【作者】 陈光；

【导师】 周浩；

【作者基本信息】 浙江大学 ， 电气工程， 2013， 博士

【摘要】 改革开放以来,在党中央的正确领导下,我国作为世界上发展最快的发展中国家,经济、社会发展取得了举世瞩目的辉煌成就,人民生活水平得到了明显改善。然而,由于长期以来我国的能源利用效率低下、技术条件落后、产业结构不合理等因素,我国在取得巨大成就的同时也付出了资源过度消耗和环境严重破坏的高昂代价,经济、社会发展与能源、环境危机的矛盾日趋尖锐,节能减排已成为我国实现可持续发展、保证中华民族长远利益的必由之路,也是应对全球能源危机和气候变化的迫切需要。电力系统作为一次能源消耗和二次能源供应的关键环节,是整个节能减排工作的重中之重。随着我国节能减排工作不断深入、政策不断加强,电力系统正迎来一系列新的变革和新的问题,迫切需要一些新的研究与分析方法。在此背景下,本文以电力系统节能减排为根本出发点,重点研究了与电力系统规划、运行密切相关的一些关键问题,主要包括计及线损和责任分摊的电力系统碳排放流分析、我国电力供应系统的碳排放转移分析、分布式电源在配电系统中的优化规划和优化重构和节能减排环境下的电力投资风险评估及不确定决策等内容。准确的碳排放核算和分析是制定节能减排政策的重要基础。为解决电力系统中的碳排放核算和分析问题,本文首先对电力系统碳排放流分析理论进行了改进和完善,建立了计及电网损耗和碳排放责任分摊的碳排放流实用分析模型和方法,为进一步完善和推广应用电力系统碳排放流分析理论提供了新的思路。采用改进的碳排放流分析模型,并结合全生命周期评价方法,对包括跨区域电煤运输和电力传输在内的我国电力供应系统进行了全生命周期碳排放核算和碳排放转移特性分析,将分析结果与已有的研究成果进行了比对,对我国电力供应系统节能减排政策的制定提出了分区域差别对待和建立碳排放责任分摊机制的建议,为我国电力系统的分地区统筹规划和发展提供了有价值的参考。在节能减排环境下,分布式电源在配电系统中正得到不断推广和应用。针对分布式电源在配电系统中的优化规划问题,构建了能够计及多种分布式电源和多种资源消耗与环境影响的综合优化规划模型。优化规划模型中采用全生命周期炯消耗作为综合指标衡量分布式电源所引起的资源消耗、环境影响以及替代传统电源和热源所造成的节能减排效益。通过同时优化全生命周期(?)消耗、经济成本和系统损耗,实现了分布式电源的多目标综合优化规划。采用机会约束条件和概率潮流分析计及了分布式电源出力和负荷不确定性的影响。为提高含分布式电源的配电系统概率潮流分析效率,提出了一种将拉丁超立方抽样方法与线性化潮流方程相结合的半线性化概率潮流分析方法,该方法以基于拉丁超立方抽样的概率潮流分析为基本框架,避免了解析概率潮流分析方法的不稳定性和误差,并在此基础上分别采用准确性高的线性化方程求取节点电压和精确的非线性方程计算支路潮流,在保证计算准确性的同时避免了耗时较多的潮流迭代求解过程。以所提出的半线性化拉丁超立方抽样概率潮流分析方法为基础,对含异步风力发电机的概率潮流分析方法进行了改进。同时,考虑分布式电源接入配电系统后的优化运行问题,以最小化线损期望值为优化目标建立了计及分布式电源出力不确定性的配电系统机会约束优化重构模型,并采用基因分块的思想改进了遗传算法求解该优化模型,避免了大量不可行解的生成,提高了优化重构的求解效率。以IEEE-33节点配电系统为例验证了所提出的模型与方法的合理性和有效性。考虑节能减排政策和分布式电源给电力投资带来更多的风险因素,采用Nataf变换在电力投资风险评估的随机模拟过程中计及了不确定因素之间的相关性,提高了电力投资风险评估的准确性。同时,在风险评估的基础上将不确定指标值和指标权重的概率特性加入到电力投资方案决策的灵敏度分析中,构建了电力投资方案决策的概率灵敏度分析指标和分析方法。最后,以实际应用案例说明了所提方法的有效性。更多还原

【Abstract】 Since reform and opening, under the correct leadership of the CPC Central Committee, China, as the world’s fastest growing developing country, has made remarkable brilliant achievements in economic and social development, improving the people’s living standard significantly. However, due to long-standing inefficient use of energy, technical conditions backward, irrational industrial structure and other factors, China has been paying high cost of excessive resource consumptions and serious environmental damages for the achievements. The contradiction between the requirement for economic and social development and the crisis of energy shortage and environmental polutions is becoming increasingly obstructive to China’s sustainable development. Energy conservation and emission reduction is the only way to ensure long-term interests of the Chinese nation, and also the response to the global energy crisis and climate change which is urgently needed.As the main consumer of primary energy and supplier of secondary energy, electricity system plays the most important role in the energy conservation and emission reduction task. Facing the deepening energy conservation and emission reduction projects, the power system is ushering in a new series of changes and new problems and requires some new approaches for research and analysis. In this context, this dissertation takes energy conservation and emission reduction as the fundamental starting point, and focuses on several key issues that are closely related with electric power system planning and operation, including the improvement and expansion of power system carbon emission flow analysis theory, life cycle analysis of carbon emission transfer in Chinese power supply system, optimal distributed generation planning, distribution system reconfiguration with distributed generatiors, and risk assessment and uncertain decision-making of power system investment.Firstly, the carbon emission flow analysis theory for power system is improved and expanded taking into account the power loss and carbon emission responsibility allocation in the dissertation. Combined with life cycle assessment methods, the improved carbon emission flow model is used to account the carbon emissions and analyse the characteristics of carbon emission transfer in China’s power supply system, including cross-regional coal transport and electricity transmission. The analytical results are compared with previous research results. According to the results, differetiated treatments upon different regions and interregional economic ties from carbon emissions are suggested for the policy formulation of China’s electricity supply system energy conservation and emission reduction.An integrated optimization model is built to solve the distributied generation planning problem in the distribution system. The objective functions not only take the economic costs and distribution system power losses into consideration, but also maximizes the benefits of energy conservation and emission reduction using life cycle exergy consumption as a unified indicator. This indicator comprehensively measures the resource consumptions and environmental impacts caused by distributed generation and the effect of substituting traditional energy sources. Chance constraints are used to simulate the uncertainties of distributed power output and load. The Latin hypercube sampling probabilistic load flow analysis is improved by conbining with linear load flow equations. The voltage vector is calculated by linear load flow equations which is proved to be efficient and accurate, avoiding time-consuming iteration process. The branch load flow vector is calculated by the nonlinear equations ensuring the accuracy. Based on the proposed semi-linear Latin hypercube sampling probabilistic load flow analysis method, the probabilistic load flow analysis method considering asynchronous wind power generators is improved. Based on such probabilistic load flow analysis method, an optimal reconfiguration model is established to solve the distribution system reconfiguration problem considering distributed generators and uncertain power loads. The genetic algorithm is improved to solve the optimization model. Finally, the IEEE-33bus distribution system is used to illustrate the proposed models and methods.The uncertainties of energy conservation and emission reduction polies bring more risks for electric power investments. To improve the accuracy of power investment risk assessment, the Nataf transformation is used in the stochastic simulation process to simulate the correlations of uncertain factors. Meanwhile, on the basis of risk assessment, probability characteristics of criterion values and criterion weights are added to the sensitivity analysis for power investment decision making, constructing probabilistic sensitivity analysis method. Practical case studies are carried out to illustrate the effectiveness and applicability of the proposed methods.更多还原