新能源电力系统广域源荷互动调度模式理论研究
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摘要
随着社会经济的迅速发展,化石能源耗竭和环境恶化的压力与日俱增；电力作为最重要的能源供应方式,其生产和利用的格局正在发生根本变革。发电侧,化石能源发电形式正在向大容量、低排放机组转变,排放耗能高的小机组逐渐淘汰；可再生能源特别是风能、太阳能等清洁能源发电的并网规模迅速扩大。负荷侧,用电结构发生显著变化,高峰负荷快速增长,导致峰谷差逐年拉大；电动汽车、分布式发电的发展使传统负荷出现了含源负荷的新特征,智能电表的推广将使电网出现分布广域、数量海量的主动负荷节点,用户不再仅仅是电网末端的刚性负荷,而是能够通过高级量测体系参与到系统运营中来,实现与电网的互动。电网的运行特性将更加复杂,调度模式需要做出相应改变,以适应传统电网向新能源电力系统转变的要求。
本文提出了新能源电力系统的广域源荷互动调度模式,并通过基础研究、核心研究和扩展研究三部分来构建较为完整的方法论体系。通过需求侧与电网双向互动的方式,探求一种实现安全经济、低碳环保目标的智能调度形式,进而提升新能源电力系统的运行品质。在此基础上,进行了如下的进一步研究：
研究了需求侧资源的虚拟发电厂管理模式,并基于价格型需求响应实现规模风电消纳。基于虚拟发电厂实现对海量需求侧资源的运行管理,介绍了虚拟发电厂的组成和特征；推导了风电出力的随机模型,并据此建立了风电消纳的随机机会决策模型,决策模型中考虑了需求侧的电量电价互弹性和自弹性,利用随机模拟粒子群算法进行求解。研究表明,通过价格型需求响应,虚拟发电厂能够较好地实现广域需求侧资源管理和参与规模风电消纳的目的,并取得良好的效益。
研究了含风电场电力系统日前发电计划的源荷互动调度模式。在介绍需求侧参与日前发电计划的互动机制的基础上,建立了源荷互动的安全约束机组组合模型,优先调度风电,目标函数为常规机组的发电成本(或耗量)和需求侧资源调用成本(或耗量当量)最小,约束条件综合考虑系统约束、机组约束、需求侧特殊约束以及静态安全约束,构建的混合整数线性规划模型可利用商业优化软件ILOG/CPLEX进行求解,模型和解法能够适用于大规模系统。算例分析表明了所提模型与解法的有效性。
研究了源荷互动调度模式下,含风电场电力系统的模糊机会调度模型与解法。基于可信性理论,推导了风电预测误差的可信性分布函数；继而建立了模糊机会约束条件,根据不同的研究问题分别定义模糊置信度指标,构建起静态经济调度、动态经济调度和安全约束机组组合的模糊机会决策模型；将模糊机会条件转化为其清晰等价类,引入有关的参数将机会条件表示成传统约束条件的形式,便于嵌入到确定性模型中快速求解。研究表明,模糊机会约束调度模型可描述风电预测误差的模糊性对电网调度的影响,决策结果能够取得经济与风险(或可靠性)的折中。
研究了节能减排环境下的广域源荷互动调度问题。根据不同碳排放管制环境,提出了三种节能减排调度模式,分别是考虑碳约束的经济调度、考虑成本约束的低碳调度以及碳排放权与发电联合调度模式,并分别构建了混合整数线性规划模型。其次,设计了一种未来碳排放交易下的需求侧备用竞价与调度模式。提出未来电力输送的过程还将是碳汇流的观点,并据此分析了基于碳交易的需求侧备用交易原理,将碳交易视为需求侧备用的节能减排机会成本；根据不同需求侧资源的调度特性和排放特性,建立了需求侧备用竞价模型和需求侧备用调度的数学模型。算例分析证明了所提模式与模型的有效性,源荷互动调度模式能够取得良好的节能减排与安全经济效益。
With the rapid development of the national economy, and the growing pressure due to the exhaustion of fossil fuel and the deteriorating ecological environment, technological revolutions have gradually hit the production and utilization pattern of electric power, which is the main energy supply resource of the world. In the generation side, fossil energy generation units with larger capacity and lower emission are welcomed, leaving a number of small units with high emission and high energy-consumption being eliminated. Renewable energy such as wind power generation and photovoltaic generation has witnessed a rapid growth in penetration scale. In the demand side, changes in electric utility structure lead to swift growths in peak load and peak-valley difference. Furthermore, with the development of electric vehicles (EV) and distributed generation (DG), a new concept of source-contained load appears. And as the extension of smart meter, the consumers, which can be seen as active load nodes of wide area and large amount, are playing a more and more important role in system operation by means of advanced metering infrastructure(AMI), instead of a simple non-elastic load, and thus realize the interaction with the grid. According to the increasing complexity of grid operation characteristics, the dispatching mode should make changes accordingly to meet the demand of the transition from the conventional power grid to new energy power system.
A new dispatch philosophy named Wide-Area Source and Load Interactive Scheduling mode (WASLIS) is proposed in this paper, the method of which involves the construction of a complete methodological system by means of basic research, core research and patulous research. The source and load interaction mode is employed to achieve a safe, economical, low carbon and environmental-friendly goal, which could promote the operation quality of new energy power system. Further studies are organized as follows.
In charpter3, a mode called virtual power plant (VPP) is studied in order to manage the large amount of demand side resources, and a chance constrained model to improve wind power usage is founded based on real time price (RTP) demand reponse (DR). Firstly, the concept and characteristics of VPP are introduced and moreover a self-organized management mode is presented. Secondly, based on the stochastic model of wind power output, a random chance constrained model is founded to decide RTP scheme improving wind power usage, which both cross-elastic and self-elastic coefficients of electricity price elasticity are considered. To solve the proposed chance constrained model, a stochastic simulation based particle swarm algorithm is employed. The research showed that according to price-based DR, VPP could achieve the purpose of demand side resource management and improving the ability of wind power usage of power system.
In charpter4, a day-ahead generation scheduling scheme is presented by means of WASLIS for power system wind farm integrated. An interaction mechanism of demand side participating in day-ahead generation scheduling is introduced, moreover a security constrainted unit commitment (SCUC) model and its algorithm are presented for source and load interaction. Considering wind power priority scheduled, the SCUC target function is minimizing both generation cost of conventional power unit and DR implemented cost. Meanwhile constraint conditions include system constraints, unit constraints, demand side special constraints and static security constraint. A mixed integer linear programming (MILP) model is developed to desribe the proposed SCUC problem, which can be solved by CPLEX. Simulation on examples verifies the validity of the proposed model and algorithm, which can be used to solve the large-scale power system SCUC problem.
In charpter5, both fuzzy chance constrained dispatch model and solution in power system contained wind farm are researched under WASLIS mode. Based on credibility theory, the credibility distribution function model of wind power forecast errors is established and then the fuzzy chance constraints are founded. The fuzzy credibility indexes are defined due to different problem, employed to describe the fuzzy chance decision models of static economic dispatch, dynamic economic dispatch and the SCUC. The fuzzy chance constraints are turned into their equivalent forms, and the parameters are proposed to change the chance constraints into traditional constraints, so the deterministic model can be used for fast solution. It is shown that the fuzzy chance constrained dispatch model can describe the impact of fuzziness of wind power forecast errors on the distribution, and the decision result can reach the balance of economic and risk (or reliability).
In charpter6, The WASLIS is studied for energy saving and emission reduction. Firstly, based on different carbon emission regulations, the economic dispatch considering carbon constraint, low-carbon dispatch considering cost constraint and coordinated dispatch of power generation and carbon emission permit are proposed, furthermore MILP model is separately established. And then, a bid-scheduling model of demand side reserve (DSR) is proposed considering the future carbon emission trading. The process of future power transmission is also carbon flow, and based on this point of view, the DSR trading principle based on carbon trading is researched, in which the carbon trading is treaded as DSR opportunity cost for energy saving and emission reduction. The trading model and dispatch model of DSR are formed based on different dispatch and emission properties of demand side resource. The analysis of the example proves the effectiveness of the pattern and the model, and WASLIS can bring good benefit on all aspects of economical efficiency, energy saving, emission reduction and safety.
本文提出了新能源电力系统的广域源荷互动调度模式,并通过基础研究、核心研究和扩展研究三部分来构建较为完整的方法论体系。通过需求侧与电网双向互动的方式,探求一种实现安全经济、低碳环保目标的智能调度形式,进而提升新能源电力系统的运行品质。在此基础上,进行了如下的进一步研究：
研究了需求侧资源的虚拟发电厂管理模式,并基于价格型需求响应实现规模风电消纳。基于虚拟发电厂实现对海量需求侧资源的运行管理,介绍了虚拟发电厂的组成和特征；推导了风电出力的随机模型,并据此建立了风电消纳的随机机会决策模型,决策模型中考虑了需求侧的电量电价互弹性和自弹性,利用随机模拟粒子群算法进行求解。研究表明,通过价格型需求响应,虚拟发电厂能够较好地实现广域需求侧资源管理和参与规模风电消纳的目的,并取得良好的效益。
研究了含风电场电力系统日前发电计划的源荷互动调度模式。在介绍需求侧参与日前发电计划的互动机制的基础上,建立了源荷互动的安全约束机组组合模型,优先调度风电,目标函数为常规机组的发电成本(或耗量)和需求侧资源调用成本(或耗量当量)最小,约束条件综合考虑系统约束、机组约束、需求侧特殊约束以及静态安全约束,构建的混合整数线性规划模型可利用商业优化软件ILOG/CPLEX进行求解,模型和解法能够适用于大规模系统。算例分析表明了所提模型与解法的有效性。
研究了源荷互动调度模式下,含风电场电力系统的模糊机会调度模型与解法。基于可信性理论,推导了风电预测误差的可信性分布函数；继而建立了模糊机会约束条件,根据不同的研究问题分别定义模糊置信度指标,构建起静态经济调度、动态经济调度和安全约束机组组合的模糊机会决策模型；将模糊机会条件转化为其清晰等价类,引入有关的参数将机会条件表示成传统约束条件的形式,便于嵌入到确定性模型中快速求解。研究表明,模糊机会约束调度模型可描述风电预测误差的模糊性对电网调度的影响,决策结果能够取得经济与风险(或可靠性)的折中。
研究了节能减排环境下的广域源荷互动调度问题。根据不同碳排放管制环境,提出了三种节能减排调度模式,分别是考虑碳约束的经济调度、考虑成本约束的低碳调度以及碳排放权与发电联合调度模式,并分别构建了混合整数线性规划模型。其次,设计了一种未来碳排放交易下的需求侧备用竞价与调度模式。提出未来电力输送的过程还将是碳汇流的观点,并据此分析了基于碳交易的需求侧备用交易原理,将碳交易视为需求侧备用的节能减排机会成本；根据不同需求侧资源的调度特性和排放特性,建立了需求侧备用竞价模型和需求侧备用调度的数学模型。算例分析证明了所提模式与模型的有效性,源荷互动调度模式能够取得良好的节能减排与安全经济效益。
With the rapid development of the national economy, and the growing pressure due to the exhaustion of fossil fuel and the deteriorating ecological environment, technological revolutions have gradually hit the production and utilization pattern of electric power, which is the main energy supply resource of the world. In the generation side, fossil energy generation units with larger capacity and lower emission are welcomed, leaving a number of small units with high emission and high energy-consumption being eliminated. Renewable energy such as wind power generation and photovoltaic generation has witnessed a rapid growth in penetration scale. In the demand side, changes in electric utility structure lead to swift growths in peak load and peak-valley difference. Furthermore, with the development of electric vehicles (EV) and distributed generation (DG), a new concept of source-contained load appears. And as the extension of smart meter, the consumers, which can be seen as active load nodes of wide area and large amount, are playing a more and more important role in system operation by means of advanced metering infrastructure(AMI), instead of a simple non-elastic load, and thus realize the interaction with the grid. According to the increasing complexity of grid operation characteristics, the dispatching mode should make changes accordingly to meet the demand of the transition from the conventional power grid to new energy power system.
A new dispatch philosophy named Wide-Area Source and Load Interactive Scheduling mode (WASLIS) is proposed in this paper, the method of which involves the construction of a complete methodological system by means of basic research, core research and patulous research. The source and load interaction mode is employed to achieve a safe, economical, low carbon and environmental-friendly goal, which could promote the operation quality of new energy power system. Further studies are organized as follows.
In charpter3, a mode called virtual power plant (VPP) is studied in order to manage the large amount of demand side resources, and a chance constrained model to improve wind power usage is founded based on real time price (RTP) demand reponse (DR). Firstly, the concept and characteristics of VPP are introduced and moreover a self-organized management mode is presented. Secondly, based on the stochastic model of wind power output, a random chance constrained model is founded to decide RTP scheme improving wind power usage, which both cross-elastic and self-elastic coefficients of electricity price elasticity are considered. To solve the proposed chance constrained model, a stochastic simulation based particle swarm algorithm is employed. The research showed that according to price-based DR, VPP could achieve the purpose of demand side resource management and improving the ability of wind power usage of power system.
In charpter4, a day-ahead generation scheduling scheme is presented by means of WASLIS for power system wind farm integrated. An interaction mechanism of demand side participating in day-ahead generation scheduling is introduced, moreover a security constrainted unit commitment (SCUC) model and its algorithm are presented for source and load interaction. Considering wind power priority scheduled, the SCUC target function is minimizing both generation cost of conventional power unit and DR implemented cost. Meanwhile constraint conditions include system constraints, unit constraints, demand side special constraints and static security constraint. A mixed integer linear programming (MILP) model is developed to desribe the proposed SCUC problem, which can be solved by CPLEX. Simulation on examples verifies the validity of the proposed model and algorithm, which can be used to solve the large-scale power system SCUC problem.
In charpter5, both fuzzy chance constrained dispatch model and solution in power system contained wind farm are researched under WASLIS mode. Based on credibility theory, the credibility distribution function model of wind power forecast errors is established and then the fuzzy chance constraints are founded. The fuzzy credibility indexes are defined due to different problem, employed to describe the fuzzy chance decision models of static economic dispatch, dynamic economic dispatch and the SCUC. The fuzzy chance constraints are turned into their equivalent forms, and the parameters are proposed to change the chance constraints into traditional constraints, so the deterministic model can be used for fast solution. It is shown that the fuzzy chance constrained dispatch model can describe the impact of fuzziness of wind power forecast errors on the distribution, and the decision result can reach the balance of economic and risk (or reliability).
In charpter6, The WASLIS is studied for energy saving and emission reduction. Firstly, based on different carbon emission regulations, the economic dispatch considering carbon constraint, low-carbon dispatch considering cost constraint and coordinated dispatch of power generation and carbon emission permit are proposed, furthermore MILP model is separately established. And then, a bid-scheduling model of demand side reserve (DSR) is proposed considering the future carbon emission trading. The process of future power transmission is also carbon flow, and based on this point of view, the DSR trading principle based on carbon trading is researched, in which the carbon trading is treaded as DSR opportunity cost for energy saving and emission reduction. The trading model and dispatch model of DSR are formed based on different dispatch and emission properties of demand side resource. The analysis of the example proves the effectiveness of the pattern and the model, and WASLIS can bring good benefit on all aspects of economical efficiency, energy saving, emission reduction and safety.
引文
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