制度—政策—技术交互下的电力转型理论与规划方法研究

发布时间：2018-06-05 11:39

本文选题：学习曲线 + 发电成本　；参考：《华北电力大学(北京)》2016年博士论文

【摘要】：“十三五”及未来一段时期,我国能源发展面临着推进能源生产和消费革命、保障国家能源战略安全、实现由能源大国向能源强国转变的艰巨任务。电力系统作为能源转型的重要领域,电力部门的低碳发展和低碳转型成为关键。作为我国耗煤主体,电力系统的能源结构优化大大滞后于发达国家,积极推动我国电力系统的低碳转型,是应对气候减排、环境和能源安全等问题与经济发展目标之间日益严峻的冲突的必然途径。首先,本文基于系统转型管理理论以及新型产业创新发展过程,采用多层视角模型(MLP)分析了转型过程及其关键动力过程,研究中国电力系统宏观图景、技术社会范式和细缝技术,构建制度-政策-技术协同演化模型,深入分析制度、政策、技术、市场之间的交互机理。其次,通过对学习曲线模型因素分析与选择,构建基于累积装机容量和累积研发投入作用下的动态双因素学习曲线模型,定量评估能源政策与技术创新和应用的关系,研究电力技术学习率和单位投资成本演变趋势。再次,基于对主要电力技术发展的前瞻性分析,通过考虑财务参数、投资参数、运维参数、税收参数、容量参数等构建多因素平准化发电成本模型,对主要电力技术进行全面的技术经济性评估,在维持现有减排措施的情景中,可再生能源于2030年之后才具备与煤电相竞争的价格优势,而通过征收高水平的煤炭资源税、碳税和环境污染税以及光伏电价补贴,2020年可再生能源电力已经低于煤电价格,经济性明显,在此基础上提出不同发展阶段的电力系统转型路径。通过设定政策转移概率矩阵,建立基于马尔科夫决策过程的动态综合资源战略规划模型,以全社会总成本最小化为目标,以电力需求、电力负荷、装机规模、灵活电源、污染物排放为约束条件,明确不同政策组合以及实施强度对电力规划的影响以及不同电源纳入规划的时间及规模,采用粒子群文化算法求解不同政策集合下的电力规划路径,情景一复制路径中,延续和发展现有体制结构和运营模式,仍然保持以煤电为主导的电力技术发展路径,煤电作为主流电源保证电力需求。情景二解构和重构路径中,可再生能源电力技术从细缝技术突破技术封锁转型成为主流技术发展路径,煤电作为调峰电源为可再生能源电力提供支撑,促使旧有社会一技术范式发生转型。情景三和情景四技术替代和范式再建路径中可再生能源发电技术与当前主流煤电技术相互竞争,煤电在2020年达到峰值,风电与太阳能发电分别在2020年、2030年实现大规模发展。最后,基于新世纪的能源安全观从经济性、环保性、适应性三个准则提出电力规划多属性决策体系,采用粗糙集理论确定指标权重,并利用区间型多属性决策的目标规划模型对各方案进行综合评价,推荐情景二作为电力转型的最优路径规划。通过上述研究工作,本文的主要创新点：第一,基于多层视角分析模型构建了制度-政策-技术的协同演化模型,研究了制度、政策、技术、市场、价格等在不同发展阶段的交互机理,构建了电力系统转型的理论基础与分析框架。第二,在多层视角分析框架下研究了动态双因素学习曲线模型,分析累积研发与累积装机容量共同作用下能源政策与技术创新之间的定量关系,探讨技术学习规律对发电成本、电力规划的动态影响机理,形成了一套“宏观图景-转型路径-政策交互-技术寻优-情景仿真”的电力转型和政策优化理论体系。第三,构建了基于马尔科夫决策过程的动态综合资源战略规划模型,通过设计政策转移概率矩阵,将政策变量引入电源规划中,给出了中国2015-2050年不同政策实施路径下的动态电力规划方案。第四,基于新世纪的能源安全观,根据经济性、环保性、适应性三个准则构建电力规划情景的多尺度决策体系,建立区间型多属性决策的目标规划模型,对电力规划情景方案进行综合比较与评价。
[Abstract]:In the "13th Five-Year" and the next period of time, China's energy development is facing the arduous task of promoting the energy production and consumption revolution, ensuring the national energy strategic security and realizing the transformation from the energy power to the energy power. As an important field of energy transformation, the power system is the key to the low carbon development and the low carbon transformation of the power sector. The energy structure optimization of the power system is greatly lagged behind the developed countries. It is an inevitable way to cope with the increasingly severe conflict between the climate reduction, the environment and the energy security and so on. First, this paper is based on the theory of system transformation management and new production. In the process of industry innovation and development, the process of transformation and its key dynamic process are analyzed with multi view model (MLP). The macro picture of the Chinese power system, the paradigm of technical society and the slit technology are studied, the system policy technology co evolution model is constructed, and the interaction mechanism between system, policy, technology and market is deeply analyzed. Secondly, through the learning music Line model factor analysis and selection, build a dynamic dual factor learning curve model based on cumulative installed capacity and cumulative R & D input, quantitatively evaluate the relationship between energy policy and technology innovation and application, study the learning rate of power technology and the evolution trend of unit investment cost. Again, based on the prospect of the development of major power technology. By considering the financial parameters, the investment parameters, the operation and maintenance parameters, the tax parameters, the capacity parameters and so on, the multi factor leveling generation cost model is constructed. The technical and economic evaluation of the main power technology is carried out in a comprehensive way. In the situation of maintaining the existing emission reduction measures, the renewable energy can be derived from the competitive price of coal electricity after 2030. By collecting the high level of coal resource tax, carbon tax, environmental pollution tax and photovoltaic price subsidy, the renewable energy power has been lower than the coal electricity price in 2020, and the economy is obvious. On this basis, the power system transformation path in different stages of development is put forward. By setting the policy transfer probability matrix, the Markoff decision is set up. The dynamic integrated resource strategic planning model, with the goal of minimizing the total cost of the whole society, takes power demand, power load, loading scale, flexible power supply and pollutant emission as constraints, and defines the impact of different policy combinations and implementation intensity on power planning and the time and size of different power sources into the planning. The group culture algorithm solves the power planning path under different policy sets. In the scene replicating path, it continues and develops the existing system structure and operation mode. It still maintains the power technology development path dominated by coal and electricity. Coal electricity is the mainstream power supply to ensure the power demand. In scenario two deconstruction and reconstruction, renewable energy power technology The technology breakthrough technology blockade from slit technology to mainstream technology development path, coal electricity as a peak power supply to provide support for renewable energy and electricity, and promote the transformation of the old social one technology paradigm. Scenario three and scenario four technology replacement and paradigm rebuilding path of renewable energy source technology and current mainstream coal technology mutual Technology Competition, coal electricity reached its peak in 2020, wind power and solar power were developed in 2020 and 2030, respectively. Finally, based on the energy security concept of the new century, the multi attribute decision-making system of power planning was proposed from the three criteria of economy, environmental protection and adaptability. The weight of index was determined by rough set theory and interval multi attributes were used. The goal planning model of decision making is a comprehensive evaluation of each scheme, and scenario two is recommended as the optimal path planning for power transformation. Through the above research work, the main innovation points of this paper are as follows: first, the cooperative evolution model of system policy technology is constructed based on multi perspective analysis model, and the system, policy, technology, market, price, etc. are studied. The theoretical basis and analysis framework of power system transformation are constructed at different stages of development. Second, the dynamic dual factor learning curve model is studied under the multi-layer perspective analysis framework, and the quantitative relationship between energy policy and technical innovation under the joint action of cumulative R & D and cumulative installed capacity is analyzed, and the technical learning rules are discussed. The dynamic influence mechanism of law on power generation cost and power planning has formed a set of power transformation and policy optimization theory system of "macro picture - transformation path - policy interaction - Technology Optimization - scenario simulation". Third, a dynamic comprehensive resource strategic planning model based on Markoff's decision-making process is constructed, and the transfer probability of policy is designed. In matrix, the policy variables are introduced into the power planning, and the dynamic power planning scheme under the different policy implementation path of China for 2015-2050 years is given. Fourth, based on the energy security concept of the new century, the multi-scale decision-making system of electricity planning scenario is constructed according to the three criteria of economy, environmental protection and adaptability, and the order of interval multi attribute decision making is set up. The standard planning model is used to comprehensively compare and evaluate the scenario of power planning.
【学位授予单位】：华北电力大学(北京)
【学位级别】：博士
【学位授予年份】：2016
【分类号】：F426.61

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