电力市场环境下的多目标输电网优化规划方法研究
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摘要
电力市场环境下的输电网规划是规划主体发生转变后,立足于市场环境的规划方法,其目标是通过输电容量合理扩充和配置来满足未来负荷增长和市场运行的需要,建立和维护市场公平竞争环境,并实现市场参与各方的合理利益。本文立足于多目标电网规划方法,着重探讨市场环境下输电网规划所面临的输电阻塞、过负荷风险、输电投资收益、电网投资收益风险以及新型模型的求解算法等问题,提出了有针对性的新的多目标输电网规划模型,主要研究成果如下:
1)提出改进的强度-帕雷托进化算法(Strength Pareto Evolutionary Algorithm,SPEA),并应用于多目标输电网规划问题的求解。建立基于“吸收孤立节点方法”的种群初始化策略以确保初始种群个体的网络连通性;在多阶段规划中给出一种倒序初始化方法,有效降低线路冗余;针对N和N-1线路容量约束,引入并扩展“边界搜索策略”,保证整个搜索寻优过程在可行域内进行。这些措施增强了初始种群的多样性,改善了Pareto最优解集分布,加快了多目标搜索进程。
2)提出考虑输电阻塞的多目标输电网规划方法。建立年阻塞盈余指标刻画输电阻塞的严重程度,并给出一种基于“虚拟最优解”的排序方法作为非劣解集中的决策参考,分别以年阻塞盈余、线路投资费用和系统缺电成本为规划目标建立多目标输电网规划模型,实现考虑输电阻塞和规划方案的经济性、可靠性的多目标电网优化规划。
3)提出考虑过负荷风险的多目标输电网规划方法。以方案总投资费用贴现值和平均网损期望值为目标函数,建立多目标多阶段输电网规划的期望值模型,以线路有功潮流过负荷随机变量的期望值和标准差构建过负荷风险约束,考虑了风险发生概率和严重程度两方面的特征,通过对不确定性信息的概率建模,利用概率直流潮流进行各随机变量的相关计算,实现了控制过负荷风险条件下的输电网优化规划。
4)提出考虑输电投资收益的多目标输电网规划方法,综合考虑市场参与者对输电投资收益和社会总福利的要求及其对输电网规划的影响。通过计及输电费率的边际成本定价模型,建立输电投资固定成本的弹性回收机制,在此基础上,以输电投资收益率、社会总福利以及输电投资成本为目标函数,建立多目标输电网规划模型,进行规划方案的寻优。
5)提出考虑输电投资风险的多目标输电网规划方法,应用Value at Risk (VaR)市场风险评价指标实现对输电投资收益的风险评估,通过风险控制增强输电投资激励。风险分析中,将节点功率的不确定性作为随机扰动,通过概率最优潮流(Probabilistic-Optimal Power Flow,P-OPF)求取该扰动下输电投资收益的随机分布。将VaR风险指标引入目标函数,并将对输电投资收益率期望值的限制作为约束条件之一,建立多目标多阶段输电网规划模型,进行优化规划。
18节点和77节点统一算例的分析和比较,说明了所提规划模型和求解算法的可行性、有效性和实用性。
The transmission planning in the power market environment is established on the basis of power market, which involves the variation of the planning maker. It aims to make a reasonable transmission expansion to satisfy the inceased power load in future and the requests of market operation, and to maintain proper benefits of all the market participants and the fair market competition. Established in multi-objective transmission planning approach, this dissertion emphasis on handling challenges for transmission planning to adapt the market environment, which include transmission congestion, risks in line overloading, transmission investment profit, risks in transmission investment and solving algorithm for new models. The corresponding means of settlement are presented by proposing new multi-objective planning models. The main returns and innocations of this dissertion are as follows:
1) An improved Strength Pareto Evolutionary Algorithm (SPEA) is proposed and applied in the multi-objective transmission planning. An“isolated nodes absorbing”method for initialization is presented to make all nodes in initial network connected; A reverseorder initialization method is presented to effectively decrease the line redundance. Concerning the“N”and the“N-1”principle, a“borderline search strategy”is adopted and developed to keep the optimal search process within the feasible domain. Those improvements above improve the variety of the initial population and the distribution of the Pareto optimal solution set and effectively accelerate the search process.
2) A novel multi-objective transmission planning model considering transmission congestion is proposed. An index of congestion surplus is presented to describe the transmission congestion degree. And a ranking method based on“the virtual optimal solution”is presented as a reference of decision-making in the Pareto optimal set. With three objectives i.e. yearly congestion surplus, transmission investment cost and cost of power outage, the multi-objective transmission planning model is presented to achieve a planning approach which simultaneously considers transmission congestion and economy and reliability of planning schemes.
3) A novel multi-objective transmission planning approach that considers line overloading risks is proposed. A standard expected value model for multi-objective multi-stage transmission planning is presented to realize the transmission optimal planning with the control of line overloading risks. In this model, a constraint of overloading risks is built with expected value and standard deviation of random line active power and two objectives are given as expected value of the average power loss and discount value of the investment cost. By modeling uncertain informations with probability theory, the probabilistic DC power flow is adopted for the correlated calculations among random variables in the planning model.
4) A novel multi-objective transmission planning approach that considers transmission investment profit is proposed. Requests for transmission investment profit and social welfare are involved in the proposed planning approach. A flexible costrecovering mechanism for transmission fixed cost is setup with a marginal cost transmission pricing model which takes account of the transmission charge rate. Afterthat, a multi-objective transmission planning model is setup for optimal planning with three objectives i.e. rate of return on transmission investment cost, social welfare and transmission investment.
5) A novel multi-objective transmission planning approach that considers transmission investment risk is proposed. The Value at Risk (VaR) index is adopted to evaluate the transmission investment risk. This quantized VaR risk evaluation index can be used to effectively evaluate and control the investment risk and enhance transmission investment incentives. In the analysis of risk, the uncertainty of nodal power is taken as a random disturb and caused by which, the random distribution of transmission investment profit is obtained by solving the probabilistic optimal power flow(P-OPF). After the VaR index is adopted in objective functions and limitation of rate of return on transmission investment is taken as one of constraits, the multi-objective transmission planning model is built up to achieve the optimal transmission planning.
Analysis and comprarision on the 18-bus system and the 77-bus system proves the feasibility, effectivity and practicability of the proposed planning models and solving algorithm in this dissertion.
1)提出改进的强度-帕雷托进化算法(Strength Pareto Evolutionary Algorithm,SPEA),并应用于多目标输电网规划问题的求解。建立基于“吸收孤立节点方法”的种群初始化策略以确保初始种群个体的网络连通性;在多阶段规划中给出一种倒序初始化方法,有效降低线路冗余;针对N和N-1线路容量约束,引入并扩展“边界搜索策略”,保证整个搜索寻优过程在可行域内进行。这些措施增强了初始种群的多样性,改善了Pareto最优解集分布,加快了多目标搜索进程。
2)提出考虑输电阻塞的多目标输电网规划方法。建立年阻塞盈余指标刻画输电阻塞的严重程度,并给出一种基于“虚拟最优解”的排序方法作为非劣解集中的决策参考,分别以年阻塞盈余、线路投资费用和系统缺电成本为规划目标建立多目标输电网规划模型,实现考虑输电阻塞和规划方案的经济性、可靠性的多目标电网优化规划。
3)提出考虑过负荷风险的多目标输电网规划方法。以方案总投资费用贴现值和平均网损期望值为目标函数,建立多目标多阶段输电网规划的期望值模型,以线路有功潮流过负荷随机变量的期望值和标准差构建过负荷风险约束,考虑了风险发生概率和严重程度两方面的特征,通过对不确定性信息的概率建模,利用概率直流潮流进行各随机变量的相关计算,实现了控制过负荷风险条件下的输电网优化规划。
4)提出考虑输电投资收益的多目标输电网规划方法,综合考虑市场参与者对输电投资收益和社会总福利的要求及其对输电网规划的影响。通过计及输电费率的边际成本定价模型,建立输电投资固定成本的弹性回收机制,在此基础上,以输电投资收益率、社会总福利以及输电投资成本为目标函数,建立多目标输电网规划模型,进行规划方案的寻优。
5)提出考虑输电投资风险的多目标输电网规划方法,应用Value at Risk (VaR)市场风险评价指标实现对输电投资收益的风险评估,通过风险控制增强输电投资激励。风险分析中,将节点功率的不确定性作为随机扰动,通过概率最优潮流(Probabilistic-Optimal Power Flow,P-OPF)求取该扰动下输电投资收益的随机分布。将VaR风险指标引入目标函数,并将对输电投资收益率期望值的限制作为约束条件之一,建立多目标多阶段输电网规划模型,进行优化规划。
18节点和77节点统一算例的分析和比较,说明了所提规划模型和求解算法的可行性、有效性和实用性。
The transmission planning in the power market environment is established on the basis of power market, which involves the variation of the planning maker. It aims to make a reasonable transmission expansion to satisfy the inceased power load in future and the requests of market operation, and to maintain proper benefits of all the market participants and the fair market competition. Established in multi-objective transmission planning approach, this dissertion emphasis on handling challenges for transmission planning to adapt the market environment, which include transmission congestion, risks in line overloading, transmission investment profit, risks in transmission investment and solving algorithm for new models. The corresponding means of settlement are presented by proposing new multi-objective planning models. The main returns and innocations of this dissertion are as follows:
1) An improved Strength Pareto Evolutionary Algorithm (SPEA) is proposed and applied in the multi-objective transmission planning. An“isolated nodes absorbing”method for initialization is presented to make all nodes in initial network connected; A reverseorder initialization method is presented to effectively decrease the line redundance. Concerning the“N”and the“N-1”principle, a“borderline search strategy”is adopted and developed to keep the optimal search process within the feasible domain. Those improvements above improve the variety of the initial population and the distribution of the Pareto optimal solution set and effectively accelerate the search process.
2) A novel multi-objective transmission planning model considering transmission congestion is proposed. An index of congestion surplus is presented to describe the transmission congestion degree. And a ranking method based on“the virtual optimal solution”is presented as a reference of decision-making in the Pareto optimal set. With three objectives i.e. yearly congestion surplus, transmission investment cost and cost of power outage, the multi-objective transmission planning model is presented to achieve a planning approach which simultaneously considers transmission congestion and economy and reliability of planning schemes.
3) A novel multi-objective transmission planning approach that considers line overloading risks is proposed. A standard expected value model for multi-objective multi-stage transmission planning is presented to realize the transmission optimal planning with the control of line overloading risks. In this model, a constraint of overloading risks is built with expected value and standard deviation of random line active power and two objectives are given as expected value of the average power loss and discount value of the investment cost. By modeling uncertain informations with probability theory, the probabilistic DC power flow is adopted for the correlated calculations among random variables in the planning model.
4) A novel multi-objective transmission planning approach that considers transmission investment profit is proposed. Requests for transmission investment profit and social welfare are involved in the proposed planning approach. A flexible costrecovering mechanism for transmission fixed cost is setup with a marginal cost transmission pricing model which takes account of the transmission charge rate. Afterthat, a multi-objective transmission planning model is setup for optimal planning with three objectives i.e. rate of return on transmission investment cost, social welfare and transmission investment.
5) A novel multi-objective transmission planning approach that considers transmission investment risk is proposed. The Value at Risk (VaR) index is adopted to evaluate the transmission investment risk. This quantized VaR risk evaluation index can be used to effectively evaluate and control the investment risk and enhance transmission investment incentives. In the analysis of risk, the uncertainty of nodal power is taken as a random disturb and caused by which, the random distribution of transmission investment profit is obtained by solving the probabilistic optimal power flow(P-OPF). After the VaR index is adopted in objective functions and limitation of rate of return on transmission investment is taken as one of constraits, the multi-objective transmission planning model is built up to achieve the optimal transmission planning.
Analysis and comprarision on the 18-bus system and the 77-bus system proves the feasibility, effectivity and practicability of the proposed planning models and solving algorithm in this dissertion.
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