Investigating the Impact of Demand Management on the Microgrid with the Presence of Renewable Resources Uncertainty and Reliability

The proliferation of renewable energy sources within distribution systems has given rise to a new structure known as microgrids. These microgrids are small power grids comprised of both controllable and uncontrollable loads. In the distribution system, microgrids can use renewable energy sources to be operated in far-away regions at lower investment costs. The energy industry faces numerous problems, including problems with energy efficiency, ensuring system confidence, and reducing the destructive environmental effects. Load management programs can help address the challenges confronting the energy industry. This essay proposes a method for evaluating the load responsiveness in microgrids. A combined algorithm, including a gravitational search algorithm as well as particle swarm optimization, to address a multi-objective optimization function. The Latin hypercube sampling method is adopted to create diverse scenarios, which are reduced by the K-means method. The objective function includes grid losses, generation costs, confidence index, and voltage stability. The suggested method is implemented on a modified 69-bus system consisting of wind turbines, solar power stations, and energy storage systems using the combined optimization algorithm in Matlab. The results show that increasing renewable energy production reduces power losses, power consumption, and cost per kilo and improves voltage deviation. Adding renewables and energy storage also reduces power fluctuations and grid losses. Adding renewable sources brings benefits such as reduced production costs, losses, and improved voltage profiles. From the simulation outcomes, it can be seen that the average voltage profile has been improved by about 4%. Also, increasing the responsive load has improved the mains voltage profile and increased by about 10%.