Kan Yang

Adaptive Genetic Algorithm for Daily Optimal Operation of Cascade Reservoirs and its Improvement Strategy

For the specialty of cascade reservoirs optimization and the premature convergence of GA, several improvement strategies are presented in this paper. Firstly, solution space generation method is found application to generate feasible initial population. Secondly, chaos optimization is adopted to optimize initial population. Thirdly, new selective operators, trigonometric selective operators, are proposed to overcome the fitness requirement of non-negative and to maintain the diversity of population. Fourthly, adaptive probabilities of crossing and mutation are adopted in order to improve the convergence speed of GA. Besides, elitist strategy is used to ensure that the best individual can be remained in each generation. Furthermore, the performance of these proposed improvement strategies was checked against the historical improvement strategies by simulating optimal operation of Three Gorges cascade reservoirs premised on historical hourly inflows, and the comparison yields indications of superior performance. In these proposed improvement strategies, trigonometric selective operators are feasible and effective for optimizing operation of cascade reservoirs. These new selective operators could help GA to find a more excellent solution in the same algebra, and the performance of convergence speed is advanced. Adaptive probabilities of crossing and mutation have better performance than other improvement strategies, such as annealing chaotic mutation and simulated annealing of large probability of mutation, because this method realizes the twin goals of maintaining diversity in the population and advancing the convergence speed of GA.

Application Research of the Improved Overall Temporal and Spatial Economic Operation Model Based on Information Entropy in Large-Scale Hydropower Station

For the high dimensional and complex inner-plant economical operation problem of large hydropower station, an improved ant colony optimization with adaptive ability, inspiring ability and local search ability was proposed. Spatial optimal load distribution model and temporal unit commitment model was combined into an overall temporal and spatial economic operation model, in which an innovative ant colony model of multiple ant colonies, multiple outsets and multiple routes was adopted. Information entropy was applied to adjust the path selection strategy and pheromone updating strategy of ant colonies along with the change of its value during the iteration. Two inspiring factors were applied in the algorithm to guide the ant colonies to search for optimal paths in a more efficient and targeted way. Local search ability was guaranteed by local translation of unit start-stop points of the optimal solution in each iteration. In the optimal load distribution model, optimal distribution table was set in advance using dynamic programming, which only took account of the stable operation regions and avoided the cavitation and vibration areas for the security and stability of units. The proposed method is applied to the Three Gorges Hydroelectric plant. Compared with other methods under different water heads, this method shows optimized result under the premise of both calculation speed and stability.

Application Research of Inner-plant Economical Operation by Multi-colony Ant Optimization

A new multi-colony ant optimization (MCAO) combined with a dynamic economic distribution (DED) technique has been proposed for the economical operation of the inner-plant of a hydropower station. MCAO and DED are applied to solve the unit commitment (UC) sub-problem and the economic load distribution (ELD) sub-problem consolidating the ramp rate constraints for the entire schedule. Moreover, a patching mechanism is developed to converge quickly on the optimal solution in two respects: minimum up/down and spinning reserve. A mechanism mitigates the premature convergence by measuring the uncertainty of pheromone with information entropy. A local research technique enriches the diversity of solution space by selecting the derived solutions from the perturbation mechanism. In comparison with the genetic algorithm, the particle swarm optimization, and the ant colony optimization, the MCAO is significantly robust and provides better solutions to the economical operation problem of hydropower stations. Numerical simulations exhibit the superiority of the DED technique regarding stably and quickly consolidating the ramp rate constraints.

Sine-roulette genetic algorithm applied in optimization operation of Qing River cascade hydropower system considering TOU power price

This paper presents the short-term joint optimal simulation operation simulation method for Qing River cascade hydropower system, which considering on time-of-use (TOU) power price and pursing maximum power generation benefit. In this method, the temporal-spatial variation of flow between cascade hydropower stations is considered. Correlation analysis is used for calibrating the measured data between hydropower stations, and an equation of linear regression is determined for dealing with the calculation of the temporal-spatial variation of flow. Furthermore, improved AGA with Sine-roulette wheel selection operator is found application in the simulation, which adopts trigonometric function to make a non-linear conversion to fitness in order to keep the diversity of population in the selection process and avoid premature of AGA. To a certain degree, the results of simulative optimal operation based on several representative hydrographs show that the improved AGA can find a more excellent solution in the same algebra.

Research on latin hypercube random simulation of optional operation of complex hydropower stations

The hydrological forecast error inevitably leads to the uncertainty of reservoir inflow, so the optimal operation of reservoirs group is also uncertain. This paper presents a method which combines the random simulation with the optimal operation of reservoirs group. The random simulation uses the method of Latin hypercube sampling to improve Monte Carlo method, which reduces the sampling frequency and improves the sampling accuracy compared with traditional sampling method. Ant colony algorithm is found application for solving the optimal operation problem of reservoirs group. According to the method presented we can obtain the scheduling scheme of reservoirs group under a given risk rate. At the same time the method changes the decision-making of stochastic operation into that of determinable operation. The study case of giant hydropower stations in Hubei Province shows that the method is practical.

Three Gorges Cascade Hydropower System Joint Simulative Optimal Operation Research in Power Market

The short-term joint optimal operation simulation of Three Gorges cascade hydropower system aiming at maximum power generation benefit is proposed. And a new method for optimizing cascade hydropower station based on Adaptive Genetic Algorithm (AGA) with trigonometric selective operators is presented. In this paper, the practical optimal operation in power market is described. The temporal-spatial variation of flow between cascade hydropower stations is considered, and time of use (TOU) power price is also taken into account. Moreover, a contrast between Tangent-roulette selection operator and traditional one is made. To a certain degree, the results of simulative optimal operation based on several representative hydrographs show that Tangent-roulette wheel selection operator can find a more excellent solution, because the Tangent-roulette one can overcome the fitness requirements of non-negative. The research achievements also have an important reference for the compilation of daily generation scheduling of Three Gorges cascade hydropower system in the environment of power market.

The Research on Cascade Reservoirs Optimal Operation Coupling with Latin Hypercube Random Simulation Method

In this paper, linear regression method is used to deal with the flow transmission. Applying large -scale system decomposition-coordination method, the paper analyzes the optimal operation problem of cascade hydropower stations. In order to research the uncertainty of the optimal operation of cascade reservoirs, this paper presents a method which combines it with the random simulation, which uses the method of Latin hypercube sampling to improve Monte Carlo method. The study case of Three Gorges cascade reservoirs shows that the method is practical

Optimal Operation of Complicated Giant Hydropower Stations Based on Decomposition-Coordination Method

Aiming at the problem of joint optimal operation at the five hydropower plants of Three Gorges and Qing River cascades, the paper adopts three-class structure to decompose and coordinate the optimal problem, which takes the maximum system power benefit as the optimization criterion under considering the flow propagation and the variable price factor. This paper derives the iterative formula of decomposition coordination method and identifies the convergence conditions of problem. The study case of Three Gorges and Qing River cascades in different conditions shows that total output of joint optimal operation is bigger than that of cascade single operation. Three Gorges and Shuibuya with large capacity of regulation, have larger output in power systems correspondingly when inflow is the same. In addition, this method is also effective in reducing the resolving time of giant hydropower stations optimal operation and improving the operational efficiency.