Smart Optimization of Energy Management in Future Buildings by Integrating Distributed Generation and Energy Storage Using a Gravitational Search Approach

One of the most crucial topics in modern smart buildings is the optimal management and utilization of power generation resources. This article investigates the optimal energy management of a residential hybrid energy system based on combined heat and power (CHP) generation. In this hybrid system, a fuel cell is utilized to generate both electricity and heat, while a battery serves as the energy storage system. A day-ahead load forecasting and scheduling algorithm is employed to manage energy production in this system. At each time step, the algorithm determines the optimal power generation amount based on the expected load, minimizing the cost of supplying electricity to the residential building. In this article, a cost function is formulated, which includes various components such as fuel cell costs, battery costs, and other system-related expenses. The objective function is then optimized using the Gravitational Search Algorithm (GSA) in the MATLAB environment, aiming to minimize the overall energy production costs of the hybrid system. The simulation results, presented in Chapter ۴, demonstrate optimal energy management and cost reduction in the CHP system (fuel cell and battery) under grid-connected conditions. Furthermore, the results validate the effectiveness, accuracy, and speed of the advanced GSA algorithm in determining the optimal operating points for the system.

کلیدواژه ها:

Smart buildings ، optimal power generation management ، distributed generation ، energy storage systems ، gravitational search algorithm