Optimum Design of Daily Load Profile of Distribution Systems Under Demand Response Conditions Using Fuzzy Multi-Objective Approach Based on Artificial Rabbits Optimization Technique

Demand response strategies are widely used by utilities to encourage customers to shift their loads from peak to off-peak periods, thereby offering lower electricity prices. This research proposes a fuzzy multi-objective artificial rabbits optimization (ARO) technique to design the optimal daily load profile of a distribution system under demand response. The daily load profile is partitioned into three zones comprising the left valley, peak period, and right valley. Two load-shifting factors governing the redistribution of peak-period demand between the two valley regions are optimized, ensuring that neither valley load factor exceeds the resulting post-shift peak load factor, while simultaneously accounting for cost-reduction and voltage-performance objectives. Optimally sized distributed generators (DGs) are allocated when demand response alone cannot restore voltage compliance. Simulation results presented for the 69-bus and 123-bus systems demonstrate that shifting load only to the left valley yields a 5.57% energy charge reduction and shifting the load only to the right valley results in a 2.43% reduction. The fuzzy multi-objective solution attains a 4.00% reduction while satisfying the loss and voltage objectives. The minimum voltage of the 69-bus system is restored to 0.95 p.u. with DG, while the 123-bus system complies without DG, and both show reduced daily real power losses. By mitigating peak demand, reducing real power losses, and integrating optimally sized DGs, the proposed method decreases the amount of energy that must be generated and delivered to satisfy the same load demand. In addition, it can defer network reinforcement requirements, thereby enhancing the economic and environmental sustainability of the distribution system.