Current trends show that renewable energy production costs continue to decrease with time, so that renewable energy sources (RES) are becoming more suitable as electricity sources. In addition to their environmental benefits, RES are especially appropriate for remote areas, where the expansion of existing power grid is impractical and fuel transportation for thermal generators is too expensive. In this regard, our work studies the optimal capacity sizing for a completely green village (CGV), which is an isolated residential microgrid (MG) whose power is entirely generated by RES. In particular, we consider a neighborhood composed of smart homes that contain programmable appliances, whose operations can be interrupted or automatically scheduled in time. Though there are many works in literature that investigate MG optimal capacity sizing, to our knowledge, our work is the first that utilizes the scheduling of programmable appliance to minimize MG investment costs. To establish the effectiveness of our method, we compare an optimal MG capacity sizing algorithm that utilizes appliances’ programmability (Opt-P) with an algorithm that places appliances into operation as soon as they are ready without shifting in time or preempting their operation (NoSch-P). Our simulation results show that Opt-P reduces the investment cost by at least 42% compared to NoSch-P, when the ratio between the energy storage investment cost per kWh and the RES’ investment cost per kW is greater or equal to 10.

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