Improving the efficiency of autonomous electrical complex with renewable energy sources by means of adaptive regulation of its operating modes

Renewable energy sources are gradually becoming useful in mining industry. They are actively used in remote, sparsely populated areas to power shift settlements, geological and meteorological stations, pipeline equipment, mobile cell towers, helicopter pads lighting, etc. In comparison with diesel generators, systems with renewable sources do not require fuel transportation, have short payback periods and flexible configuration for different categories of electrical loads. The main obstacles to their spread are instability of generation and high cost of produced electricity. One of the possible ways to solve these problems is to develop new technologies, increase power density of generators and energy storage systems. The other way represents energy saving and rational use of affordable resources. The new solutions for implementation of the second method are proposed in this work. The object of the study is autonomous DC electrical complex with photovoltaic and wind power sources. In such systems the generated power from renewable sources is transferred to consumers via intermediate DC bus, the voltage level of which affects the power losses in the process of power transmission. The vast majority of complexes have a problem that their DC bus voltage is constant, while the optimum voltage level with lowest losses varies depending on the generated and consumed power. Therefore, electrical complexes potentially lose a part of the transmitted energy. To avoid this, a special algorithm was added to automatically adjust DC bus voltage to optimum level according to changes in working conditions. An additional contribution to efficiency improvement can be made by dynamic change of operating frequency in power converters depending on their load. The evaluation based on results of computer simulation showed that in a complex with rated power 10 kW active power losses during its lifetime can be reduced by 2-5 %.