Optimal sizing of hybrid PV–Wind–Battery storage system for Net Zero Energy Buildings to reduce grid burden

Abstract

Accessing reliable, clean and affordable energy can be achieved by hybridization of renewable energy sources (RES) such as solar and wind. Such a hybrid photovoltaic (PV) and wind system along with battery storage (BS) has been considered for this work to realize the concept of Net Zero Energy (NZE) for a group of buildings (NZEBs). Generally, optimal sizing of hybrid PV–Wind system for NZEBs are carried out to ensure the minimum Loss of Power Supply Probability (LPSP) and cost with NZE balance constraints. But, the energy transfer between the buildings and grid has not been considered which is a vital parameter in optimal sizing of renewable energy generators for NZEBs. In NZEBs, over sizing/under sizing of renewable energy generator leads to greater energy export/import between the building and grid, which eventually increases burden on the electrical grid. So, in this work, minimization of total energy transfer (TET) is considered as the third objective function along with LPSP and cost to minimize the grid burden. A Non-dominated Sorting Genetic Algorithm II (NSGA-II) has been utilized for optimization of three objective functions such as annualized cost of the system (ACS), LPSP and TET, which are conflicting and incomparable. Based on the proposed sizing technique, the size of hybrid PV–Wind generators and BS capacity are determined from the pareto front solutions. To exemplify the reduced grid burden by reducing the TET, the results of proposed three objective function sizing technique are compared with the results of two objective function (cost and LPSP) sizing technique and analyzed for two different conditions of LPSP. The results confirm that the reduced TET has been achieved through the proposed sizing technique.