Intelligent Optimal Scheduling Methods And Realization For Small Hydro Group

Small hydropower is high-quality,sustainable and clean renewable energy.Great achievement has been made in China regarding small hydro development.With the development of society,conservancy is shifted from its traditional type to a resources-focused and sustainable-development-oriented type;the operation of mall hydro should correspondingly be changed from regular experience-based scheduling to optimal scheduling.The small hydro groups in local power grid should be joined together to realize optimal scheduling so as to display the positive role to greatest extent and promote its sustainable development.Small hydro optimal scheduling is a nonlinear problem of large scale and for multi purposes.The key of achieving this is modeling and solution finding.A mathematic model with its optimal scheduling objective of achieving maximum power output does not meet the environmental and ecological demands.Optimal scheduling based on dynamic programming can lead to dimension disasters.Genetic Algorithm(GA) is widely applied to overall study on hydropower operation,but efforts have been making in applying improved genetic algorithm and other new and better optimization algorithms to hydropower optimal scheduling.The paper focuses on the optimal scheduling for small hydro group in local power grid, developing such a system by modeling and solving the problem.The main research works of the paper are listed as follow:(1) It firstly introduces the background and significance of the study on the optimal scheduling for small hydro group.Based on the summary of many documents and records,it provides an overview of the domestic and oversea researches made on optimal scheduling for small hydro group.(2) It gives a thorough research on various optimal scheduling mathematic models for small hydro group.An optimal scheduling mathematic model with its objective of achieving maximum power output is set up.It gives a unified description of serial, parallel and mixed group of small hydropower plants.After analyzing the requirements and principles of ecological scheduling for small hydro,a new mathematic model is proposed.Its objectives are normal reservoir level and minimum surplus.The environmental and ecological functions of small hydro are taken into consideration in the restrains.(3) It studies the optimal scheduling for small hydro group based on Particle Swarm Optimization(PSO).A solution to the optimal scheduling for series small hydro groups by applying Adaptive Particle Swarm Optimization(APSO) is developed.The validity and convergence of APSO are tested and verified in a simulation example of two series small reservoirs.APSO is proved to be of higher performance than standard PSO and simple GA.It also develops a solution to the optimal scheduling for small hydro group by applying Resilient Particle Swarm Optimization Algorithm(RPSO). The self-adaptive strategy is introduced into the RPSO to improve its performance.The time complexity of the RPSO algorithm is analyzed.The validity of the algorithm and the model are tested and verified by making simulations.Differences between standard PSO,APSO and RPSO are also identified and compared in the simulation tests.(4) It studies the optimal scheduling for small hydro group based on Memetic Algorithm(MA) and Cultural Algorithm(CA).After summarizing the development and application of MA and CA,the paper develops a cultural algorithm which is called MA here.It characterized by co-evolution and co-promotion of the population space and belief space.An improved GA is used to represent the population space,and some updating regulations to describe the belief space.A simulated annealing algorithm and particle swarm algorithm are introduced to deal with the local variation as belief space governing population space.The validity of the algorithm is verified in a simulation test, and the time complexity of the algorithm is analyzed.The performance comparison between different algorithms is made,and the optimal scheduling results basing on MA and delivered by different mathematic models are also analyzed.(5) It studies the optimal scheduling for small hydro group based on Gene-Meme Co-evolution Algorithms(GMCA).After introducing the definition of meme and culture,the paper develops a gene-meme co-evolution algorithm,in which a coding meme and a particular meme are added,ways to evolute different algorithm cultures are setted,four cultural evolution operators(development,defection,revival and renaissance) are established,and a way of judging cultural senility is proposed.It develops a solution to the optimal scheduling for small hydro group based on GMCA.The validity of the algorithm is tested and verified in the case of small hydro group optimal scheduling.In the experiment comparison with that of GA,APSO,RPSO,MA and etc.the higher performance of GMCA is well demonstrated.(6) It studies the optimal scheduling system for small hydro group of local power grid,including its functions,components,design methods of individual module,and its realization.The system embodies two functions of administrative information management and query and optimal scheduling for small hydro plants.In particular,it includes runoff forecasting,long-term and short-term optimal scheduling,and daily operation.In combination with practical research project,the application of the system is also dealt with.Finally,the paper summarizes the studies made here and gives an outlook at the prospect of the optimal scheduling for small hydro group.