不确定性需求响应建模在电力积分激励决策中的应用

构建了计及不确定性的用户响应模型,通过负荷削减能力和响应的不确定性两个特征描述需求响应随经济激励及其他因素变化的规律。以基于电力积分机制的需求响应满足有序用电计划的缺口为背景,将用户负荷形状的改变和外部因素之间的关系用不确定性模型来表征,不仅突出激励水平对于用户负荷削减或转移能力的影响,还兼顾响应行为主观、随机的特点。基于此构造了以电网公司为实施主体的决策模型,结合随机模拟和扩展优先顺序法求解。算例分析验证了建模和求解的有效性,用户响应行为的不确定性建模能为电网公司提供更全面的决策信息,针对性地提高需求响应实施效果。     

Evaluation of nonlinear models for time-based rates demand response programs

Demand Response (DR) programs have been implemented in many competitive electricity markets to prevent price spikes and power systems unreliability. Mathematical modeling of these programs helps regulators to evaluate the impact of price responsive loads on market conditions. In this paper, several nonlinear economic models of price responsive loads are derived based on price elasticity of demand and customer benefit function. The main objectives of the paper include extracting different mathematical models for Time of Use (TOU) programs, and comparing these models to find out which model shows more conservative and which one shows non-conservative results compared with the initial load curve. This could be used by ISOs or DR programs developers as a guideline to use conservative models to have lower error in load profile characteristics estimation, such as variation in peak load or amount of energy consumptions. In order to evaluate the performance of the proposed nonlinear DR models, numerical studies are conducted on the load curve of different markets. Results obtained by using different models are presented and compared considering different scenarios for price, elasticity and potentiality of DR programs implementation. Characteristics of both linear and nonlinear economic models of price responsive loads have been evaluated.     

Optimal siting and sizing of demand response in a transmission constrained system with high wind penetration

This paper describes algorithms that use demand-side management to address large-scale integration of wind power. In particular, demand response (DR) is used to manage wind power intermittency by shifting the time that electrical power system loads occur in response to real-time prices and wind availability. An economic dispatch with transmission, DR capacity and operational constraints is used to model the operation of a transmission constrained system with a high penetration of wind power. This optimization model is used to determine the optimal sizing and distribution of DR given a fixed budget for customer incentives and the installation of enabling technology. We demonstrate the effectiveness of the operational model based on a simple PJM 5-bus system and an IEEE 118-bus system. Simulation results show that transmission constraints have a greater effect on sizing of DR capacity than the location of wind power, which means that buses electrically close to congested lines tend to have higher incentives to deploy DR resources than other buses. The second part of the work examines optimal siting of technology that enables DR based on the frequency of DR based load changes, which are generally a function of the network location.     

Derivation of class load pattern by field test for temperature sensitivity analysis

This paper proposes systematic procedures to derive the load pattern of various customer classes in a utility company. The questionnaires are adopted to find the power consumption of key electrical appliances. The customer load information is obtained through intelligent equipment which records customers' electricity demand on a 15-minute interval basis throughout the year. Five hundred meters are installed on statistically selected samples from the various customer classes. By the proposed sampling theory, the customer load characteristics will be derived with a sufficient confidence level. Statistical analysis is then performed to find the typical load pattern of each customer class based on the power measurements of field tests. The temperature effect on the power consumption of each customer class is then solved by investigating the relationship between customer power consumption and the ambient temperature. The proposed procedure has been adopted by Taipower Company to determine the customer load pattern to provide valuable information for better distribution planning and to design better load management programs to enhance system operating efficiency.     

电力客户负荷模式分析

了解客户的用电模式、制订相应的购电合同,对于增加电力部门的经济效益有着重要的作用。针对获取的客户用电数据,在经过一定的预处理后使用多种聚类分析方法进行分析,通过选取最合适的聚类方法以及聚类数目得到典型负荷代表曲线。通过与经济类型代码分类方法进行比较,所获取的负荷曲线能有效地区分并合理地代表各种经济类型的负荷,表明了通过聚类所获取负荷模式的方法是有效可行的。     

基于高斯混合模型的居民聚合响应潜力多重置信评估

针对居民用电负荷与源端出力多变背景下传统电力系统运行灵活性不足的现实问题,需求响应可有效提高系统运行灵活性与安全经济效益,价值尤为凸显,而响应潜力的精细化评估是其重要基础支撑。文中提出一种在缺少历史响应数据支撑时基于高斯混合模型的聚合响应潜力评估方法。首先,通过家庭及相似日的两次聚类分析选取典型样本数据,强化数据的代表性;然后,引入高斯混合模型精准挖掘家庭用电行为的概率分布,形成单个家庭的响应潜力;最后,自下而上加权汇总,实现多重置信情景下聚合需求响应潜力的评估。实验分析表明该方法能够仅从历史用电数据中挖掘出小时级的居民需求响应潜力信息,充分反映用电负荷分布及响应潜力分布特征,并通过对比分析验证了两次聚类选取典型样本数据的有效性。     

考虑需求响应的负荷控制对供电可靠性影响分析

需求响应一般分为基于电价与激励两种模式,采取需求响应的目的是降低峰时段负荷,减少运行风险。研究的重点是构建包含负荷控制的分时电价负荷模型,分析同时采用负荷控制激励模式与分时电价两种需求响应措施后负荷变化对电网可靠性的影响,从不同角度分析两种模式下配电网运行情况,并提出一种新的通过负荷曲线聚类来计算配电网在动态负荷下的可靠性方法。通过引入改进的k-means聚类算法对不同需求响应模式下的负荷曲线聚类,得到负荷概率模型,结合蒙特卡洛模拟方法来计算不同负荷水平下最终的配电网可靠性指标,分析了在需求响应不同模式下的负荷变化对配电网可靠性影响。算例结果表明,需求响应措施能提高系统可靠性,且包含负荷控制激励的分时电价比单一措施下的可靠性更高。     

需求侧管理参与的孤岛型微电网多目标优化调度

分析了MG中分布式电源的功率特性和需求侧响应的基本理论与相关政策,并建立了DG的数学模型和基于负荷分类的DR模型;综合考虑微源的出力成本、需求侧管理成本和环境治理费用,建立了考虑需求侧管理的多目标微电网优化调度模型,引入不同的孤岛微电网运行评价指标评价DR对微电网经济性、环保性以及可靠性的影响,并选择不同的场景分析验证。采用改进粒子群算法优化外点法对规划问题进行求解,在将约束条件纳入目标函数的同时,尽可能避免求解规划时陷入局部极值的问题。算例分析表明,通过考虑需求侧管理,可以增加可再生能源的消纳,减轻负荷高峰时段的供电压力,缓解孤岛系统供电不足的问题,并有效提高微电网的整体效益。     

考虑需求响应的CCHP系统中分布式电源的选址定容

以往对于冷/热/电联供(combined cooling heating and power,CCHP)系统的研究主要集中在其运行优化上,较少对系统中分布式电源(distributed generation,DG)的选址定容问题进行研究,更少有文献将基于价格与基于激励的需求响应(demand response,DR)综合考虑在系统中。该文利用CCHP系统的多能源互补特性,综合考虑基于价格与基于激励的需求响应,以分布式电源接入节点与接入容量为变量,提出了计及需求响应的分布式电源选址定容模型。首先,建立了CCHP系统热电耦合运行模型。其次,综合考虑负荷削减量、中断持续时间与中断时间因子等因素,提出了可中断负荷的单位电量补偿定价的方法。通过在目标函数中分析需求响应成本,使规划目标更为全面,从而节约投资。另外,综合基于激励与基于价格的需求响应作用,考虑用户对于电价、燃气价格、可中断负荷单位电量补偿定价的响应,定义了改进的价格弹性系数,并利用此系数对负荷预测进行修正。最后,通过基于邻域再搜索的改进粒子群算法(neighborhood re-dispatch particle swarm optimization,NR-PSO)对规划模型进行求解,并通过对某13节点综合园区系统的仿真分析,验证了所提模型及方法的有效性。     

考虑多重评价指标的多时段分时电价优化模型

分时电价策略是当前电力系统需求侧管理的主要措施之一,执行分时电价能够有效降低负荷波动,实现削峰填谷。合理开展峰谷双时段或峰平谷3时段分时电价策略的选择有利于提高电网供电可靠性和用户满意度。提出基于电价弹性矩阵的用户响应模型并定量计算用户综合满意度,根据相应模型分别求解负荷峰值、负荷峰谷差以及用户综合满意度,建立峰谷分时电价与峰平谷分时电价的多重评价指标模型,利用所提指标构造电价优化的目标函数。通过对3类用户进行仿真计算验证所提方法的正确性与有效性。     

A pattern recognition methodology for evaluation of load profiles and typical days of large electricity customers

This paper describes a pattern recognition methodology for the classification of the daily chronological load curves of each large electricity customer, in order to estimate his typical days and his respective representative daily load profiles. It is based on pattern recognition methods, such as k-means, self-organized maps (SOM), fuzzy k-means and hierarchical clustering, which are theoretically described and properly adapted. The parameters of each clustering method are properly selected by an optimization process, which is separately applied for each one of six adequacy measures. The results can be used for the short-term and mid-term load forecasting of each consumer, for the choice of the proper tariffs and the feasibility studies of demand side management programs. This methodology is analytically applied for one medium voltage industrial customer and synoptically for a set of medium voltage customers of the Greek power system. The results of the clustering methods are presented and discussed.     

大规模空调负荷聚合建模及跟踪控制方案研究

需求响应技术可以削峰填谷,提高能源利用效率,提升电力系统稳定性。直接负荷控制通过直接控制用电负荷使得需求侧负荷变成可调用资源,是实施基于激励的需求响应的一种有效方法,实现相对容易。空调用电量大,储热、储冷能力较好,将空调在高峰时段的用电量转移到低谷时段,对用户的影响小。因此,空调能够影响总负荷曲线的峰谷差异,是重要的需求响应资源。基于此,建立了空调的热力学模型,提出了基于蒙特卡洛方法建立大规模空调负荷聚合模型,并研究了实施直接负荷控制的空调负荷跟踪控制方案,讨论了空调负荷参与需求响应的负荷削减潜力。根据负荷调峰的需求计算控制空调温度或开、关状态的参考信号,然后采用自适应爬坡控制方法,跟踪参考信号的实施情况。仿真结果表明,通过跟踪参考信号来实施空调负荷的直接负荷控制可以依据需求有效削减负荷。     

电力负荷参数辨识的实用改进及实测结果

针对电力负荷参数辨识中出现的参数不稳定问题,对参数辨识过程作了改进:一是将负荷参数分为重点参数和次要参数,只对重点参数进行辨识,对次要参数则直接采用其典型值进行计算;二是给出了参数初始搜索范围选取的一般方法;三是对系统容量基值和感应电动机容量基值下的参数作了一些说明,在进行联网计算时,感应电动机自身容量基值下的参数要根据系统容量基值折合;四是提出了模型类别的判别指标。基于以上改进措施,对河南电网和江苏电网的实测数据进行了参数辨识,表明以上改进措施使电力负荷建模达到实用要求。     

计及可中断负荷的电力系统可用输电能力计算

为分析需求响应对系统可用输电能力的影响,提出一种开放电力市场环境下可用输电能力的计算方法。以可中断负荷这一典型的需求响应资源作为研究对象,构建考虑负荷服务实体和独立系统运营商不同利益需求的双层优化模型:上层模型以负荷服务实体的成本最小为目标,确定参与需求响应的用户;下层模型以发电总报价最小为目标确定节点边际电价,同时实现经济调度。将根据需求响应和发电机组报价分配的有功功率作为基态,在此基础上计算区域间可用输电能力。求解双层模型时,运用下层经济调度模型的KKT条件可将双层优化问题转化为均衡约束数学规划问题,根据强对偶理论消除约束中的非线性项,将原模型转化成混合整数线性规划模型。最后,在GAMS环境下调用CPLEX求解化简后的数学模型。通过对PJM-5节点、IEEE 30节点、IEEE118节点和IEEE 300节点系统的仿真计算,验证了所提方法的可行性和有效性,以及在可用输电能力计算中计及需求响应的必要性。     

基于NILE算法量化热水器参与需求响应的灵活性

居民电热水器(EWH)因其功耗与日负荷模式高度相关且占家庭负荷比重高等特点,在需求响应(DR)市场中极具潜力。识别住宅侧EWH集群的负荷模式及量化其参与DR的灵活性有助于电网运营商制定合理的调控策略。首先,对居民EWH不同时间类型下的负荷模式(用电事件的起止时间和用电时长)建立了概率统计模型。然后,提出了一种基于负荷印记和功率块极值的无训练过程的非侵入式负荷提取(NILE)算法,其可自动分离不同额定功率的EWH负荷。最后,建立了电价激励的DR模型以优化EWH的负荷模式,根据其在优化前后使用行为的变化情况量化其灵活性。此外,在真实数据集上验证了所提算法的有效性,并基于分离的负荷数据在不同情况下量化了EWH集群参与DR的灵活性。     

A fuzzy logic based approach to direct load control

Power system demand side management programs are strategies designed to alter the shape of the load curve. In order to successfully implement such a strategy, customer acceptance of the program is vital. It is thus desirable to design a model for direct load control which may accommodate customer preferences. This paper presents a methodology for optimizing both customer satisfaction and electric utility unit commitment savings, based on a fuzzy load model for the direct load control of appliances     

面向需求侧主动响应的工商业用户电力套餐优化设计

电力需求响应是应对电网峰谷差持续拉大、间歇性可再生能源大规模并网、能源结构转变等问题的有效方法。为此,提出了一种新的需求侧主动响应策略——面向工商业用户的电力套餐,并对电力套餐的设计问题进行了优化研究。首先,采用基于特性指标降维的负荷聚类方法辨识工商业用户的负荷特征,为电力套餐的设计进行市场细分;其次,在综合考虑电费支出满意度和用电方式满意度对用户决策的影响的基础上,基于多项Logit模型构建用户对电力套餐的选择行为模型;接着,构建基于成本—效益分析的电力套餐综合评估模型,以衡量电力套餐的经济价值;然后,在此基础上,提出以最大化益本比为优化目标的电力套餐设计的优化模型。算例采用某地区工商业用户的实际数据,结果显示了所提电力套餐的经济价值及其调动需求侧主动参与负荷管理的效果。     

Home energy management incorporating operational priority of appliances

Home energy management (HEM) schemes persuade residential customers to actively participate in price-based demand response (DR) programs. In these price-based HEM methods, a controller schedules the energy consumption of household’s controllable appliances in response to electricity price signals, considering various customer preferences. Although numerous methods have been recently proposed for HEM application, prioritizing the operation of controllable appliances from the customer’s viewpoint in price-based HEM has not been addressed, which is the focus of the present paper. To do this, the value of lost load (VOLL) of each appliance is defined to indicate the operational priority of that appliance from the customer perspective. Considering appliances’ VOLL, electricity tariffs, and operational constraints of appliances, an optimization problem is proposed to minimize customer energy and reliability costs. The output of the proposed HEM would be the optimum scheduling of household electrical demand. Numerical studies illustrate the effectiveness of the proposed HEM method in a smart home, considering different time-varying electricity pricings.     

用户侧互动模式下发用电一体化调度计划

针对大规模风电反调峰特性和空调负荷等因素造成的系统负荷高峰谷差给电网安全、经济运行带来的挑战,在分析商业、工业负荷移峰潜力的基础上,设计了用户侧自愿申报用电意愿和移峰成本的新型用户侧互动模式。基于该互动模式,建立了能够充分反映用户意愿的用户侧互动负荷模型,并将其嵌入传统的安全约束机组组合模型中,提出了发用电一体化调度计划模型。实现了用户侧互动负荷作为可调度资源参与电网运行,减少了高成本机组启停,降低了系统运行成本。新英格兰39节点系统验证了所提出的模式和模型的有效性。     

计及需求侧响应日前-日内两阶段鲁棒备用优化

为增强电力系统应对不确定性因素的能力,提高电网运行效率,提出一种计及需求侧响应日前—日内两阶段鲁棒备用优化模型。一方面,在模型中协同优化价格型与激励型需求侧响应提高电网运行的灵活性;另一方面,综合考虑风电出力不确定性与电力设备N-k强迫停运,增强电力系统应对不确定性因素的鲁棒性。基于鲁棒模型对系统运行备用进行优化,最小化电网在最恶劣运行场景下的调整成本,保证电网的安全可靠运行,并采用列和约束生成算法对两阶段三层优化问题进行求解。修改的6节点系统与IEEE RTS-79测试系统算例验证了所提模型与算法的有效性。结果表明,综合考虑多重不确定性因素进行备用优化,可以提升电网应对极端运行场景的能力;同时,需求侧响应的实施可以大大提高电网运行的灵活性。其中,激励型需求侧响应通过直接控制负荷,对于增强电网运行鲁棒性的作用更加明显;而电价型需求侧响应在要求保障负荷供电的场景下更为适用。