Facilitating high levels of wind penetration in a smart grid through the optimal utilization of battery storage in microgrids: An analysis of the trade-offs between economic performance and wind generation facilitation

•Optimization of building operating costs & facilitation of wind energy from smart grid.•Optimal battery schedule determined for a building with integrated microgrid.•Trade-off analysis between building operating costs and wind energy facilitation.•Small increases to building costs led to large increases in wind energy facilitation. The aim of this paper was to investigate the trade-offs that can be achieved between optimizing the electricity costs of a building integrated microgrid, while simultaneously facilitating high levels of wind penetration in a smart grid. This study applied multi-objective optimization to obtain a daily charge and discharge schedule of a battery bank, which was used to store electricity from the microgrid and smart grid and could also provide electricity to the building and smart grid. Multi-objective optimization was employed due to the independent objectives of minimizing building operating cost and maximizing the facilitation of wind energy from the smart grid. The trade-offs between the two objectives were simulated, evaluated and analyzed. A priority weighting factor (α) was applied to each objective. The purpose of α was to vary the importance of each objective relative to the other in an inversely proportional manner. This enabled the algorithm to optimize the battery operating schedule for the economic performance of the microgrid, the facilitation of wind generation from the smart grid or for trade-offs in between. The results present a comprehensive evaluation of 96 scenarios with varying daily weather conditions, building electricity demand, electricity pricing, microgrid output and wind penetration from the smart grid. A multi-objective optimization approach was then applied for each of the 96 scenarios with 11 α values to determine optimal trade-offs in these scenarios. Generally for the 96 scenarios analyzed, when the α value was 20% or higher, the amount of extra wind generation facilitation obtained was negligible while microgrid operating costs continued to increase. The results showed that when changing from an α value of 0% to an α value of 20%, there was a large increase in wind generation facilitation compared to the corresponding increase in cost, with wind generation facilitation increasing from its minimum value to within 89% of its maximum value (10.7% to 14.3% of facilitated wind generation). The corresponding building cost increased from its minimum value to within 13% of its maximum value (€1.14/day to