Integrated Optimization of Grid-Bound Energy Supply Systems

Abstract

Energy supply is facing the challenge to be secure, competitive and sustainable, in spite of a shortage of fossil energy sources, while worldwide demand is growing, prices for oil and gas are increasing and important regions in the word are politically instable. The European Board as well as the Federal Republic of Germany have passed laws and set regulations to intensify competition, to reduce dependency of imports of recourses, to increase energy-efficiency and to support new technological solutions. Therefore, an optimization of existing energy supply systems is necessary, taking into account alternative energy supply concepts. The concepts, which are investigated in this article, consist of grids, distributed generation units and heating systems. Combinations of these components define different energy supply concepts. All energy supply concepts have an electricity supply via the electrical grid in common. Three energy carriers, and their associated networks, are commonly used to supply heat demand: electricity, natural gas and district heating. Since the complexity of the planning process increases with the number of new technologies and possible energy supply concepts, handling complex planning tasks is challenging. Due to the aforementioned high pressure to reduce costs and to increase energy-efficiency, a solution should be found that is as cost and energy efficient as possible. Computer-based optimization methods provide the opportunity to identify long-term cost- and energy-efficient energy supply systems. Especially heuristic optimization algorithms have shown a good performance in related network optimization problems. Their essential advantages are a reduced computational effort leading to computing times allowing investigation of large-scale supply tasks while simultaneously delivering several, similarly cost-efficient energy supply systems. Therefore, an optimization method for grid-bound energy supply systems based on Genetic Algorithms is proposed. For a given supply task the method is capable of calculating cost-efficient energy supply systems with regard to all technical and environmental constrains in an integrated planning process. Exemplary applications demonstrate the method’s capability and the advantages of applying this method for long-term planning of energy supply systems. Comparing optimized energy supply systems with existing systems allows direct conclusions for necessary adjustments and possible gains of efficiency.