This study presents an optimal sizing methodology for a stand‐alone and grid connected PV‐biomass hybrid energy system that serves the electricity demand of a typical village. However, this method is scalable and can be used in any test system. A recently developed artificial bee colony (ABC) algorithm is used to detect out the optimum hybrid system configuration with the least levelised cost of energy while minimising annualised cost of the system. It has been observed from the results that a grid connected hybrid PV‐biomass system is cost effective and reliable choice for rural electrification as compared with stand‐alone hybrid PV‐biomass energy system. It has been emerged from this study that the proposed system offers reliable and affordable electricity in a sustainable way by harnessing locally available natural resources. A brief comparison of results obtained from the ABC algorithm and hybrid optimisation model for electric renewable (HOMER) has been carried out. Moreover, it is also observed from the results that the ABC algorithm provides better results as compared with HOMER.

Renewable energy has become very popular in recent years. The amount of renewable generation has increased in both grid-connected and stand-alone systems. This is because it can provide clean energy in a cost-effective and environmentally friendly fashion. Among all varieties, photovoltaic (PV) is the ultimate rising star. Integration of other technologies with solar is enhancing the efficiency and reliability of the system. In this paper a fuel cell–solar photovoltaic (FC-PV)-based hybrid energy system has been proposed to meet the electrical load demand of a small community center in India. The system is developed with PV panels, fuel cell, an electrolyzer and hydrogen storage tank. Detailed mathematical modeling of this system as well as its operation algorithm have been presented. Furthermore, cost optimization has been performed to determine ratings of PV and Hydrogen system components. The objective is to minimize the levelized cost of electricity (LCOE) of this standalone system. This optimization is performed in HOMER software as well as another tool using an artificial bee colony (ABC). The results obtained by both methods have been compared in terms of cost effectiveness. It is evident from the results that for a 68 MWh/yr of electricity demand is met by the 129 kW Solar PV, 15 kW Fuel cell along with a 34 kW electrolyzer and a 20 kg hydrogen tank with a LPSP of 0.053%. The LCOE is found to be in 0.228 $/kWh. Results also show that use of more sophisticated algorithms such as ABC yields more optimized solutions than package programs, such as HOMER. Finally, operational details for FC-PV hybrid system using IEC 61850 inter-operable communication is presented. IEC 61850 information models for FC, electrolyzer, hydrogen tank were developed and relevent IEC 61850 message exchanges for energy management in FC-PV hybrid system are demonstrated.

The rapid depletion of fossil fuel resources and increase in demand of electricity has renewed interest in micro‐grids (MGs). Incorporating renewable energy sources (RESs) and storage devices into MG could play a vital role in enhancing the reliability of the system. However, due to the intermittent nature of RESs, voltage fluctuations may occur in the system. Therefore, storage devices can be the most viable option to handle the intermittent issues of RESs. Nowadays, handling a group of batteries with different ratings in the MG has been a major focus of research. The batteries with different ratings used for storage as well as grid support is termed as a distributed energy storage system. This work mainly emphasises on optimal power management of an MG by controlling the charging and discharging rates of individual battery. A droop‐based controller is proposed for optimal power management of batteries. An aggregator has been suggested at the MG which distributes the power among the various charging stations (CSs) and each CS finally distributes the power among the individual batteries based on droop participation factor. Moreover, the charging and discharging rates of batteries are controlled to achieve the desired power flow between the MG and CSs. The simulation results show the efficacy of the controller to meet the desired power at the MG. The proposed system is compared with an existing system to prove the efficacy of the proposed controller. Moreover, all the critical cases have been considered, such as the sudden failure of any generating unit. It has been observed that due to sudden failure of any generating unit, CSs manages power of the MG by altering charging and discharging rate of the batteries.