风电并网条件下的火电厂选址与燃煤供应链优化研究

发布时间：2018-08-14 19:31

【摘要】：习近平主席于2016年APEC峰会时曾表示,中国准备在公用事业进行供给侧结构性改革。电力行业存在盈利能力差、产能过剩的隐忧,亟待政策引导统筹化解。2017年,电力企业供给侧改革将进入实质性阶段。如何去产能、去库存、去杠杆、降成本、补短板成为结构性供给侧改革的重点任务。受电力供给宽松、煤价高企等多重因素影响,占电力供应70%左右的煤电正处于盈利能力的历史低点。小型落后火电产能过剩、亟待改善的盈利能力与京津冀、华东、华南地区严苛的环境保护指标,无不对煤电企业利润与燃煤物流成本产生着影响。传统方式将煤炭运抵东部、南部电力负荷区发电的形式,电煤供应链复杂,极易造成供应链断裂,煤炭输送成本过高,煤电企业盈利能力大幅下降。“西电东送”战略工程实施以来,我国能源开发重心不断西移、北移,根据国家电网“十三五”规划,从我国的西北部能源基地往东部负荷中心输送的电量将会越来越大、距离也会越来越远。于电煤主产区建厂发电外送,可有效降低煤炭运输费用,在提高煤电盈利能力的同时,改善负荷区煤电产能过剩与环境污染问题。然而,随着风电并网比例的不断提高,风电的动态性和随机性,对火电厂布局与燃煤供应链的优化产生了越来越大的影响,对解决供应链优化问题而言是一种新的挑战。在本文中,首先对火电厂燃煤供应链优化的发展历史与研究现状进行了总结,阐述在电力行业供给侧架构性改革与“西电东送”背景下电煤供应链发生的变化,结合风电并网分析对传统火电厂燃煤供应链的影响。针对风电的随机波动性,以符合系统运行特点的技术条件为约束,分析风电场与火电厂的综合布局对燃煤供应链的影响,以利益最大化为原则建立燃煤供应链优化的随机规划模型,并对模型的有效性进行评价。之后,提出的量子离散粒子群一二次规划方法是在贪心变异策略的基础上改进而来的,使用量子离散粒子群算法与二次规划法求解含风电场的火电厂最优燃煤库存量。基于贪心变异策略对量子离散粒子群算法进行改进,比传统算法相更易于得到最优解。最后,本文基于燃煤供应链经济化为原则以含风电场的的火电厂布局与火电厂燃煤库存优化流程,求解了火电厂在风电场出力不确定的情况下燃煤库存量与火电厂、风电场布局,结果验证了本文建模与算法的可行性和有效性,从而确保了燃煤供应链的经济性,达到提高煤电盈利能力的目的。
[Abstract]:At the 2016 APEC summit, President Xi Jinping said China was prepared to undertake supply-side structural reforms in public utilities. The power industry has the potential of poor profitability and overcapacity, which needs to be solved as a whole through policy guidance. In 2017, the supply-side reform of electric power enterprises will enter a substantial stage. How to reduce production capacity, inventory, leverage, cost reduction and repair of structural supply-side reform has become the key task of structural supply-side reform. Coal, which accounts for about 70 percent of the electricity supply, is at an all-time low of profitability, driven by multiple factors such as easy electricity supply and high coal prices. The overcapacity of small and backward thermal power, the urgent need to improve profitability and the harsh environmental protection indicators in Beijing, Tianjin and Hebei, East China and South China all have an impact on the profits of coal and power enterprises and the cost of coal combustion logistics. The traditional way of transporting coal to the east and south of the power load area is the form of power generation. The supply chain of electric coal is complex, which can easily lead to the breakage of the supply chain, the high cost of coal transportation, and the decline of profit ability of coal power enterprises. Since the implementation of the "West-to-East Power Transmission" strategic project, the focus of energy development in China has been moving westward and northward. According to the 13th Five-Year Plan of the State Grid, the amount of electricity transferred from the northwest energy base of our country to the eastern load center will be increasing. The distance will grow farther and further. Building power plants in the main coal-producing areas can effectively reduce the cost of coal transportation, improve the profitability of coal power, and improve the problems of coal power overcapacity and environmental pollution in the load area at the same time. However, with the increasing proportion of wind power connected to the grid, the dynamic and randomness of wind power has more and more influence on the layout of thermal power plant and the optimization of coal-fired supply chain, which is a new challenge to solve the problem of supply chain optimization. In this paper, firstly, the development history and research status of coal-fired supply chain optimization in thermal power plants are summarized, and the changes of coal-fired supply chain under the background of supply-side structural reform and "power transmission from west to east" in power industry are expounded. Combined with wind power grid analysis of the traditional coal-fired power supply chain. In view of the random fluctuation of wind power, the influence of the comprehensive layout of wind farm and thermal power plant on the coal-fired supply chain is analyzed under the constraints of the technical conditions according to the characteristics of the system operation. Based on the principle of maximum benefit, the stochastic programming model of coal-fired supply chain optimization is established, and the effectiveness of the model is evaluated. After that, the quantum discrete particle swarm optimization (QDPSO) is improved on the basis of greedy mutation strategy. Quantum discrete Particle Swarm Optimization (QDPSO) and quadratic programming are used to solve the optimal coal-fired inventory of thermal power plants with wind farms. Quantum discrete particle swarm optimization (QDPSO) is improved based on greedy mutation strategy, which is easier to obtain optimal solution than traditional algorithm. Finally, based on the principle of economization of coal-fired supply chain, based on the layout of coal-fired power plant with wind farm and the optimization process of coal-fired inventory of coal-fired power plant, the coal-fired inventory and thermal power plant in the case of uncertain wind farm output are solved. The result of wind farm layout verifies the feasibility and effectiveness of the modeling and algorithm in this paper, thus ensuring the economy of coal supply chain and achieving the purpose of improving the profitability of coal power.
【学位授予单位】：华北电力大学(北京)
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：F426.61;F426.21

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