Evaluating the use of a Net-Metering mechanism in microgrids to reduce power generation costs with a swarm-intelligent algorithm

The micro-generation of electricity arises as a clean and efficient alternative to provide electrical power. However, the unpredictability of wind and solar radiation poses a challenge to attend load demand, while maintaining a stable operation of the microgrids (MGs). This paper proposes the modeling and optimization, using a swarm-intelligent algorithm, of a hybrid MG system (HMGS) with a Net-Metering compensation policy. Using real industrial and residential data from a Spanish region, a HMGS with a generic ESS is used to analyze the influence of four different Net-Metering compensation levels regarding costs, percentage of renewable energy sources (RESs), and LOLP. Furthermore, the performance of two ESSs, Lithium Titanate Spinel (Li4Ti5O12 (LTO)) and Vanadium redox flow batteries (VRFB), is assessed in terms of the final $/kWh costs provided by the MG. The results obtained indicate that the Net-Metering policy reduces the surplus from over 14% to less than 0.5% and increases RESs participation in the MG by more than 10%. Results also show that, in a yearly projection, a MG using a VRFB system with a 25% compensation policy can yield more than 100000$ dollars of savings, when compared to a MG using a LTO system without Net-Metering.