Energy flexibility of space-heating or cooling in Spain based on Developed Wildebeest Herd Optimization algorithm

Abstract

The present study analyzes the feasibility of energy flexibility for space cooling and heating of a typical Spanish domestic building during dissimilar geographical conditions. This study uses a new modified metaheuristic algorithm, called the Developed Wildebeest Herd Optimization (DWHO) algorithm to improve the demand for thermostat settings. The algorithm is also decreasing the network interaction and the costs of the operation. The main reason for using the proposed DWHO algorithm is to improve the accuracy of the algorithm and also to resolve the problem of convergence speed. The study also analyzes the Expected Flexibility Savings Index (EFSI) score. Simulation results indicated that the utilized energy flexibility indicator depends on different factors, such as electricity tariffs utilization time; thermal inertia of the typical domestic, and geographical position of the building users’ comfort boundaries. Simulations are established during a 24-h period. Simulation shows that the largest potential is achieved by Algezares with better irradiation capability. Alternatively, available cost flexibility in summer is decreased as the outside temperatures. Results show that the operation cost saves well. The final results indicate that the flexibility value is improved when the PV has been added to the system. This is proved based on the penalty factor. This shows that the proposed approach unites any desired period and can be used as an efficient planning tool for the policymakers.