations
The microgrid system model mentioned in the proposed work consists of organic Rankine cycle (ORC) low-temperature STPSs, wind turbine generators (WTGs), diesel engine generators (DEGs), fuel cells (FCs) and hydrogen aqua electrolyzers (AEs) as energy storage elements
Summary
The demand for electricity consumption is growing day by day, in line with consumer activities. DR with pricing indicators on residential load control, such as thermostatically controllable loads (TCLs) [21,22,23,24], can be modeled with various optimization techniques such as the genetic algorithm (GA)- [25] and salp swarm algorithm (SSA)-based controllers (PI and PID) [26]. The application of SSA is a maiden one which has never been leveraged for frequency regulation of an isolated hybrid microgrid system in the presence of price-based DR (PBDR). The application of electricity pricing-based demand response (PBDR) for TCLs for the optimal management of energy utilization by the users; Comparison of the dynamic responses of various PI and PID controllers in the hybrid isolated microgrid system with and without PBDR; The optimization of (PI and PID) controller gains by applying the genetic algorithm (GA) and SSA in the developed model.
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