摘要
This study presents an optimization technique and design for a stand-alone photovoltaic (PV) system to provide the required electricity for a single residential household in remote areas. From the basic solar components analysis, the irradiance on tilted surface is derived and compared to that on horizontal surface for Furu-Awa locality to infer the appropriate tilt angle (β) that maximizes the collection of solar energy. Seven optimum values of β applicable to the PV network were then derived depending of the period of the year and this simulation resulted that the panels are to be adjusted seven times a year. The optimization technique for load demand based on total apparent power of the household appliances produces an increase of 18% compared to the simple case of the PV components design using active power but leads to the optimum configuration that meets the real load demand of the household. Following the sizing of the station, reliability tests simulations were conducted for a one year corresponding period to infer the sensitivity of power supply to initial state of charge, to check the system autonomy and to evaluate the effect of random variation of the load on the smooth functioning of the PV system using a pseudo random number generator. This analysis shows that the minimum capacity of the battery for normal run of the Plan is 22.2% and that with random fluctuation of load, there will be periods of the year where the system experiences power failure depending on how important is the variation. The result of the study may imply a small increase in the cost of the entire plant but improves the stability and flexibility of such a station.
This study presents an optimization technique and design for a stand-alone photovoltaic (PV) system to provide the required electricity for a single residential household in remote areas. From the basic solar components analysis, the irradiance on tilted surface is derived and compared to that on horizontal surface for Furu-Awa locality to infer the appropriate tilt angle (β) that maximizes the collection of solar energy. Seven optimum values of β applicable to the PV network were then derived depending of the period of the year and this simulation resulted that the panels are to be adjusted seven times a year. The optimization technique for load demand based on total apparent power of the household appliances produces an increase of 18% compared to the simple case of the PV components design using active power but leads to the optimum configuration that meets the real load demand of the household. Following the sizing of the station, reliability tests simulations were conducted for a one year corresponding period to infer the sensitivity of power supply to initial state of charge, to check the system autonomy and to evaluate the effect of random variation of the load on the smooth functioning of the PV system using a pseudo random number generator. This analysis shows that the minimum capacity of the battery for normal run of the Plan is 22.2% and that with random fluctuation of load, there will be periods of the year where the system experiences power failure depending on how important is the variation. The result of the study may imply a small increase in the cost of the entire plant but improves the stability and flexibility of such a station.
