Xinyu Wu

Short-Term Scheduling for Large-Scale Cascaded Hydropower Systems with Multivibration Zones of High Head

AbstractConstruction of huge hydropower plants in the southern region of China has been rapidly increasing in recent years. These plants usually have multiple vibration zones of high head that have a great effect on short-term scheduling and real-time operations. This paper presents a novel approach for optimizing short-term scheduling of large-scale cascaded hydropower systems with multivibration zones of high head. For the purpose of cutting down peak loads, standard deviation minimization relevant to the remaining load series for thermal systems was chosen as the objective nonlinear function. Before the optimization, unit forbidden operation zones were identified by assembled mathematical techniques and hydro unit commitments were optimized using dynamic programming. The combined sets of forbidden operation zones and hydro unit commitments were repeatedly used during the search process. An optimization framework that combined the progressive optimality algorithm with a vibration zone avoidance strategy...

Parallel discrete differential dynamic programming for multireservoir operation

The curse of dimensionality and computational time cost are a great challenge to operation of large-scale hydropower systems (LSHSs) in China because computer memory and computational time increase exponentially with increasing number of reservoirs. Discrete differential dynamic programming (DDDP) is one of the most classical algorithms for alleviating the dimensionality problem for operation of LSHSs. However, the computational time performed on DDDP still increases exponentially with increasing number of reservoirs. Therefore, a fine-grained parallel DDDP (PDDDP) algorithm, which is based on Fork/Join parallel framework in multi-core environment, is proposed to improve the computing efficiency for long-term operation of multireservoir hydropower systems. The proposed algorithm is tested using a huge cascaded hydropower system located on the Lancang River in China. The results demonstrate that the PDDDP algorithm enhances the computing efficiency significantly and takes full advantage of multi-core resources, showing its potential practicability and validity for operation of LSHSs in future.

Chance-Constrained Optimal Hedging Rules for Cascaded Hydropower Reservoirs

AbstractA multiobjective model with chance constraints is proposed to obtain hedging rules for hydropower reservoirs based on initial reservoir operating rules derived using stochastic dynamic programming. In the model, hedging rules are evaluated through simulations and the maximizations of minimum powers in simulation horizon of hydropower reservoirs are taken as objectives. The maximum-minimum objectives are substituted by aggregated functions. A genetic algorithm is used to solve the model, with a fuzzy optimal method evaluating the individuals. A case study shows that the proposed approach is feasible and efficient to produce a series of hedging rules with different reliability levels, and valuable to balance the magnitudes of generation below firm power and the chances of such events.

Centralized versus Distributed Cooperative Operating Rules for Multiple Cascaded Hydropower Reservoirs

AbstractMultiple cascaded hydropower reservoir systems serving the same area need to cooperate to increase overall benefits and reliability. To meet system demand while balancing among cascaded systems, both centralized and distributed five segment energy available based operating rules, making power decisions for subsystems and the whole system, are proposed for cooperation across multiple cascaded hydropower reservoirs. Unlike existing methods, the cooperative operating rules are optimized to the global objective of maximizing the minimum system power production, with constraints on local cascade minimum energy generation to confine the possible local profit earnings or losses because of cooperation, making the operating rules more acceptable for cooperative operations among local cascade system agents. The operating rule optimization models are solved using a genetic algorithm. A case study for three cascaded systems in southwest China shows that distributed and centralized cooperative operating rules ...

Long-Term Generation Scheduling of Hydropower System Using Multi-Core Parallelization of Particle Swarm Optimization

A multi-core parallel Particle Swarm Optimization (MPPSO) algorithm is developed to improve computational efficiency for long-term optimal hydropower system operation, in response to rapidly increasing size and complexity of hydropower systems, especially in China. The MPPSO can be implemented in three steps with easily accessible multi-core hardware platforms. First, a multi-group parallel computing strategy is introduced to maintain the diversity of population for finding the global optima. Second, the fork/join framework based on divide-and-conquer strategy is adopted to distribute multiple populations to different CPU cores for parallel calculations to take full advantage of CPU performance. Third, the results generated in different CPUs are merged to achieve an improved acceleration effect on computational time cost and more accurate optimal scheduling solution. Results for a system of twelve hydropower stations in the Guizhou Power Grid in China demonstrate that the proposed algorithm makes full use of multi-core resources, and significantly improves the computational efficiency and accuracy of the optimal solution, in addition to its low parallelization cost and low implementation cost. These suggest that the proposed algorithm has great potential for future optimal operation of hydropower systems.

Power Generation Scheduling for Integrated Large and Small Hydropower Plant Systems in Southwest China

AbstractElectric power transmission lines in service in southwest China have fallen far behind the power sources. With rapid development of hydropower in this area, severe water spills for hydropow...

Fast-Growing China's Hydropower Systems and Operation Challenges

During the past two decades, in particular the past decade, the construction of hydropower and power grid was under rapid development stage. It is foreseeable that the same rate of development will be maintained in the next decade. The installed generation capacity of hydropower in China has now surpassed 200GW and ranks first in the world.The rate of expansion and scales of construction are very rare in the world history. The operation and management of large-scale hydropower systems have become one of significant factors in constraining the security and economic operation of power grid in China. With the appearance of huge hydropower plants in the southern region of China, the large-scale hydropower transmission with multi-level regulation, the multiple vibration zones for plants with huge capacity and high head, peak regulation for trans-provincial and trans-region multi-power grids, aggravation of influence of extreme climate on operation of hydropower, the solution efficiency and practicality of hydropower system, etc, are fresh difficulties which pose a real challenge to the modelers and have a great impact on hydropower scheduling and operations. There are needs for finding their solutions. This article introduces the current status of construction and development of hydropower in China, analyzes the new challenges that it faces, highlights the key scientific and technological issues that need to be solved, and pinpoints that the solution of these problems will be the key to the realization of energy saving and emission reduction by China in 2020.

Some Practical Strategies and Methods for Large-Scale Hydropower System Operations in China

With the rapid increase of number and capacity of hydropower plants operated by single dispatching departments in China, more attention should focus on seeking more robust methods for reducing dimension curse, improving effectiveness and practicability of optimization results, and enhancing computational efficiency of large-scale complex hydropower system operations. In this paper, a general solution framework for large-scale complex hydropower system operations is presented from the real hydropower systems in China. The framework consists of intelligent strategies to reduce problem size during modeling, integrated optimization methods and search methods to vanquish dimensionality difficulties effectively and cope with complicated spatial-temporal constraints, as well as interactive interfaces to adjust optimal results. Two case studies are presented.

Short-Term Generation Scheduling for Hydropower Systems with Discrepant Objectives

The paper presents a novel discrepant model, which has been developed to determine reasonable 96-points generation scheduling for each hydropower plant by simultaneously optimizing different objective functions for the classified plant groups. The hydropower plants are in advance classified into groups that are characterized as the operation roles, inflows and regulating ability of reservoirs. Correspondingly, a methodology incorporating the dynamic programming successive approximation (DPSA) and improved progressive optimality algorithm (IPOA) is proposed to solve short-term generation scheduling problems for hydropower systems with discrepant objectives. The Hongshuihe River hydropower system, which is located in southwest China and consists of 9 built hydropower plants, is used as case study. The two objectives, which are cutting down peak load and maximizing generation, are used to optimize short-term generation scheduling for different plants. Results show that the developed model is able to effectively coordinate discrepant objectives and meet practical operational demands of power

A parallel multi-objective particle swarm optimization for cascade hydropower reservoir operation in southwest China

Abstract Due to the expanding system scale and increasing operational complexity, the cascade hydropower reservoir operation balancing benefit and firm output is becoming one of the most important problems in China’s hydropower system. To handle this problem, this paper presents a parallel multi-objective particle swarm optimization where the swarm with large population size is divided into several smaller subswarms to be simultaneously optimized by different worker threads. In each subtask, the multi-objective particle swarm optimization is adopted to finish the entire evolutionary process, where the leader particles, external archive set and computational parameters are all dynamically updated. Besides, a novel constraint handling strategy is used to identify the feasible search space while the domination strategy based on constraint violation is used to enhance the convergence speed of swarm. The presented method is applied to Lancang cascade hydropower system in southwest China. The results show that PMOPSO can provide satisfying scheduling results in different cases. For the variation coefficient of generation in 30 independent runs, the presented method can bettered the serial algorithm with about 66.67% and 61.29% reductions in normal and dry years, respectively. Hence, this paper provides an effective tool for multi-objective operation of cascade hydropower system.