含分布式发电的配电网优化运行研究
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摘要
近年来,随着全球对环境保护和节能问题的日益关注,以及风力发电、光伏发电等可再生能源发电技术的日益成熟,分布式发电(Distributed Generation, DG)技术成为国内外研究的热点。DG具有安装灵活、供电方便、环保等特点,通常DG安装在用户附近以增强负荷的供电可靠性及电能质量。DG接入配电网后,配电网结构和运行控制方式都将发生巨大改变。配电网自动化和需求侧管理需要考虑与DG间的协调控制,使其控制和管理将变得更加复杂。目前,国内外研究者在DG对电力系统的影响方面作了较多的研究,但对DG并网后配电网的优化运行研究得还较少。因此,研究DG并网后的配电网优化运行是大规模DG接入配电网急需解决的问题,具有重要的理论意义和实际意义。本文对含DG的配电网三相潮流算法、含DG的配电网重构与供电恢复、双馈电机风电场并网后的配电网无功优化以及风电场无功优化与配电网重构的间协调控制等方面进行了深入的研究,主要研究成果如下:
(1)为解决不同类型DG并入配电网后的潮流计算,本文建立了风力发电、光伏电池等不同类型DG在潮流计算中的数学模型,提出了基于前推回代法的可处理PQ、PV节点类型DG的配电网三相潮流算法。根据发电机通常采用电压正序分量幅值作为电压调节参数的原理,将PV节点DG的电压正序分量幅值作为修正变量,采用灵敏度补偿算法计算PV节点无功补偿量。最后通过IEEE34节点系统算例验证了该算法的正确性,并分析了不同类型DG对配电网电压的影响。
(2)研究了DG并网后配电网在正常运行条件下和故障情况下的重构问题和供电恢复问题。正常运行条件下,提出了一种基于粒子群优化算法的配电网重构和DG注入功率综合优化算法。该算法考虑了DG注入功率对重构的影响,在对电网进行重构的同时将DG作为可调度设备对其注入功率进行优化,提高了DG并网后配电网的电能质量和供电可靠性。当配电网发生严重故障引起大面积停电时,考虑DG并网后孤岛效应产生的影响,提出了一种利用DG孤岛效应的配电网供电恢复算法。该算法首先将DG按孤岛划分方案转入孤岛运行模式维持对孤岛内重要负荷供电,然后采用基于二进制粒子群优化算法的供电恢复算法对孤岛外非故障停电区域进行供电恢复。最后,通过算例验证了该算法的有效性。
(3)研究了双馈电机风电场并网后的配电网无功优化问题。建立了双馈感应风电机组的稳态数学模型,分析了双馈感应风电机组的P-Q容量极限,根据双馈感应风电机组灵活的无功调节能力提出在最大效率利用风能前提下,将双馈电机风电场作为连续无功源参与配电网无功优化。该算法将风电场在不同风速条件下的无功出力极限作为约束条件,考虑了风电场无功调节极限与风电场并网点电压和风速间的关系,最后以系统有功功率损耗和电压偏差最小为目标函数,采用粒子群优化算法对含双馈电机风电场的配电网无功优化问题进行了求解。研究结果表明,利用双馈感应风电机组灵活的无功调节能力,将双馈电机风电场作为连续无功源参与配电网无功电压调节能大大节省风电场并网后额外安装大容量无功补偿装置产生的配置费用,并能有效解决传统配电网无功调压手段因调节离散化、调节速度慢、难以实现风电场并网后电压连续调节等问题。
(4)鉴于配电网络无功优化和重构是配电网络优化运行的两种主要措施,本文提出了一种含小波变异算子混合粒子群优化算法的风电场无功优化控制与配电网络重构的综合优化算法。该算法将双馈电机风电场无功功率和配电网转换开关状态作为控制变量,在优化网络结构的同时寻求风电场最优无功出力以达到系统有功功率损耗最低和电压偏差最小的目的。研究结果表明该算法相对于单独进行风电场无功优化控制或配电网重构能进一步降低系统有功功率损耗和提高电压质量,实现了风电机组无功优化控制与配电网重构间的协调控制。
In recent years, along with increasing global concerns for environmental protection and energy saving issues, and with wind power, photovoltaic power generation and other renewable energy technologies becoming more sophisticated, the Distributed Generation (DG) technology has become a hot research topic. Therefore, after DG connected into the distribution network, the distribution network structure, operation and control mode will be tremendous changed, and the distribution automation and demand side management need to consider the coordination between DG and distribution network control, distribution system control and management will become more complex. At present, domestic and foreign researchers have done much research in the DG impact on the power system, but few of them studied on the distribution system optimal operation with grid-connected DG. Thus, study of the distribution system optimal operation after DG connected in the distribution network become an urgent need when large-scale DG access to distribution network, it have important theoretical and practical significance.
In this dissertation, the distribution network optimal operation with grid-connected DG is studied. The contributions of this dissertation are summarized as follows:
(1) To calculate the power flow of distribution network connected with various DG, a three phase power flow algorithm based on forward and backward substitutions that can cope with DG modeled as PV or PQ nodes is proposed. First, the models of the wind turbines, photovoltaic system in power flow calculation are presented. During the coping with DG modeled as a PV node, the positive sequence voltage magnitude of PV node is used as voltage regulating parameter, which represents the automatic voltage regulation mechanism of a generating unit properly. The sensitivity compensation method is used to calculate the amount of reactive power compensation of PV node. Finally, the correctness of the proposed algorithm is verified by the calculation results of IEEE34-bus test system, and the impacts of various type of DG on distribution network voltage are researched.
(2) In this dissertation, based on the PSO, a joint optimization algorithm of network reconfiguration and injected power of DG is proposed. In this algorithm, the reconfiguration result influenced by the DG injected power is considered and the DG is treated as a dispatchable device. Through combining the network reconfiguration and the DG power injection optimization simultaneously, the power quality and power supply reliability of the distribution network are improved. When serious failures result in large area power blackout, a distribution system service restoration method using DG islanding technique is proposed. In this algorithm, DG switch to the islanding operation mode using islanding algorithm to maintain the power supply for the important load first, then a service restoration method based on the binary particle swarm optimization is proposed to restore non-failure power blackout area outside the islanding. Finally, the correctness of the proposed algorithm is verified.
(3) In this dissertation, the reactive power optimization algorithm in distribution network considering doubly fed induction generator (DFIG) wind farm is proposed. First, the mathematical model of the DFIG wind turbine is developed, and the reactive power generation and absorption capacity for each generated active power of the DFIG wind turbine is analyzed. Utilizing the reactive power regulation capability of DFIG, wind farm made up with doubly fed induction generators is proposed to use as the continuous reactive power source to take part in the reactive power optimization in distribution network. In the proposed algorithm, the reactive power output of the wind farm is utilized as the constraint, and the relationship between the wind farm reactive power regulation capacity and the connection point voltage and the wind speed is considered, finally, the real power loss minimization is chose as the objective function and the particle swarm optimization algorithm is applied to solve the problem.
(4) Considering both the distribution network reactive power optimization and reconfiguration are two main measures to optimize distribution networks, a joint optimization algorithm based on an improved hybrid particle swarm optimization with wavelet mutation algorithm (HPSOWM) combining reactive power control of wind farm and network reconfiguration is proposed. In the proposed joint optimization algorithm, reactive power output of wind farm and status of switches are utilized as the control variable to find the optimal network structure and the optimal reactive power output of wind farm for losses minimization and voltage profile improvement. The simulation results show that the joint optimization algorithm gets better solution results than using the wind farm reactive power control optimization or the network reconfiguration alone.
(1)为解决不同类型DG并入配电网后的潮流计算,本文建立了风力发电、光伏电池等不同类型DG在潮流计算中的数学模型,提出了基于前推回代法的可处理PQ、PV节点类型DG的配电网三相潮流算法。根据发电机通常采用电压正序分量幅值作为电压调节参数的原理,将PV节点DG的电压正序分量幅值作为修正变量,采用灵敏度补偿算法计算PV节点无功补偿量。最后通过IEEE34节点系统算例验证了该算法的正确性,并分析了不同类型DG对配电网电压的影响。
(2)研究了DG并网后配电网在正常运行条件下和故障情况下的重构问题和供电恢复问题。正常运行条件下,提出了一种基于粒子群优化算法的配电网重构和DG注入功率综合优化算法。该算法考虑了DG注入功率对重构的影响,在对电网进行重构的同时将DG作为可调度设备对其注入功率进行优化,提高了DG并网后配电网的电能质量和供电可靠性。当配电网发生严重故障引起大面积停电时,考虑DG并网后孤岛效应产生的影响,提出了一种利用DG孤岛效应的配电网供电恢复算法。该算法首先将DG按孤岛划分方案转入孤岛运行模式维持对孤岛内重要负荷供电,然后采用基于二进制粒子群优化算法的供电恢复算法对孤岛外非故障停电区域进行供电恢复。最后,通过算例验证了该算法的有效性。
(3)研究了双馈电机风电场并网后的配电网无功优化问题。建立了双馈感应风电机组的稳态数学模型,分析了双馈感应风电机组的P-Q容量极限,根据双馈感应风电机组灵活的无功调节能力提出在最大效率利用风能前提下,将双馈电机风电场作为连续无功源参与配电网无功优化。该算法将风电场在不同风速条件下的无功出力极限作为约束条件,考虑了风电场无功调节极限与风电场并网点电压和风速间的关系,最后以系统有功功率损耗和电压偏差最小为目标函数,采用粒子群优化算法对含双馈电机风电场的配电网无功优化问题进行了求解。研究结果表明,利用双馈感应风电机组灵活的无功调节能力,将双馈电机风电场作为连续无功源参与配电网无功电压调节能大大节省风电场并网后额外安装大容量无功补偿装置产生的配置费用,并能有效解决传统配电网无功调压手段因调节离散化、调节速度慢、难以实现风电场并网后电压连续调节等问题。
(4)鉴于配电网络无功优化和重构是配电网络优化运行的两种主要措施,本文提出了一种含小波变异算子混合粒子群优化算法的风电场无功优化控制与配电网络重构的综合优化算法。该算法将双馈电机风电场无功功率和配电网转换开关状态作为控制变量,在优化网络结构的同时寻求风电场最优无功出力以达到系统有功功率损耗最低和电压偏差最小的目的。研究结果表明该算法相对于单独进行风电场无功优化控制或配电网重构能进一步降低系统有功功率损耗和提高电压质量,实现了风电机组无功优化控制与配电网重构间的协调控制。
In recent years, along with increasing global concerns for environmental protection and energy saving issues, and with wind power, photovoltaic power generation and other renewable energy technologies becoming more sophisticated, the Distributed Generation (DG) technology has become a hot research topic. Therefore, after DG connected into the distribution network, the distribution network structure, operation and control mode will be tremendous changed, and the distribution automation and demand side management need to consider the coordination between DG and distribution network control, distribution system control and management will become more complex. At present, domestic and foreign researchers have done much research in the DG impact on the power system, but few of them studied on the distribution system optimal operation with grid-connected DG. Thus, study of the distribution system optimal operation after DG connected in the distribution network become an urgent need when large-scale DG access to distribution network, it have important theoretical and practical significance.
In this dissertation, the distribution network optimal operation with grid-connected DG is studied. The contributions of this dissertation are summarized as follows:
(1) To calculate the power flow of distribution network connected with various DG, a three phase power flow algorithm based on forward and backward substitutions that can cope with DG modeled as PV or PQ nodes is proposed. First, the models of the wind turbines, photovoltaic system in power flow calculation are presented. During the coping with DG modeled as a PV node, the positive sequence voltage magnitude of PV node is used as voltage regulating parameter, which represents the automatic voltage regulation mechanism of a generating unit properly. The sensitivity compensation method is used to calculate the amount of reactive power compensation of PV node. Finally, the correctness of the proposed algorithm is verified by the calculation results of IEEE34-bus test system, and the impacts of various type of DG on distribution network voltage are researched.
(2) In this dissertation, based on the PSO, a joint optimization algorithm of network reconfiguration and injected power of DG is proposed. In this algorithm, the reconfiguration result influenced by the DG injected power is considered and the DG is treated as a dispatchable device. Through combining the network reconfiguration and the DG power injection optimization simultaneously, the power quality and power supply reliability of the distribution network are improved. When serious failures result in large area power blackout, a distribution system service restoration method using DG islanding technique is proposed. In this algorithm, DG switch to the islanding operation mode using islanding algorithm to maintain the power supply for the important load first, then a service restoration method based on the binary particle swarm optimization is proposed to restore non-failure power blackout area outside the islanding. Finally, the correctness of the proposed algorithm is verified.
(3) In this dissertation, the reactive power optimization algorithm in distribution network considering doubly fed induction generator (DFIG) wind farm is proposed. First, the mathematical model of the DFIG wind turbine is developed, and the reactive power generation and absorption capacity for each generated active power of the DFIG wind turbine is analyzed. Utilizing the reactive power regulation capability of DFIG, wind farm made up with doubly fed induction generators is proposed to use as the continuous reactive power source to take part in the reactive power optimization in distribution network. In the proposed algorithm, the reactive power output of the wind farm is utilized as the constraint, and the relationship between the wind farm reactive power regulation capacity and the connection point voltage and the wind speed is considered, finally, the real power loss minimization is chose as the objective function and the particle swarm optimization algorithm is applied to solve the problem.
(4) Considering both the distribution network reactive power optimization and reconfiguration are two main measures to optimize distribution networks, a joint optimization algorithm based on an improved hybrid particle swarm optimization with wavelet mutation algorithm (HPSOWM) combining reactive power control of wind farm and network reconfiguration is proposed. In the proposed joint optimization algorithm, reactive power output of wind farm and status of switches are utilized as the control variable to find the optimal network structure and the optimal reactive power output of wind farm for losses minimization and voltage profile improvement. The simulation results show that the joint optimization algorithm gets better solution results than using the wind farm reactive power control optimization or the network reconfiguration alone.
引文
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