Synergetic Dispatch of Power System with Integration of Large-Scale Renewable Energy

This paper comes up with a concept of synergetic advanced dispatch in order to deal with the ever-increasing uncertainty in power grid: Decision is made with respecting to AGC units and active load on the basis of synergetic unit combination such that active load’s advantages in regulation speed is put to full use in achieving efficient cooperation with renewable energy power. Meanwhile, factoring in allowable frequency variation range during decision-making may help to reduce AGC units’ regulation load and improve power grid's capacity of accommodating renewable energy power. Calculation example analysis suggested that the model and technique presented in this paper is capable of efficient coordination between active loads and renewable energy power, delivering friendly transition with day-ahead dispatch and AVC control.

Operating Analysis and Data Mining System for Power Grid Dispatching

The dispatching center of power-grid companies is also the data center of the power grid where gathers great amount of operating information. The valuable information contained in these data means a lot for power grid operating management, but at present there is no special method for the management of operating data resource. This paper introduces the operating analysis and data mining system for power grid dispatching. The technique of data warehousing online analytical processing has been used to manage and analysis the great capacity of data. This analysis system is based on the real-time data of the power grid to dig out the potential rule of the power grid operating. This system also provides a research platform for the dispatchers, help to improve the JIT (Just in Time) management of power system.

Optimal Dispatch in Power Systems with Intermittent Power Sources

With the increasing integration of intermittent power sources (IPSs) into the power system, the uncertainty of IPSs requires solution and current dispatch system needs improvement. This paper aims to generate the optimal dispatch plan for day-ahead scheduling and real-time dispatch using the proposed model of characteristic optimal power flow (COPF). The integral time period represented by the median load point and the heavy and light load point with simplicity and accuracy. Simulation case studies on a 30-bus system are presented, which shows that COPF is an effective model to generate the optimal dispatch plan for power systems with high penetration of IPSs.

A Multi-Agent Particle Swarm Optimization for Power System Economic Load Dispatch

A new versatile optimization, the particle swarm optimization based on multi-agent system (MAPSO) is presented. The economic load dispatch (ELD) problem of power system can be solved by the algorithm. By competing and cooperating with the randomly selected neighbors, and adjusting its global searching ability and local exploring ability, this algorithm achieves the goal of high convergence precision and speed. To verify the effectiveness of the proposed algorithm, this algorithm is tested by three different ELD cases, including 3, 13 and 40 units IEEE cases, and the experiment results are compared with those tested by other intelligent algorithms in the same cases. The compared results show that feasible solutions can be reached effectively, local optima can be avoided and faster solution can be applied with the proposed algorithm, the algorithm for ELD problem is versatile and efficient.

A DISPATCHER TRAINING SIMULATOR SYSTEM INTEGRATED WITH THE EXIST SCADA/EMS

To utilize exist SCADA(Supervisory Control and Data Acqui si tion)/EMS (Energy Management System) fully and economize capital, Henan Electric Power Dispatching and Communication Center in China established a set of Henan Dispatcher Training Simulator (HNDTS) base on its exist SCADA/EMS. In order to i ntegrated with exist SCADA/EMS, the integration method and technique are propose d. Graph data integration discussed with emphasis. After integration implemented , HNDTS can share all data with SCADA/EMS and dispatchers can be trained in same environment as real work situation, in the same time it can avoid amout of work of maintenance engineers. Both advantages and disadvantages of integration are analyzed. In the end of paper, the requirement for future DTS is put forward bas e on the experience of author.

Operation Indices for Smart Power Dispatch Center Design

With the development of power systems, power grid within a control area becomes much more complicated due to increasing number of nodes and renewable energy interconnections. The role of power system control center is more critical in maintaining system reliable and security operations. Latest developed information and communication technologies provide a platform to enhance the functions and performance of power system control center. Smart power dispatch concept will be the trend of future control center development. In this paper, we start from the human factors of control center design and propose operation indices to reduce the information presented to the system operator. The operation indices will be the important criteria in situation awareness of a power grid. Past, present, future and capability states of a power grid are also proposed to provide better visions to the operator of system conditions. The basic ideas of operation indices and operation states are discussed in the paper. In the end, the design factors for a power dispatch cockpit are discussed.

Present State and Development Planning ofEast China Power System

This paper presents the existing state anddevelopment planning of East China PowerSystem, which refers to load, power source,power network, system protection, dispatchautomation and system communication.

新能源电力系统不确定优化调度方法研究现状及展望

风电场和光伏电站出力的不确定性给电力系统优化调度带来很大技术挑战。文中主要介绍了考虑新能源不确定性的电力系统优化调度方法的研究现状及后续研究方向展望。首先,重点论述了各种不确定优化调度(UOD)方法,包括随机优化方法、鲁棒优化方法、随机鲁棒优化结合方法和基于人工智能技术的方法。其中,随机优化方法包括场景法、机会约束规划法和近似动态规划法;鲁棒优化方法包括传统鲁棒优化法和分布鲁棒优化法;随机鲁棒优化结合方法包括采样鲁棒优化法和分布鲁棒机会约束规划法。然后,介绍了每一种方法的优化模型形式、模型的转化和求解原理及其优缺点。最后,对UOD的后续重点研究方向进行展望,包括兼顾多个目标的UOD问题及多目标不确定优化方法、输配系统UOD问题及分布式不确定优化方法、考虑稳定性约束的UOD问题及含常微分方程约束的不确定优化方法、考虑管道传输动态的综合能源系统UOD问题及含偏微分方程约束的不确定优化方法。

Rolling Generation Dispatch Based on Ultra-short-term Wind Power Forecast

The power systems economic and safety operation considering large-scale wind power penetration are now facing great challenges, which are based on reliable power supply and predictable load demands in the past. A rolling generation dispatch model based on ultra-short-term wind power forecast was proposed. In generation dispatch process, the model rolling correct not only the conventional units power output but also the power from wind farm, simultaneously. Second order Markov chain model was utilized to modify wind power prediction error state (WPPES) and update forecast results of wind power over the remaining dispatch periods. The prime-dual affine scaling interior point method was used to solve the proposed model that taken into account the constraints of multi-periods power balance, unit output adjustment, up spinning reserve and down spinning reserve.

含整体煤气化燃料电池-碳捕集电厂的风火储系统分布鲁棒调度方法

整体煤气化燃料电池(integrated gasification fuel cell,IGFC)是与碳捕集技术高度适配的清洁、高效、稳定的绿色煤电技术,有望克服传统碳捕集技术在低浓度CO_(2)环境下产生的高成本、高能耗问题。该文构建含IGFC碳捕集电厂的风火储发电系统。研究IGFC碳捕集电厂的运行机理,对IGFC内部各环节建立数学模型,提出工况匹配时燃烧利用率和阴极空气利用率需要满足的运行条件,并针对该型碳捕集电厂的电碳特性进行分析。为计及风电出力的不确定性,构建风火储系统的两阶段分布鲁棒经济调度模型,引入k阶适应性理论,提出基于正交支撑子集策略的求解方法来获得鲁棒对等式。最后,在改进IEEE-30节点系统中进行算例分析,结果表明,该型碳捕集电厂可利用阳极碳富集的优势,实现系统低碳经济调度的目标,并验证所提优化方法能为可行解提供可解释性。

新型电力系统中的规划运营与电力市场:研究进展与科研实践

“碳达峰、碳中和”战略目标下,能源结构清洁化—可再生能源并网比例不断提高、能源要素多元化—发输配用各环节海量灵活性资源接入两大趋势带来的挑战,对电力规划、调度运营、电力市场产生了重大影响。规划中如何综合考虑海量运行场景与多元化要素,运营中如何高效调度多样灵活性资源,市场如何设计机制激励主体提供灵活性,都是新型电力系统建设亟待解决的问题。该文从电力规划、调度运营、电力市场3个层面出发,对近年来新型电力系统中规划运营与电力市场的相关研究进展进行系统梳理,涵盖基础理论、机制设计、应用研究、系统研发等多类型研究文献。进一步从规划、调度、市场3个方面展望未来研究趋势,如新型要素接入下的电网韧性、电碳耦合调度理论与高效求解技术、辅助服务与容量市场交易品类、考虑储能等新型主体的市场交易机制等,以期为我国新型电力系统的建设提供有益参考。

风电和光伏发电功率联合预测与预调度框架

随着多区域互联电力系统的发展,风电、光伏等新能源发电大规模并网,风电-光伏功率的联合预测和协调调度是必然趋势和迫切需求。为此,从风电-光伏发电的时空相关性分析出发,对风电-光伏功率时空耦合、风电光伏联合预测建模、风电光伏联合预测模型参数优化、考虑风电-光伏联合预测的电力系统预调度等方面进行了分析讨论。首先,研究揭示风电-光伏功率在时间-空间上的交互影响机理,提出面向多时间尺度的风电-光伏功率时间互补性分析方法,建立风电-光伏发电空间相关性量化模型,构建基于多阶图卷积神经网络风电-光伏发电时空耦合模型;基于此,研究提出了融合异构图神经网络的风电-光伏联合预测方法,建立了风电-光伏联合预测模型参数优化模型,构建了新能源有功功率预测误差矢量评价体系,为风电-光伏联合发电系统的协调调度和控制提供决策支撑;在风电-光伏联合发电预测的基础上,采用风电、光伏发电时间互补、空间互济的思路探讨了风电-光伏联合的电力系统预调度策略和方法,对不同时间尺度风电-光伏的协调调度策略进行了剖析,建立了电网-区域-集群-场站空间递阶的风电-光伏联合发电系统分层调度框架。最后,展望了未来风电-光伏联合预测与预调度方面应研究的方向。

储液式CCS耦合P2G的综合能源系统低碳经济调度

为应对电转气P2G(power-to-gas)和碳捕集系统CCS(carbon capture system)在可再生能源出力不足时耦合失效的问题,考虑对常规CCS引入CO_(2)储液罐以加强P2G和CCS的耦合。首先,构建储液式CCS和P2G的耦合模型,利用储液罐将CCS捕集的CO_(2)时移至可再生能源富足时段,供P2G再利用;其次,构建储液式CCS与P2G耦合的电热气综合能源系统日前优化调度模型;最后,以北方某工业园区为例进行仿真。结果证明所提模型可以充分利用CCS捕集的CO_(2),从而获得更好的经济和环境效益。

基于火电灵活性改造的可再生能源消纳系统成本优化

随着风电等可再生能源的大规模发展,带来了消纳难等新挑战,通过火电灵活性改造可以增强电力系统灵活调节能力、提升可再生能源消纳空间,同时需要考虑火电灵活性改造的经济性和对可再生能源消纳的影响。因此,综合考虑火电机组常规运行成本及灵活性改造后增加的各项成本,结合碳排放成本和弃风成本,建立以总成本最小为目标的火电灵活性改造前后优化调度模型,采用对比差值法计算基于火电灵活性改造的可再生能源消纳系统成本。通过算例,将所建模型应用于对比改造前后、不同碳排放强度、是否考虑弃风等不同方案下的机组运行状况及消纳系统成本大小,并拟合得到可再生能源渗透率和消纳系统成本的关系曲线,验证了模型的有效性。

考虑可再生能源配额的风水火多能源电力系统年度调度模型

通过分析配额制的实施对购电策略的影响,建立考虑可再生能源配额的风水火多能源电力系统的年度调度模型。为减小计算负担,将月度的负荷与风电用数个典型场景及其占比来表示。提出能够自动选择最佳聚类数的改进k-means算法,并应用于典型场景生成过程中。将同一天的负荷与风电的历史数据曲线拼接为一条功率曲线,并基于改进k-means算法进行聚类,得到考虑负荷与风电时序相关性的典型场景。仿真结果表明:(1)所提典型场景生成方法对年度电量刻画的精度平均提高了12.7%,由其所生成典型场景的平均符合率提高了20.25%,所提方法具有更好的年度电量刻画效果和更高的平均场景符合率;(2)当绿色证书的价格高于风电与火电价格差值时,实施配额制后能够提高风电的消纳量,这对绿色证书价格的确定具有重要参考价值。

计及深度调峰的风-光-水-火-抽蓄多能源联网系统优化调度研究

多种能源联网运行逐步成为未来电力系统发展的方向,多能源联网系统的优化调度是应对规模化新能源并网消纳的重要手段。文中建立了计及火电机组深度调峰成本的风-光-水-火-抽蓄联网系统成本模型和考虑调峰主动性的风-光-水-火-抽蓄联网系统日前优化调度模型。针对多能源耦合系统结构复杂的情况,提出了分层优化调度的模型求解策略。上层模型以净负荷波动最小为优化目标,得到等效负荷曲线;下层模型根据上层模型的调度结果,以调峰运行的经济性最优和新能源弃电率最低为目标函数,计及调峰主动性,求解考虑火电机组深度调峰煤耗特性的含新能源系统的经济调度问题。仿真算例表明所建模型实现了多能源联网系统的互补运行,提升了火电机组的深度调峰能力,降低新能源弃电率和系统运行成本。

Q学习差分进化算法求解热电动态经济排放调度

热电联产动态经济排放调度同时考虑了燃料成本花费和污染气体排放两个目标值,且下一时间段的热电产量受当前时间段热电产量的影响,这是近年来电力系统运行中的一个重要问题。文中提出一种基于Q学习强化多目标差分进化(Q Learning Multi-Objective Differential Evolution,QLMODE)算法,以此求解热电联产动态经济排放调度(Combined Heat and Power Dynamic Economic Emission Dispatch,CHPDEED)问题。在QLMODE中,采用Q学习技术调整算法的比例因子参数,即在迭代过程中利用子代解和父代解之间的支配关系确定动作奖励和惩罚,并通过Q学习调整参数值,以获得最适合环境模型的算法参数。文中将所提QLMODE用于求解11机组和33机组的热电联产动态经济排放调度问题。仿真结果表明,与4种成熟的多目标优化算法相比,QLMODE算法燃料成本最小,污染气体排放最少,收敛性和多样性指标优于其他4种算法,且QLMODE在两组问题上都获得了更好的Pareto最优前沿。

面向需求响应市场的柔性负荷调度方法研究

为保障新能源的充分消纳和电力系统的安全性及可靠性,需要更多的灵活性资源参与调度,以市场化手段制定负荷聚合商等新型主体的调度运行机制,充分发挥其调节能力,对新型电力系统的建设和发展具有重要意义。从参与主体、准入条件、响应规则和补偿规则4方面分析了目前柔性负荷参与需求响应现状,根据负荷控制场景下的调频及调峰需求,构建柔性负荷优化调度模型。按照目前大部分省市所应用单边报量报价的模式,以“价格优先、容量优先”竞价原则,决定补贴价格及各负荷主体响应量。利用包括独立负荷及负荷聚合商在内的5000个柔性负荷规模系统测试调度优化速度,测试表明模型满足需求响应市场下快速高效调整负荷的需求。

居民负荷参与电力系统调控关键技术综述与展望

“双碳”目标下,新能源发电占比的不断升高和用电需求的持续增长,严重影响了电力系统供需平衡。居民负荷以体量大、响应快速和控制灵活的特点,逐渐成为发挥电力系统灵活调控能力的重要资源之一,是近几年研究关注的热点。文章结合国内外最新研究成果,从居民负荷的调控机制、可调节特性、调控策略及应用场景4个方面对居民负荷参与电力系统调控的关键技术进行综述,重点比较了用于生成最优调控策略的多种算法以及居民负荷参与调控的多样化场景。最后,针对现阶段实施调控过程中面临的实际挑战,提出了信息-物理-社会系统视角下的居民负荷调控市场机制建设、调节能力精准快速感知,以及弱通信环境下调控策略优化与执行等重点问题,并对未来研究方向进行了展望。