摘要
梯级水电站的优化调度一直是水电优化调度和水火电力系统发电计划中的难点。经过多年的发展,梯级水电优化调度的数学模型日益精确,逐渐贴近实际。文中比较了梯级水电优化调度的确定性模型和随机模型,并着重探讨了确定性模型。由于模型的复杂性,从理论上找到全局最优解存在困难,对算法提出很高的要求。文中对各种用于求解梯级水电站优化调度的算法进行了综述,将其分为经典算法、现代智能优化算法和混合算法三类,比较了各类算法的优缺点。在经典算法中,逐次规划法的应用较为广泛。同时,以遗传算法为代表的智能算法在求解梯级水电优化调度问题时也取得了比较令人满意的结果,成为当前研究的热点。伴随着世界范围内电力市场改革热潮的兴起,新的市场环境给传统的梯级水电优化调度提出了新的要求,市场环境下的梯级水电优化调度成为一个新的发展方向。
The optimal scheduling of cascaded hydropower stations has often been considered a difficult problem to solve. Researched many years, the mathematical models of cascaded hydropower stations optimal scheduling become more accurate. In this paper, the deterministic model of cascaded hydropower station optimal scheduling is compared with the stochastic model, and the deterministic model is mainly researched. It＇s very difficult to obtain the global optimal solution because of the problems＇ inherent complexity. The complex models demand more effective and speedier algorithm. On the basis of studying various algorithms, those algorithms fall into three main categories., the classical optimization algorithm, the modern intelligence optimization algorithm and the hybrid optimization algorithm. The advantages and disadvantages of them are compared. Among classical optimization algorithms, progressive optimality algorithm is widely applied. Modern intelligence optimization algorithm becomes a research hotspot because of its satisfying application result. With the development of electricity market, the optimal scheduling of cascaded hydropower stations under electricity market becomes a new research tendency.
出处
《现代电力》
2007年第1期78-83,共6页
Modern Electric Power
关键词
梯级水电
优化调度
优化算法
经典算法
现代智能优化算法
cascaded hydropower station
optimal scheduling
optimization algorithm
classical algorithm
modern intelligence optimization algorithm
