Cost calculation algorithm for stand-alone photovoltaic systems

Abstract

Photovoltaics are the technology that generates direct current (DC) electrical power measured in watts or kilowatts from semiconductors when they are illuminated by photons. Photovoltaics are the technological symbol for a future sustainable energy supply system in many countries. A considerable amount of money is invested in research, development and demonstration; several governments set up substantial market introduction programs and industry invests in larger production facilities. Life Cycle Cost Analysis (LCCA) is an economic method of project evaluation in which all costs arising from owning, operating, maintaining and ultimately disposing of a project are considered to be potentially important to that decision. Doing a LCCA gives the total cost of a PV system-including all expenses incurred over the life of the system. LCCA is particularly suitable for the evaluation of building design alternatives that satisfy a required level of building performance, but that may have different initial investment costs; different operating, maintenance and repair (OM&R) costs; and possibly different lives. In this study, a software computer program for educational purposes is designed to determine initial, life cycle and unit energy costs of a stand-alone photovoltaic system in Turkey. Depending on the selected location, material and criteria, the proposed software implements the life cycle analysis of the system. The database and fixed constants of proposed software can be updated and new elements can be added at any time. Present value algorithm is described in previous section is used for cost calculation. Inappropriate selection of components is blocked by the software. Also, too large selection of particular elements such as inverter and batteries is blocked for optimal sizing of the system. As a result of the calculations were performed using software designed, in terms of lifetime cost and unit energy costs of PV systems most suitable provinces are Mersin, Antalya, Adana, Mardin, Van, Adιyaman, Aydιn and Kilis respectively. In the opposite, the highest costs are in Gümüşhane, Yalova, Aǧrι, Çankιrι and Kastamonu provinces.