福建电力需求侧管理的企业对策

本文介绍需求侧管理(DemandSideManegement,简称DSM)和综合资源规划(IntegratedResoursePlanning,简称IRP),分析在实施海峡西岸经济区的战略中的电力资源“瓶颈”,侧重评价当前实施电力需求侧管理系统工程中急需解决的问题。针对电力企业在实施电力需求侧管理中的主体作用,提出电力企业改革经营理念和经营模式,以发挥需求侧管理的功效。     

试析考虑需求侧管理的微网经济优化运行

;为追求更高的效益,将微网电力负荷建立成由固定负荷、可转移负荷和随机负荷三部分组成的考虑需求侧管理的微网经济优化模型。考虑需求侧管理的微网优化模型是以可转移负荷为侧管理的主要内容和目标,它将分布式电源和需求侧负荷管理中的非线性问题转化为混合整数的规划问题进行解决,并且利用相关软件得出侧管理下的微网具有使用的经济价值。     

基于Benders分解算法的跨区互联电力系统协调规划模型

研究跨区互联电力系统的协调规划,对于提高投资效率实现更大范围的资源配置具有较强现实意义。本文首先描述多区域电力系统扩张规划问题,并建立多区域扩张规划模型,旨在寻求最优的扩容方案,以最小投入来满足多区域电力系统负荷增长需求;其次,采用Benders分解算法将多区域扩张规划问题分解为一个规划主问题和一个运行子问题,通过主子问题之间的迭代求解,获得最终的最优解;最后,对某个典型的包含7个区域的多区域电力系统进行模拟仿真,验证了本文所构建模型及算法的有效性。     

二重趋势性季节型电力负荷预测组合灰色神经网络模型

对于具有增长和波动二重趋势性的季节型电力负荷,首次提出了季节型负荷预测的组合优化灰色神经网络模型,研究了同时考虑两种(非线性)趋势的复杂季节型负荷预测问题,说明了此优化模型分别优于两种单一发展趋势负荷预测模型,给出了电力负荷预测的应用实例,为季节型电力负荷预测提供了一种新的、有效的方法。     

供热工程中规划与现状分析的协调问题探讨

供热系统是一个城市重要的组成部分,城市的供热关系到居民的生活和社会的生产,只有对供热工程进行合理有效的规划,才能最大限度地保证城市的经济效益和社会效益。在供热中如何因地制宜地合理有效地利用能源,提高资源的利用效率是当前的首要问题。我国是资源大国,同时也是人口大国,每年的能源消耗是巨大的,能源造成的环境污染也是不能忽视的,如果不提高能源的利用效率,不仅会给环境造成巨大的压力,也会造成能源的枯竭。因此,为了响应国家的号召,坚持可持续发展战略,必须找到解决问题的办法。文章主要对供热工程中规划与现状分析的协调问题进行探讨。     

高比例可再生能源接入下的电力系统规划研究

可再生能源是实现能源转型和可持续发展的关键.然而，高比例可再生能源接入下的电力系统所面临的间歇性、波动性、以及不确定性远高于当前水平，电力供应体系的经济稳定运行遭遇巨大挑战.本研究将电力系统短期经济调度与长期产能扩张规划相结合，通过聚类和情景树技术引入可再生能源的不确定性，建立高时空分辨的电力系统随机优化模型，旨在揭示电力系统如何通过电源、电网、储能等措施的协同优化经济有效地接纳高比例可再生能源.研究结果表明，不同区域在应对风、光间歇性和不确定性方面的主要措施是有显著差异的，电力系统需协同优化风、光、煤产业布局，强化跨区消纳和调峰能力，发挥电源、电网、储能的互补优势，同时避免技术锁定效应.     

粒子群优化灰色模型在负荷预测中的应用

针对电力系统负荷特性,分析灰色模型GM(1,1)的应用局限性,引入向量α改进灰色模型背景值序列的计算公式,从而构建了适应性更强的GM(1,1,α)模型。应用粒子群优化算法非线性全局寻优能力来求解最优α值,提出了基于粒子群优化算法的灰色模型PSOGM,并给出了电力负荷预测的应用实例。实例证明PSOGM模型具有较高的预测精度和较广的应用范围。     

分布式与集中式储能并存的微电网负荷优化调度

发展微电网是合理利用可再生能源的重要途径，储能系统在协调微电网中多类型能源并实现高效的协同优化过程中发挥了重要的作用。本文构建了同时考虑分布式储能系统(distributed energy storage systems, DESSs)和集中式储能系统(centralized energy storage system, CESS)的微电网负荷优化调度模型，该模型同时考虑了微电网的经济成本和稳定性，旨在降低微电网经济成本的同时增加微电网的稳定性。同时，提出的调度模型考虑了需求响应的影响。实验表明，与只有单一DESSs的微电网相比，同时含有DESSs和CESS的微电网可以进一步地降低微电网的经济成本，并提高微电网的稳定性。而微电网通过参与需求响应能够实现更低的经济成本和更高的稳定性。此外，研究发现经济成本和稳定性权重因子对微电网调度的影响，权重因子的选取是微电网经济性和稳定性之间的权衡，提出了兼顾微电网经济性与稳定性的最优解的求解方法。本文的研究对于具有DESSs和CESS的微电网的经济稳定运行具有重要的现实意义。     

对中长期负荷预测方法的综述

中长期负荷预测各种预测方法都具有其各自的优缺点和适用范围,在实际预测工作中,必须根据实际情况,着重从预测目标、期限、精确度等诸多方面作出合理选择,寻求能获取所需精度的预测方法。本文针对电力系统中长期电力负荷预测方法做出分析。     

能源系统复杂性管理建模方法研究

提出了一种基于能源系统微观主体行为的仿真建模方法,将微观仿真与中观能源规划、宏观社会经济均衡有机结合,进而发展出由演化模块(E)、综合优化模块(O)及系统动力学模块(D)构成,以智慧(W)为统领的Weod架构,体现了综合集成方法从定性到定量,人机结合实现信息知识和智慧的综合集成思想,旨在为能源系统复杂性预测、评价与优化管理提供一个有力的方法工具。     

中国电力企业对电力体制改革适应性的管理结构模型研究

中国电力市场化改革实施以来效果如何,是公众广为关注的问题.本文依据路径-目标理论,构建了电力企业对电力体制改革适应性的管理结构模型,通过问卷调查分析,运用PLS(Partial Least Squares)方法,从电力企业管理的微观角度,审视电力体制改革对发电、电网两种类型企业的影响以及电力体制改革中存在的问题.模型可靠性和有效性良好.结果表明,市场化改革的思路可以有效引导企业积极变革,企业管理总体上是健康的;电力体制改革应该增强系统性,增加透明度,稳定企业对改革的预期;发电企业和电网企业需要进一步适应市场化环境,提高发展战略等薄弱环节的管理水平.     

基于可变区间权重的中期用电量半参数预测模型

由于数据变化规律的多样性,中期电力负荷的波动有着不同于短期、长期负荷的特点。基于电力系统复杂性的研究视角,重点讨论了中期负荷预测过程中模型的不确定性、参数的时变特性以及负荷波动的周期性规律。根据中期负荷的数据特性,建立了基于非参数修匀的半参数模型,定义了函数区间的划分粒度以及模型权重的求解方法,提出了基于可变区间权重的动态预测方法,给出了基于经验模态分解和波动能量分析的噪声序列提取、检验方法。试验研究结果表明,气候因素对用电消耗的影响最大,经济因素次之;从选取的指标来看,不同时期的影响因素对于模型的解释能力是时变的;所提方法能够对电力负荷进行精确的多粒度、多维度分析,进而掌握其局部变化规律,可有效用于电力系统中期负荷预测。     

Evaluating and Visualizing the Economic Impact of Commercial Districts Due to an Electric Power Network Disruption

Critical infrastructure networks enable social behavior, economic productivity, and the way of life of communities. Disruptions to these cyber–physical–social networks highlight their importance. Recent disruptions caused by natural phenomena, including Hurricanes Harvey and Irma in 2017, have particularly demonstrated the importance of functioning electric power networks. Assessing the economic impact (EI) of electricity outages after a service disruption is a challenging task, particularly when interruption costs vary by the type of electric power use (e.g., residential, commercial, industrial). In contrast with most of the literature, this work proposes an approach to spatially evaluate EIs of disruptions to particular components of the electric power network, thus enabling resilience‐based preparedness planning from economic and community perspectives. Our contribution is a mix‐method approach that combines EI evaluation, component importance analysis, and GIS visualization for decision making. We integrate geographic information systems and an economic evaluation of sporadic electric power outages to provide a tool to assist with prioritizing restoration of power in commercial areas that have the largest impact. By making use of public data describing commercial market value, gross domestic product, and electric area distribution, this article proposes a method to evaluate the EI experienced by commercial districts. A geospatial visualization is presented to observe and compare the areas that are more vulnerable in terms of EI based on the areas covered by each distribution substation. Additionally, a heat map is developed to observe the behavior of disrupted substations to determine the important component exhibiting the highest EI. The proposed resilience analytics approach is applied to analyze outages of substations in the boroughs of New York City.     

Risk-Management and Risk-Analysis-Based Decision Tools for Attacks on Electric Power

Incident data about disruptions to the electric power grid provide useful information that can be used as inputs into risk management policies in the energy sector for disruptions from a variety of origins, including terrorist attacks. This article uses data from the Disturbance Analysis Working Group (DAWG) database, which is maintained by the North American Electric Reliability Council (NERC), to look at incidents over time in the United States and Canada for the period 1990-2004. Negative binomial regression, logistic regression, and weighted least squares regression are used to gain a better understanding of how these disturbances varied over time and by season during this period, and to analyze how characteristics such as number of customers lost and outage duration are related to different characteristics of the outages. The results of the models can be used as inputs to construct various scenarios to estimate potential outcomes of electric power outages, encompassing the risks, consequences, and costs of such outages.     

The flow refueling location problem with load flow control

Battery electric vehicles as well as renewable energy are two key factors that can contribute significantly to sustainable development within the transportation and the energy sector. However, the market introduction of these technologies results in new challenges, especially with regard to the interaction between both sectors. So far, neither location models for charging stations nor load flow models for the electrical grid consider these interactions sufficiently. Thus, an integration of planning problems from both sectors is needed in order to exploit potential synergies and to avoid negative impacts.In this paper, we present such an integrated planning approach to locate charging infrastructure for battery electric vehicles considering interactions with the electrical grid. Herein, we combine a charging station location model and a power flow model with integrated energy stores. We aim at determining a network configuration that satisfies the charging demand of battery electric vehicles, herein maximizing the benefits and minimizing the negative impacts resulting from the interactions of the two sectors. To demonstrate the benefit of our integrated planning approach, we apply it to an illustrative case and present results of a sensitivity analysis. We derive managerial insights regarding the interdependencies of the number of sited charging stations and the installed storage capacity based on renewable energy generation and charging demand.     

Planning for electricity generation in India

A country's economy and its energy base have a complex yet strong relationship. As a result the provisioning of an increasing quanta of energy is a vital pre-requisite for the economic growth of a country. With certain exceptions it has been found from a study of the per capita electric energy generation and per capita income that between 0·7 and 2 units of electric energy are required for generation of one unit of income. The exact relationship will vary from country to country depending on the particular energy-mix, the extent of industrialization and the energy efficiency of the economy. In the case of India, with the increasing contribution being made by the manufacturing, mining, transportation and communication sectors to the gross national product, the linkage between energy consumption and the deflated GNP are specific and strong. This paper outlines the methodology by which the relationship has been modelled and a forecast made of the energy demand.     

A Risk Analysis Framework for Cyber Security and Critical Infrastructure Protection of the U.S. Electric Power Grid

The purpose of this article is to introduce a risk analysis framework to enhance the cyber security of and to protect the critical infrastructure of the electric power grid of the United States. Building on the fundamental questions of risk assessment and management, this framework aims to advance the current risk analysis discussions pertaining to the electric power grid. Most of the previous risk-related studies on the electric power grid focus mainly on the recovery of the network from hurricanes and other natural disasters. In contrast, a disproportionately small number of studies explicitly investigate the vulnerability of the electric power grid to cyber-attack scenarios, and how they could be prevented or mitigated. Such a limited approach leaves the United States vulnerable to foreign and domestic threats (both state-sponsored and “lone wolf”) to infiltrate a network that lacks a comprehensive security environment or coordinated government response. By conducting a review of the literature and presenting a risk-based framework, this article underscores the need for a coordinated U.S. cyber security effort toward formulating strategies and responses conducive to protecting the nation against attacks on the electric power grid.     

Prestorm Estimation of Hurricane Damage to Electric Power Distribution Systems

Hurricanes frequently cause damage to electric power systems in the United States, leading to widespread and prolonged loss of electric service. Restoring service quickly requires the use of repair crews and materials that must be requested, at considerable cost, prior to the storm. U.S. utilities have struggled to strike a good balance between over‐ and underpreparation largely because of a lack of methods for rigorously estimating the impacts of an approaching hurricane on their systems. Previous work developed methods for estimating the risk of power outages and customer loss of power, with an outage defined as nontransitory activation of a protective device. In this article, we move beyond these previous approaches to directly estimate damage to the electric power system. Our approach is based on damage data from past storms together with regression and data mining techniques to estimate the number of utility poles that will need to be replaced. Because restoration times and resource needs are more closely tied to the number of poles and transformers that need to be replaced than to the number of outages, this pole‐based assessment provides a much stronger basis for prestorm planning by utilities. Our results show that damage to poles during hurricanes can be assessed accurately, provided that adequate past damage data are available. However, the availability of data can, and currently often is, the limiting factor in developing these types of models in practice. Opportunities for further enhancing the damage data recorded during hurricanes are also discussed.     

基于用户电器分类的智能电网实时定价研究

目前，电力运行环境日趋复杂，电力体制改革也在不断进行。针对电力行业逐渐向信息化转变、能源利用率较低以及用户与电力公司交互性不高的现状，提出了一种电器分类实时定价模型。该模型根据不同类型用户的用电器进行分类，电力公司根据不同类型电器的用电情况实时制定出不同种类电器的用电价格，以便引导用户在不同时段根据不同类型电器的电价来使用电器，控制居民的用电行为。智能电表的使用，可使用户了解到不同电器的实时电价，并以此调整使用电器，电力公司也随时得到用户的用电量来调整电价和供电量，达到削峰填谷的作用。此模型既有时效性也能使供需双方用电效用最大化。最后通过数值实验对比分析，结果验证了所提出的模型的有效性。     

An LP model for assessing congeneration strategies

A linear programming model is described which is designed to assist in the assessment of optimum operational strategies for industrial plants with cogeneration facilities. A concise format is provided for linking together basic elements such as boilers, valves, turbines and processes with steam and electricity demands with steam, fuel and electricity balance equations. The model should prove particularly useful for assessment when electricity tariffs have time-of-use energy or demand charges or when tariffs have conditions which require consideration of strategies over an extended period. The model has been applied to a paper mill which utilises pass-out turbines for cogeneration of electricity and process steam. Results indicate that savings in fuel costs of the order of 400,000 dollars per year could be obtained by implementing optimal strategies for operating the present turbines. Savings of the order of one million dollars per year could be obtained by converting the turbines to give high pressure pass-out steam and then operating optimally.