Demand Side Management (DSM) is a well-recognized concept that seeks to optimize the efficiency and effectiveness of a distribution system. DSM encompasses load shifting and load curtailment strategies, both designed to mitigate the system's peak demand. The former is an optimization-based method that repositions the elastic loads to hours with low tariff rates, thereby filling the gaps and reducing the peak. The latter offers incentives to consumers to encourage their participation and reduce energy consumption during periods of high demand. In order to minimize the overall operating cost, the unique work done in this study intends to analyze ten exhaustive cases on a low voltage (LV) microgrid (MG) system and optimally schedule the distributed energy resources (DERs). The complexity of the work is further enhanced by the inclusion of plug-in hybrid electric vehicle (PHEV) which integrates Grid to Vehicle (G2V) and Vehicle to Grid (V2G) technologies to charge and discharge itself using the utility assigned electricity market price. The work used the Differential Evolution (DE) method as an optimisation framework. The ten exhaustive scenarios were analyzed to acknowledge the impact of the involvement and pricing of the grid, PHEV and DSM strategies mentioned above. Numerical study confirms that the load shifting policy and the type of load curtailing policy which rewarded the customer based on their willingness to curtail loads along with delivering benefit to the DISCOM were more cost-effective compared to the rest of the cases. Furthermore, it was also noted that time of usage (TOU) based electricity pricing was economical for entities which participated in bidirectional flow of power like grid and PHEV.

Grid-connected mode of microgrid (MG) operation is the most economical and reliable mode of service because the grid participates in the buying and selling of power with the MG, which reduces the generation cost of the MG system. Various types of electricity market pricing strategies are available in the literature with which the grid buys and sells power to the MG system. These strategies are implemented in turns on two different low voltage (LV) MG systems, and the generation cost of the systems are recorded to distinguish the cheapest strategy among them. A novel hybrid of recently developed superior optimization algorithms viz. grey wolf optimizer (GWO), sine cosine algorithm (SCA), and crow search algorithm (CSA) is used to minimize the overall generation cost of the MG system. It was evident from the results that generation cost was minimum when electricity market pricing was done using Strategy 2. Also, active participation of the grid incurred 15% savings in the system generation cost for the same strategy compared to the case when the grid was operating passively. Furthermore, statistical analysis corroborates to the superiority of the proposed hybrid MGWO-SCA-CSA over other algorithms used.

This article presents a metaheuristic algorithm namely Ameliorated Harris Hawk Optimizer (AHHO) to solve multiconstrained optimization problems. AHHO mimics the hunting behavior of Harris Hawks and is modified to draw a synergy between exploration and exploitation by conducting neighborhood search of already visited iterations utilizing random exploratory forage and local random forage. The oppositional based learning has been incorporated to generate adequate diversity among solutions. The proposed algorithm is substantiated on a set of 23 standard benchmark functions to test its characteristics in finding optimal solutions. The algorithm is mathematically modeled in the current work to obtain solution for voltage constrained reactive power dispatch (VCRPD) problem for IEEE 57 and 118 bus systems. The proposed method of VCRPD is implemented first with shunt capacitors as var sources and then replacing them with static var compensator (SVC) for improved performance. The optimal placement of SVC is determined by fast voltage stability index method. The proposed AHHO algorithm reduces the transmission losses by 9.42% with shunt capacitors in IEEE 57 bus and 10.344% in IEEE 118 bus system. Similarly, transmission loss with SVC compensated system is reduced by 12.86% in IEEE 57 bus and 14.74% in IEEE 118 bus system. Results reveal the proposed technique has the potent to solve real world optimization problems and is competitive with recent methods reported in state-of- art literature.