电力需求侧响应的效益评估与特性分析
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摘要
随着电力工业的改革、发展,以及社会环境的不断演变,电力需求侧(即用户)的作用正在被逐步得到重新的认识,尤其是化石燃料的枯竭、环保形势的严峻,以及大规模可再生能源发电等并入电网趋势的推进,使电力系统在维持电压、频率质量前提下,发电与需求的实时平衡面临困境,使维持这一平衡可使用的资源越显匮乏。由此,如何将需求侧纳入到电力系统的主动调控之中,以促使电力系统安全、可靠、经济的运行,正在成为业界的共识。因此,在这一背景下,急切需要回答需求侧响应机制与效果的若干问题。如：在市场机制下,发电侧与需求侧间平衡的经济规律,需求侧变动的经济效益指标,以及需求侧变动带来的效益评估等；需求侧大比重的某类别负荷或某行业负荷的用电规律；需求响应作用下的用电行为规律；以及电价制定中,目标群体的聚类及其特征的抽取,以及各类别下电价实施效果评估等问题。这些问题的研究,可为充分挖掘需求侧资源,发挥需求侧在电网运行中的良性互动作用提供理论指导和技术支持。
本文在总结电力需求侧研究成果的基础上,以需求侧响应特性为核心,围绕与发电侧互动、降温负荷规律、阶梯电价和分时电价激励效果等若干角度,依据优化数学理论、统计回归理论、数据挖掘技术,开展了富有成效的研究,其创新性的研究工作和成果体现如下：
(1)考虑机组启停的需求响应效益评估。需求侧响应产生效益的本质是发电侧整体的效率,只有使发电侧效率提高的需求侧响应才是需要的。针对目前需求响应效益评估中不考虑响应后机组启停状态发生改变所存在的问题,以日前机组启停决策问题为基础,建立了考虑需求侧直接参与市场的电力库模型,依据拉格朗日松弛法对该模型予以求解。依此,从综合效益和边际效益两方面探讨需求转移可能引起的机组启停状态的改变,以及电价的变动,同时分析了考虑机组启停后,系统整体和各市场参与者的效益变化,以及效益的再分配机制,揭示了机组启停变化可能引起新的电价尖峰对效益评估的影响,并依据边际效益,分析了用户需求响应参与程度不同时,用户侧与发电侧利益的变化规律,指出需求响应的实施应兼顾发电侧和用户侧。
(2)考虑非气象因素的夏季降温负荷回归分析。季节性变化会导致需求侧用电规律的变化,这一变化中存在大量可实施需求响应的成分,而这一成分又与用电者的状况构成紧密的联系。针对目前电网夏季降温负荷变化规律研究中,仅关注气温等自然环境因素的影响,从而导致模型对降温负荷规律的反映普适性不强的问题,对降温负荷关于温度因子的回归模型做进一步深入分析,从中揭示出非气象因素,即经济状况和发达程度,对降温负荷的关键影响。由此,提出考虑经济水平因子和区位电能消费倾向因子等概念下的夏季降温负荷模型,从而提高了模型在时域与地域上的广泛适用性。该模型应用于地区电网,可为地区电网挖掘降温负荷的需求响应资源,有针对性地制定迎峰度夏需求响应措施提供科学依据。
(3)分时电价下用户响应行为的模型与算法。分时电价是国内外都在采用的需求响应措施,也是电力市场化的根本。因此,在若干用户中,分时电价的效果究竟如何,用电行为受分时电价影响的规律是什么等问题急待需要解决。由此,在分时电价实施的背景下,基于电力用户响应行为的大量历史数据,针对如何挖掘其中的用户用电响应规律问题,建立分时电价下电力用户响应行为规律的模型与算法,解决了回归模型输入与输出属性的确定问题,以及含丰富数据信息的训练样本的构建问题,从而实现通过支持向量机回归对该规律的挖掘,取得较好效果。
(4)基于用户聚类的阶梯电价制定方法。阶梯电价是引导不同收入的居民群体(实践中以不同月用电量代表)合理用电,从而促进能源节约的电价政策。在阶梯电价制定中,分档的数量以及各档基准电量的合理确定是核心问题,它关系到如何在尽可能方便操作的情况下,找准目标群体并施以合理激励。基于居民月用电量曲线,本文应用自组织映射(SOM)聚类算法建立了一种居民月用电量聚类分析方法,能够分类把握居民月用电量特征规律,实现了对居民用电阶梯电价分档数及档基准电量的准确提取。本文得出的档基准电量反映出,居民用电存在明显的城乡差异与地区差异,能够为阶梯电价的进一步实施提供了重要参考。
(5)在地区电网中,高耗能行业的负荷在总负荷中占比重很大,它们的用电规律是否能准确把握,实施需求响应措施后效果如何,对于整个地区电网的需求侧管理是至关重要的。在地区电网用电信息采集系统广泛普及的条件下,积累了大量行业及行业中用户个体的负荷信息历史记录,对这样数据进行分析是发现行业用电规律与响应规律的重要途径。本文运用频域分解方法和聚类算法,分别对6类高耗能行业用电的规律以及实施分时电价的效果进行讨论,实现了对行业用电规律与响应规律的准确把握,这将为今后有针对性地对行业负荷进行调控奠定良好的基础。
总之,本文课题是新形势下电力需求侧研究中亟待解决的问题。这些问题的深入探讨和研究,可以使需求侧行为规律把握更清晰,需求侧作用效果更显著,需求侧激励机制的决策更有的放矢。
With the revolution and development of electricity industry and the evolving social environment, the effect of electricity demand side (namely consumers) is gradually re-recognized. Especially, the depletion of fossil fuels, severe pressure on environment, and the large scale integration of renewable generation into power grid make the real time balance between supply and demand becomes more difficult on the premise of the system voltage and frequency quality requirements. The available resources which can be used to keep the balance become scarcer. In order to keep the safe, reliable and economical operation of power systems, it is very necessary to involve the demand side into the active management of the power system and this has already become a consensus of the industry. Therefore, under this background it is eager to solve the problems related to demand response effect and mechanism. These problems include economic rules of balance between supply and demand under the market mechanism, profit of demand side variation, assessment of the profit of the demand side variation, electricity consumption regularity of some large loads belongs to the same category or industry, variation principle of demand under demand response mechanism, clustering of consumers' roup, and the assessment of implementation effect of various electricity price models, etc. The research on these problems can provide theoretical guide and technical support for exploiting demand side resources. They are also helpful when understanding the positive interaction between demand and power grid operation. Based on the existing research on electricity demand, the characteristics of demand response are emphasized. This thesis studies the positive interaction between demand side and generating units, characteristics of cooling loads, assessment of implementation effect of time-of-use electricity price model and multi-step electricity model. The novelty and achievements of the research are shown below:
(1) Responsive profit assessment of demand considering unit on/off status. The essence of the profit produced by the demand response reflects the entire efficiency of generating units. The required demand responses are those who can enhance the efficiency of generation side. In the previous research, when assessing the demand response profit, the variation of unit status is not considered. In this thesis, based on the unit status of day-ahead unit commitment problem, the power pool bidding model which considers the direct participation of demand is established. The model is solved by Lagrangian relaxation method. After the demand is switched, the variations of unit status and electricity price are analyzed in terms of both general profit and marginal profit. The variation and redistribution of profit of every market participant after considering the unit status is computed and analyzed. New electricity price spike which results from the variation of unit status may occur and the effect of the price spike on the profit assessment is revealed. The variations of interest of supply and demand under different demand response participating degree are analyzed in terms of marginal profit. The research reveals that the implementation of demand response should take into account the interest of both supply and demand.
(2) Regression analysis of summer cooling loads considering non-meteorological factors. The demand is seasonally varied and this variation underpins the implementation of demand response management which strongly related to the consumers. Inthe previous research, the research on the variation role of summer grid cooling loads only considers the effect of temperature. Thus the universality of the model is not good enough to reflect the regularity of the cooling loads. In this thesis, the regression model of the cooling loads with respect to the temperature is further analyzed. The key effect of non-meteorological aspects, namely economic conditions and level of development, on the cooling loads is also analyzed. A new summer cooling load model which considers the economical factor and regional energy consumption prosperity factor is proposed. The applicability of the model is enhanced in terms of time domain and geography. When this model is used in regional power systems, it can exploit the cooling loads as demand response resources, and can help in making the demand response strategy.
(3) Model and algorithm of demand response behavior under time-of-use electricity price. Time-of-use electricity is used around the world and it is the basis of the electricity market. Therefore, the implementation effect of time-of-use electricity on some loads needs to be considered. And how the electricity consumption is affected by the time-of-use electricity price also needs to be carefully analyzed. When time-of-use electricity price is implemented, based on the tremendous consumer historical data during the analysis of demand response behavior, the regulation of demand response will be revealed. The model and algorithm of demand response regulation based on time-of-use electricity price will be established. The determination of input and output attributes of the regression model is solved, and the training sample with rich data is also established. Finally, the support vector machine based regression model is successfully implemented.
(4) Determination of multi-step electricity price based on demand clustering. Multi-step electricity price can induce consumers with different level of incomes (which are represented by monthly electricity consumption in practice) consumes electricity reasonably. Finally the total energy can be saved. During the determination of multi-step electricity price, the center problems are to find the methods to determine the number of block and the energy amount for each block. The methods should be simple enough. These methods should also be able to find the appropriate consumers efficiently and reasonably stimulate the consumers. Based on the consumers'monthly demand curve, a demand clustering analysis method is established based on SOM cluster algorithm. This method can achieve the demand characteristics by classifying the consumers. And it can determine the number of block and energy of each block of the multi-step electricity price accurately. The obtained energy of each block reflects the electricity consumption difference between rural and urban, and between different regions. The proposed method provides important support for the further implementing of multi-step electricity price model.
(5) In the regional power system, loads in energy-intensive industries account for a large proportion of the total load. Whether their electricity consumption can be accurately seized has a significant effect on the implementation of the demand response of the entire regional system. Since the information collection system is widespread implemented in region power system, numerous historical load data in many industries are collected. The industrial electricity consumption principles and response characteristics can be achieved based on the analysis of these historical data. In this thesis, frequency domain decomposition method and cluster algorithm are used, the electricity consumption principles of six energy-intensive industries are analyzed. The effect of time-of-use electricity price is discussed. The electricity consumption principle and response characteristic of industries are analyzed. All of these establish a good basis for adjusting the demand in an industry. In a word, this thesis solves the demanding problems in electricity demand side research. The effect of demand is correctly understood by in-depth analysis of these problems mentioned above. The load characteristics and consumer behavior are accurately described. The effect of demand response will be more prominent and the demand side incentive mechanism will be more targeted.
本文在总结电力需求侧研究成果的基础上,以需求侧响应特性为核心,围绕与发电侧互动、降温负荷规律、阶梯电价和分时电价激励效果等若干角度,依据优化数学理论、统计回归理论、数据挖掘技术,开展了富有成效的研究,其创新性的研究工作和成果体现如下：
(1)考虑机组启停的需求响应效益评估。需求侧响应产生效益的本质是发电侧整体的效率,只有使发电侧效率提高的需求侧响应才是需要的。针对目前需求响应效益评估中不考虑响应后机组启停状态发生改变所存在的问题,以日前机组启停决策问题为基础,建立了考虑需求侧直接参与市场的电力库模型,依据拉格朗日松弛法对该模型予以求解。依此,从综合效益和边际效益两方面探讨需求转移可能引起的机组启停状态的改变,以及电价的变动,同时分析了考虑机组启停后,系统整体和各市场参与者的效益变化,以及效益的再分配机制,揭示了机组启停变化可能引起新的电价尖峰对效益评估的影响,并依据边际效益,分析了用户需求响应参与程度不同时,用户侧与发电侧利益的变化规律,指出需求响应的实施应兼顾发电侧和用户侧。
(2)考虑非气象因素的夏季降温负荷回归分析。季节性变化会导致需求侧用电规律的变化,这一变化中存在大量可实施需求响应的成分,而这一成分又与用电者的状况构成紧密的联系。针对目前电网夏季降温负荷变化规律研究中,仅关注气温等自然环境因素的影响,从而导致模型对降温负荷规律的反映普适性不强的问题,对降温负荷关于温度因子的回归模型做进一步深入分析,从中揭示出非气象因素,即经济状况和发达程度,对降温负荷的关键影响。由此,提出考虑经济水平因子和区位电能消费倾向因子等概念下的夏季降温负荷模型,从而提高了模型在时域与地域上的广泛适用性。该模型应用于地区电网,可为地区电网挖掘降温负荷的需求响应资源,有针对性地制定迎峰度夏需求响应措施提供科学依据。
(3)分时电价下用户响应行为的模型与算法。分时电价是国内外都在采用的需求响应措施,也是电力市场化的根本。因此,在若干用户中,分时电价的效果究竟如何,用电行为受分时电价影响的规律是什么等问题急待需要解决。由此,在分时电价实施的背景下,基于电力用户响应行为的大量历史数据,针对如何挖掘其中的用户用电响应规律问题,建立分时电价下电力用户响应行为规律的模型与算法,解决了回归模型输入与输出属性的确定问题,以及含丰富数据信息的训练样本的构建问题,从而实现通过支持向量机回归对该规律的挖掘,取得较好效果。
(4)基于用户聚类的阶梯电价制定方法。阶梯电价是引导不同收入的居民群体(实践中以不同月用电量代表)合理用电,从而促进能源节约的电价政策。在阶梯电价制定中,分档的数量以及各档基准电量的合理确定是核心问题,它关系到如何在尽可能方便操作的情况下,找准目标群体并施以合理激励。基于居民月用电量曲线,本文应用自组织映射(SOM)聚类算法建立了一种居民月用电量聚类分析方法,能够分类把握居民月用电量特征规律,实现了对居民用电阶梯电价分档数及档基准电量的准确提取。本文得出的档基准电量反映出,居民用电存在明显的城乡差异与地区差异,能够为阶梯电价的进一步实施提供了重要参考。
(5)在地区电网中,高耗能行业的负荷在总负荷中占比重很大,它们的用电规律是否能准确把握,实施需求响应措施后效果如何,对于整个地区电网的需求侧管理是至关重要的。在地区电网用电信息采集系统广泛普及的条件下,积累了大量行业及行业中用户个体的负荷信息历史记录,对这样数据进行分析是发现行业用电规律与响应规律的重要途径。本文运用频域分解方法和聚类算法,分别对6类高耗能行业用电的规律以及实施分时电价的效果进行讨论,实现了对行业用电规律与响应规律的准确把握,这将为今后有针对性地对行业负荷进行调控奠定良好的基础。
总之,本文课题是新形势下电力需求侧研究中亟待解决的问题。这些问题的深入探讨和研究,可以使需求侧行为规律把握更清晰,需求侧作用效果更显著,需求侧激励机制的决策更有的放矢。
With the revolution and development of electricity industry and the evolving social environment, the effect of electricity demand side (namely consumers) is gradually re-recognized. Especially, the depletion of fossil fuels, severe pressure on environment, and the large scale integration of renewable generation into power grid make the real time balance between supply and demand becomes more difficult on the premise of the system voltage and frequency quality requirements. The available resources which can be used to keep the balance become scarcer. In order to keep the safe, reliable and economical operation of power systems, it is very necessary to involve the demand side into the active management of the power system and this has already become a consensus of the industry. Therefore, under this background it is eager to solve the problems related to demand response effect and mechanism. These problems include economic rules of balance between supply and demand under the market mechanism, profit of demand side variation, assessment of the profit of the demand side variation, electricity consumption regularity of some large loads belongs to the same category or industry, variation principle of demand under demand response mechanism, clustering of consumers' roup, and the assessment of implementation effect of various electricity price models, etc. The research on these problems can provide theoretical guide and technical support for exploiting demand side resources. They are also helpful when understanding the positive interaction between demand and power grid operation. Based on the existing research on electricity demand, the characteristics of demand response are emphasized. This thesis studies the positive interaction between demand side and generating units, characteristics of cooling loads, assessment of implementation effect of time-of-use electricity price model and multi-step electricity model. The novelty and achievements of the research are shown below:
(1) Responsive profit assessment of demand considering unit on/off status. The essence of the profit produced by the demand response reflects the entire efficiency of generating units. The required demand responses are those who can enhance the efficiency of generation side. In the previous research, when assessing the demand response profit, the variation of unit status is not considered. In this thesis, based on the unit status of day-ahead unit commitment problem, the power pool bidding model which considers the direct participation of demand is established. The model is solved by Lagrangian relaxation method. After the demand is switched, the variations of unit status and electricity price are analyzed in terms of both general profit and marginal profit. The variation and redistribution of profit of every market participant after considering the unit status is computed and analyzed. New electricity price spike which results from the variation of unit status may occur and the effect of the price spike on the profit assessment is revealed. The variations of interest of supply and demand under different demand response participating degree are analyzed in terms of marginal profit. The research reveals that the implementation of demand response should take into account the interest of both supply and demand.
(2) Regression analysis of summer cooling loads considering non-meteorological factors. The demand is seasonally varied and this variation underpins the implementation of demand response management which strongly related to the consumers. Inthe previous research, the research on the variation role of summer grid cooling loads only considers the effect of temperature. Thus the universality of the model is not good enough to reflect the regularity of the cooling loads. In this thesis, the regression model of the cooling loads with respect to the temperature is further analyzed. The key effect of non-meteorological aspects, namely economic conditions and level of development, on the cooling loads is also analyzed. A new summer cooling load model which considers the economical factor and regional energy consumption prosperity factor is proposed. The applicability of the model is enhanced in terms of time domain and geography. When this model is used in regional power systems, it can exploit the cooling loads as demand response resources, and can help in making the demand response strategy.
(3) Model and algorithm of demand response behavior under time-of-use electricity price. Time-of-use electricity is used around the world and it is the basis of the electricity market. Therefore, the implementation effect of time-of-use electricity on some loads needs to be considered. And how the electricity consumption is affected by the time-of-use electricity price also needs to be carefully analyzed. When time-of-use electricity price is implemented, based on the tremendous consumer historical data during the analysis of demand response behavior, the regulation of demand response will be revealed. The model and algorithm of demand response regulation based on time-of-use electricity price will be established. The determination of input and output attributes of the regression model is solved, and the training sample with rich data is also established. Finally, the support vector machine based regression model is successfully implemented.
(4) Determination of multi-step electricity price based on demand clustering. Multi-step electricity price can induce consumers with different level of incomes (which are represented by monthly electricity consumption in practice) consumes electricity reasonably. Finally the total energy can be saved. During the determination of multi-step electricity price, the center problems are to find the methods to determine the number of block and the energy amount for each block. The methods should be simple enough. These methods should also be able to find the appropriate consumers efficiently and reasonably stimulate the consumers. Based on the consumers'monthly demand curve, a demand clustering analysis method is established based on SOM cluster algorithm. This method can achieve the demand characteristics by classifying the consumers. And it can determine the number of block and energy of each block of the multi-step electricity price accurately. The obtained energy of each block reflects the electricity consumption difference between rural and urban, and between different regions. The proposed method provides important support for the further implementing of multi-step electricity price model.
(5) In the regional power system, loads in energy-intensive industries account for a large proportion of the total load. Whether their electricity consumption can be accurately seized has a significant effect on the implementation of the demand response of the entire regional system. Since the information collection system is widespread implemented in region power system, numerous historical load data in many industries are collected. The industrial electricity consumption principles and response characteristics can be achieved based on the analysis of these historical data. In this thesis, frequency domain decomposition method and cluster algorithm are used, the electricity consumption principles of six energy-intensive industries are analyzed. The effect of time-of-use electricity price is discussed. The electricity consumption principle and response characteristic of industries are analyzed. All of these establish a good basis for adjusting the demand in an industry. In a word, this thesis solves the demanding problems in electricity demand side research. The effect of demand is correctly understood by in-depth analysis of these problems mentioned above. The load characteristics and consumer behavior are accurately described. The effect of demand response will be more prominent and the demand side incentive mechanism will be more targeted.
引文
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