电力市场发电资产虚拟拆分的模式比较

发电资产虚拟拆分一般通过拍卖虚拟发电机组（Virtual Power Plant,VPP）来实现,按VPP机组的实际发电调度权来区分,发电资产虚拟拆分存在金融VPP和物理VPP两种模式。为了比较研究两种虚拟拆分模式对发电商市场力的影响,分别建立了考虑金融VPP和物理VPP的电力市场古诺竞争均衡模型,并采用非线性互补方法来求解。从理论上证明了在相同拆分数量的情况下,采用物理VPP模式的虚拟拆分比金融VPP模式更能降低市场价格。算例仿真进一步表明,当需求弹性越小时,物理VPP模式的虚拟拆分在降低市场价格方面优于金融VPP模式的效果更明显。这意味着对于需求弹性相对较低的电力市场,采用物理VPP模式的虚拟拆分更有利于缓解发电商市场力和提高社会福利。     

区域电力市场应急调峰调频电厂上网电价研究

目前区域电网保留的部分调峰、调频电厂尚无上网电价机制.建立了调峰、调频电厂电价的计算模型,对某区域电力市场调峰、调频电厂电价进行测算,并对调峰、调频电厂电价的敏感性进行分析,算例结果表明该电价计算模型的合理性.     

发电企业在区域电力市场中的协调竞价机制

通过对我国现阶段发电集团公司的组织结构和区域市场现状的分析,讨论了集团公司、区域公司和电厂在区域电力市场协调竞价机制中的地位与作用,并以集团、电厂两级协调竞价体系为研究对象,进一步阐述了该协调竞价机制的基本流程、利益平衡机制及基本的竞价策略.     

市场环境下区域电网调峰的直调机组网际出力优化配置研究

在中国特高压建设、西电东送的大背景下,低谷调峰已经成为诸多区域电网内多个省(市)电网运行的困难之一。为有效缓解区域电网内多个省级电网的调峰难题,引入竞争的电力市场环境,对网内优质的调峰资源进行优化调用。以区域电网为背景,构建分省低谷调峰交易市场,对市场框架进行设计。在此市场环境中提出了以电网负荷过程平稳性和区域直调机组收益最大化为优化目标的网际出力优化配置模型,探索了价格迭代分层优化方案。并针对多种耦合多电网调峰需求方案及统调比例设置方案进行了分析与研究。通过华东直调系统简化算例模拟,可见提出的网际出力优化模型均能够切实高效地解决市场环境下区域电网调峰问题。     

区域电力市场环境下的省电力公司报价策略研究

在区域电力市场环境下,如何利用有效信息,获得最优报价策略是省电力公司急待解决的问题。针对存在多个发电商和多个省电力公司报价的区域电力市场,采用线性报价规则和统一边际电价结算方法对市场出清价的解析式进行推导;在不完全信息条件下,对各发电商和省电力公司的报价策略进行估计,并采用概率统计理论,假设其服从一定的分布;根据其分布参数进一步推导市场出清价的分布。在此基础上,对省电力公司报价成功与不成功的概率进行计算,并采用博弈论构建省电力公司的期望收益优化模型,通过求解得出报价的贝叶斯均衡,即省电力公司的最优报价策略。算例表明,本文提出的报价策略模型是可行的,对省电力公司有一定的指导作用。     

煤电价格联动机制对发电成本-利润影响分析

电煤价格变动对发电成本和利润影响极为显著。国家发展和改革委员会为此制定了煤电联动政策。实施煤电联动机制对发电企业经济效益影响的定量分析是发电企业极为关注的问题。从经济核算和盈亏平衡的角度研究煤电价格联动机制对火电企业成本-利润的影响,进而建立影响大小的计算模型。通过典型实例计算,得出如下结论:如果不实施煤电价格联动机制,煤价每上升1%,发电利润将下降超过3%;而实施煤电价格联动机制(消化比例为30%),则煤价每上升1%,发电利润将下降约0.95%。     

电力市场交易计划中的发电调度规约研究

在电力市场中，机组的出力计划需要根据有关交易计赳和市场规则中的发电调发规约来测定。机组的发电调度规约主要包括机组开停机规约、发电公司(厂)内部各机组间合同电量的分配就约、边际机组间的出力分配规约、机组发电计划调整规约等，结合我国电力市场建设的实际，分别针对全电量竟价模式和部分电量竞价模式分析了竞价开机、合同开机2种机组开停机规约；为协调发、购电双方的利益要求。提出了根据竞价机组可用发电量的比例或竞价上网电量的比例等2种在发电公司(厂)内部分配各竞价机组合同电量的方法；为协调边际机组间的边际负荷分配问题，提出了比例分配法、依次分配法2种分配边际负荷的基本方法；根据机组发电计划的组成特点．提出并分析了日合同计划不可调、日合同计划可调2种机组发电计划调整规约。     

电力市场环境下无功功率集中度的评估和分析(英文)

通过测量发电机有效可用的无功功率,已经实现了无功功率集中度的评估.采用基于价值的方法,考虑有功无功负载最大时所需的无功出力,计算有效可用无功功率,进而确定发电机组的无功集中度,最后分析了负荷水平对无功集中度的影响.并以IEEE 24节点可靠性测试系统和印度75节点系统为例,验证了所提出的评估无功集中度方法的可行性.     

电力市场中市场力的评估与发电竞标策略

提出发电公司竞标价格函数，并构建了在不健全市场下发电公司的竞标模型，在这种竞标模型和竞标价格函数的基础上对市场力加以评估。市场力的评估主要针对供不应求而且具有价格限制的市场。当市场经常出现供不应求的局面时，具有装机容量非常大或市场中主要的市场垄断者或所在地理位置可容易地造成输电阻塞等特性的发电公司，可利用其对市场需求的准确预测，来行使市场力，控制市场价格，从而获取高额的利润。数字仿真结果表明，在市场供不应求和市场供求均衡等2种情况下发电公司实现利润最大化的竞标策略完全不相同，从另一方面看也证实了市场力的存在和表现。     

Minnesota,microgrids and MISO: Getting down to brass tacks on utilizing utility owned/operated microgrids (UOMs) in organized electricity markets

The need for resilient and reliable electric power sources have led to the rise of microgrids. These small power systems are able to provide continued electric power supply to those connected in times of very large scale events (VLSEs) that affect a portion of the larger electric grid. Microgrid systems have also being proposed as a route to “leap frog” the development of electric power systems in parts of the world that still lack access to electricity. In this paper microgrids in the state of Minnesota are considered. The concept of a Utility Owned/Operated Microgrid (UOM) is considered. An important Microgrid Potential Study for Minnesota is analyzed. The potential of using UOMs to provide grid reliability and resilience services in Minnesota, while at the same time providing value for electric utilities through their participation in the Midcontinent Independent System Operator’s (MISO) electricity market is considered.     

基于动态模拟的发电市场情景分析与机制研究

发电容量投资的周期性波动不仅对于电力工业意味着巨大的浪费,影响到输电项目的扩容规划和投资评价,甚至还可能会危及系统的供电可靠性。通过建立发电侧市场的动态模拟模型,选取发电侧市场的多种典型情景研究分析了单一能量机制和容量费用机制下发电投资和市场供需的周期性波动问题。进一步,以容量费用机制为例分析并认为,对于容量电价应当由政府还是市场制定的问题,其核心在于政府或市场能否完全或者在一定程度上替代对方,引导充裕的发电投资和稳定的市场供需。     

An evaluation of the optimal generation mix for controlling carbon dioxide emissions

This paper presents an efficient computational algorithm for selecting the optimal generation mix considering CO₂ emissions. To demonstrate the effectiveness and feasibility of the proposed method, a fundamental study of the evaluation of the optimal generation mix for controlling CO₂ emissions is indicated. Furthermore, by using a parametric analysis which considers load characteristics as parameters, a general trend for the optimal generation mix which is affected by controlling CO₂ can be derived. The proposed method is based on an optimization method known as simulated annealing. In the method, solutions in a generation mix problem are equivalent to state of a physical system, and the cost of a solution is equivalent to the energy of a state. The proposed method can easily accommodate not only CO₂ emissions but also many practical constraints of generation expansion planning, such as integer solutions of unit capacities, condition of existing units, and so on. Case studies with various annual load patterns (combinations of annual load factors and the shapes of annual load duration curve) are presented and discussed. Consequently, a general trend for selecting generation technologies that should be added to a power system is derived, i.e., a useful guideline for studying generation expansion planning under controlling CO₂ emissions can be provided.     

基于电力生产环节的英美电力市场成本覆盖对比分析

在电力市场化改革进程中,欧美国家成熟的电力市场运营对我国电力市场建设有重要的借鉴经验。从电力生产成本覆盖的角度,以英国电力库时期、NETA时期和美国PJM时期电力市场为例,在简单介绍3种电力市场模式结构的基础上,深入分析对比三者在电力生产环节——发电侧、输电侧、变电和配电侧的成本覆盖情况,以宏观介绍和微观比较相结合的方式阐述在不同时期及市场环境下的电力市场交易模式与规则。     

The effect of wind generation and weekday on Spanish electricity spot price forecasting

This paper empirically compares the predictive accuracy of a set of methods for day-ahead spot price forecasting in the Spanish electricity market. The methods come from time series analysis and artificial intelligence disciplines, and include univariate, multivariate, linear and nonlinear. Within the univariate methods, the double seasonal ARIMA and the recently proposed exponential smoothing for double seasonality are compared and used as benchmarks. They allow us to quantify the improvement on price forecasting when including explanatory variables or using more complex models. Dynamic regression models including the electricity load forecast are then considered. Their good performance in price forecasting has been pointed out by many authors. However, we find evidences of their predictive accuracy can be significantly outperformed by accounting the wind generation forecast provided by the System Operator. Moreover, these forecasts can be even more accurate if changes of price's behavior according with the day of the week are taken into account by means of periodic models. The last of the tested methods are feed-forward neural networks used as multivariate nonlinear regression methods with universal function approximation capabilities. The influence of the wind generation forecast on price prediction is also proved with this approach. Detailed out-of-sample results of the tested methods are given.     

Evaluation of the plug‐in hybrid electric vehicle considering learning curve on battery and power generation best mix

The plug‐in hybrid electric vehicle (PHEV) is a technology intended to reduce CO₂ emissions in the transport sector. This paper presents scenarios that show how widely used PHEVs will be in the future, how much CO₂ emissions will be reduced by the introduction of PHEVs, and whether there will be serious effects on the power supply system. PHEVs can run on both gasoline and electricity, and therefore we evaluate CO₂ emissions not only from gasoline consumption but also from electricity consumption. Consideration of the distribution of daily trip distances is important for evaluating the economical benefits and CO₂ emissions resulting from the introduction of PHEVs. Also, future battery costs are very important in constructing PHEV growth scenarios. The growth of the number of PHEVs will make battery costs lower. Thus, we formulate an overall model that combines the passenger car sector and power supply sector, taking account of the distribution of daily trip distances and incorporating a learning curve for battery costs. We use the iteration method to provide a learning curve that is nonlinear. Therefore, we set the battery cost only in the first year of the simulation: battery costs in the later years are calculated in the model. We focus on a 25‐year time period in Japan, starting from 2010, and divided into 5 parts (1st to 5th). The model selects the most economical combinations of car types and power sources. © 2011 Wiley Periodicals, Inc. Electr Eng Jpn, 176(2): 31–40, 2011; Published online in Wiley Online Library ( wileyonlinelibrary.com ). DOI 10.1002/eej.21098     

Assessment of the decarbonization capabilities of solar energy in the strategic Indian electricity generation sector

Increased exploitation of solar power could help in reducing hydrocarbon imports and emissions, but will require significant upfront capital investments. A clear sustainability vision will be needed to shape the strategies required for long-term decarbonization pathways.     

新冠肺炎疫情对2020年电力消费影响及趋势研究

电力消费是电网公司制定中长期电力规划、当年综合计划的重要边界条件,精准衡量2020年新冠肺炎疫情影响意义重大。构建疫情对电力消费的影响测算和预测模型,设计基准、风险情景,从总量、产业、行业、区域、省份等维度测算疫情及政策因素对电力消费影响程度,预测2020年电力消费增长趋势。结果表明：预计疫情及政策因素拉低2020年国家电网经营区用电量增速2.6~3.3个百分点。新冠肺炎疫情对电力消费产生了明显冲击,后期应紧密跟踪疫情影响、滚动调整预测结果。     

新冠肺炎疫情对2020年电力消费影响及趋势研究

电力消费是电网公司制定中长期电力规划、当年综合计划的重要边界条件,精准衡量2020年新冠肺炎疫情影响意义重大。构建疫情对电力消费的影响测算和预测模型,设计基准、风险情景,从总量、产业、行业、区域、省份等维度测算疫情及政策因素对电力消费影响程度,预测2020年电力消费增长趋势。结果表明：预计疫情及政策因素拉低2020年国家电网经营区用电量增速2.6~3.3个百分点。新冠肺炎疫情对电力消费产生了明显冲击,后期应紧密跟踪疫情影响、滚动调整预测结果。     

Evaluation of a plug‐in hybrid electric vehicle considering power generation best mix

In the transport section, it is necessary to reduce the amount of CO₂ emissions and oil dependence. Bio fuels and fuel cell vehicle (FCV), electric vehicle (EV) and plug‐in hybrid electric vehicle (PHEV) are expected to reduce CO₂ emissions and oil dependence. We focus on PHEV. PHEV can reduce total energy consumption because of its high efficiency and can run with both oil and electricity. Introduction of PHEV reduces oil consumption, but it also increases electricity demands. Therefore, we must evaluate PHEV's CO₂ reduction potential, not only in the transport section but also in the power grid section. To take into account the distribution of the daily travel distance is also very important. All energy charged in the PHEV's battery cannot always be used. That influences the evaluation. We formulate the total model that combines passenger car model and power utility grid model, and we also consider the distribution of the daily travel distance. With this model, we show the battery cost per kWh at which PHEV begins to be introduced and oil dependence in the passenger car section is to be reduced to 80%. We also show PHEV's CO₂ reduction potentials and effects on the power supply system. © 2010 Wiley Periodicals, Inc. Electr Eng Jpn, 171(2): 12–22, 2010; Published online in Wiley InterScience ( www.interscience.wiley.com ). DOI 10.1002/eej.20920