Optimal Scheduling Cascade Multi-hydropowers Based On Ecological Punishment

Small hydropower as a renewable clean energy is an important part of social development.Construction of water conservancy and economic benefits human life convenience, but also produced a series of river ecological problems. In recent years, with the introduction of the concept of sustainable development and harmonious development of eco-economy, research and development of small hydropower in intelligent scheduling and optimization of the energy-saving equipment has made considerable progress. Considering ecologic into daily scheduling has also become a trend. Optimal ecological runoff calculations have become the most important measure to ensure ecological factors.To deal with small hydropower based on the ecological basis of the original scheduling constraints, we improved the calculation method to suite ecological experience for small hydropower; proposed ecological factors as an ecological punishment into scheduling models optimized for small hydro scheduling; established optimal scheduling model scheduled for small hydro problems; improved an intelligent optimization algorithms and had given the solving methods. The main works has been done as follows:(1) Calculating a suitable ecological runoff process. For monthly runoff calculation method of ecological low frequency, accuracy is insufficient. By linear regression, residual analysis, and P-III curve processing, we screened limit to replace the historical hydrological error data. In this way we improved the accuracy and reasonableness of ecological Small Hydropower recommend appropriate runoff values.(2) According to the properties of small hydropower ecological, scheduling intelligent algorithm has been improved. Based on the dynamic topology of PSO algorithm, we joined the immune clone with the dynamic field of structural optimization mechanism. In order to overcome the short connections of dynamic field structure, we improve the algorithm of random searching performance and convergence speed. This helps the optimization model finding the optimal solution quicker and the solving process easier.(3) By analyzing the characteristics of hybrid cascade small hydropower, we established relationships between the amounts of water. At the same time we established small hydropower swarm optimization scheduling model while using the appropriate ecological flow value as apenalty factor. This integrated into the model, making ecological punishment establishing optimal scheduling model based on ecological punishment. We imported the new eco-runoff calculations results into optimal scheduling model, with improved immune clonal selection based on the dynamic field of PSO algorithm, we are able to find the better solution.The results show that, Lushui River model based on the ecology of punishment can be solved by improved algorithm. New model allows the entire reservoir group get more profits,better runoff closer to the river natural runoff process. The results will protect the river environment system while improving water and electricity group comprehensive income.