Today's power grids are constantly facing reliable problems especially when unexpected periods of interruption occur. In recent years, the micro-grid has been proposed as a complimentary solution to help mitigate the reliability issues. The micro-grid, as part of the smart grid realization, consists of renewable generation, energy storage units and demand management through a low-voltage distribution network. Proliferation of renewable generation is one of the key drivers of establishing the need of micro-grid. Presently, renewable resources, e.g., solar energy, are employed globally due to the rapid development of the technologies and benefits to the environment during the past decades.
The UCLA Smart Grid Energy Research Center (SMERC) performs research focusing on the integration of solar generation in a laboratory level micro-grid. Components of the laboratory level micro-grid consist of solar PV panels, battery storage units and laboratory loads, including LED lightings, smart appliances and electric vehicles. During the implementation process, we focus on two essential impediments. Firstly, the integration of renewable generation into the micro-grid will require the assistant from forecasting. Forecasting is the ability to determine periods of stable generation from renewable sources. This is paramount to the reliability issues since it can reduce the uncertainty of the inconsistent renewable generation. Prediction models are developed to obtain accurate solar generation forecasting, which benefit the micro-grid by determining available power at any time and balancing the loads accordingly. The prediction models used in SMERC's research include the auto-regressive moving average (ARMA) model and the persistence model, due to their applicability in the micro-grid. Secondly, we aim to study the optimal sizing of solar PV panels and battery storage units by presenting a case study based on empirical weather and load data. To determine the system, we consider the optimization problem that reaches some desirable objectives subject to certain conditions.