Optimal Scheduling of Battery Energy Storage for Grid-Connected Load using Photovoltaic System (PV) via Binary Particle Swarm Optimization (BPSO)

Eduardo  D. Piedad Jr. ,; Marc Edwin   F. Montilla,; Mark Joseph  E. Ortega,

Optimal Scheduling of Battery Energy Storage for Grid-Connected Load using Photovoltaic System (PV) via Binary Particle Swarm Optimization (BPSO)

Eduardo D Piedad Jr. | Marc Edwin F Montilla | Mark Joseph E Ortega

Abstract:

This paper presents an optimal dispatch of battery storage and its economic viability with a photovoltaic system. There are four modelled scenarios based on the combination of interruptible load program and the time-of-use scheme. The scenarios were modelled using a Binary Particle Swarm Optimization and were simulated using Matlab v6. In all the scenarios, this model successfully optimizes the battery dispatch scheduling while simultaneously minimizes the DU’s penalty from exceeding the maximum allowable power demand. This algorithm also optimizes the linearly forecasted demand for the next six year for all the scenarios. Then, an economic analysis for the possible investment to the combined BESS and PV system is conducted through the comparison of the payback periods of each scenario. The first scenario is implemented without ILP and a ToU scheme and has 79.86 payback years. With ILP scheme only, the second scenario has 33.37 payback years. Then the third scenario with ToU scheme only has a 30.29 payback years. Finally, the fourth scenario, with both ILP and ToU schemes,shows the fastest recovery of the investment with 21.57payback years. Thus the combination of both ILP and ToU schemes provide the best economic benefit. Though the current proposed system is still not economically feasible, however, the foreseen positive trends on solar and battery technologies will make this system viable.