Theory Study and Application of the BP-ANN Method for Power Grid Short-Term Load Forecasting

Aiming at the low accuracy problem of power system short-term load forecasting by traditional methods, a back-propagation artificial neural network （BP-ANN） based method for short-term load forecasting is presented in this paper. The forecast points are related to prophase adjacent data as well as the periodical long-term historical load data. Then the short-term load forecasting model of Shanxi Power Grid （China） based on BP-ANN method and correlation analysis is established. The simulation model matches well with practical power system load, indicating the BP-ANN method is simple and with higher precision and practicality.

Load distribution model and voltage static profile of Smart Grid

Voltage profiles of feeders with the connection of distributed generations(DGs) were investigated.A unified typical load distribution model was established.Based on this model,exact expressions of feeder voltage profile with single and double DGs were derived and used to analyze the impact of DG's location and capacity on the voltage profile quantitatively.Then,a general formula of the voltage profile was derived.The limitation of single DG and necessity of multiple DGs for voltage regulation were also discussed.Through the simulation,voltage profiles of feeders with single and double DGs were compared.The voltage excursion rate is 7.40% for only one DG,while 2.48% and 2.36% for double DGs.It is shown that the feeder voltage can be retained in a more appropriate range with multiple DGs than with only one DG.Distributing the total capacity of DGs is better than concentrating it at one point.

Fuzzy Logic–Based Scheme for Load Balancing in Grid Services

Load balancing is essential for efficient utilization of resources and enhancing the responsiveness of a computational grid, especially that hosts of services most frequently used, i.e. food, health and nutrition. Various techniques have been developed and applied;each has its own limitations due to the dynamic nature of the grid. Efficient load balancing can be achieved by an effective measure of the node’s/cluster’s utilization. In this paper, as a part of an NSTIP project # 10-INF1381-04 and in order to assess of FAQIH framework ability to support the load balance in a computational grid that hosts of food, health and nutrition inquire services. We detail the design and implementation of a proposed fuzzy-logic-based scheme for dynamic load balancing in grid computing services. The proposed scheme works by using a fuzzy logic inference system which uses some metrics to capture the variability of loads and specifies the state of each node per a cluster. Then, based on the overall nodes’ states, the state of the corresponding cluster will be defined in order to assign the newly arrived inquires such that load balancing among different clusters and nodes is accomplished. Many experiments are conducted to investigate the effectiveness of the proposed fuzzy-logic-based scheme to support the load balance where the results show that the proposed scheme achieves really satisfactory and consistently load balance than of other randomize approaches in grid computing services.

TCP/IP Based Intelligent Load Management System in Micro-Grids Network Using MATLAB/Simulink

Computerized power management system with fast and optimal communication network overcomes all major dicrepencies of undue or inadequate load relief that were present in old conventional systems. This paper presents the basic perception and methodology of modern and true intelligent load management scheme in micro grids topology by employing TCP/IP protocol for fast and intelligent switching. The network understudy performs load management and power distribution intelligently in a unified network. Generated power is efficiently distributed among local loads through fast communication system of server in the form of source and clients in the form of loads through TCP/IP. The efficient use of information between server and clients enables to astutely control the load management in a power system of micro grids system. The processing time of above stated system comes out to be 10ms faster than others which ensure very less delay as compared to conventional methods. The Micro Grids system operating through TCP/IP control has been implemented in MATLAB/Simulink and results have been verified.

Grid Power Optimization Based on Adapting Load Forecasting and Weather Forecasting for System Which Involves Wind Power Systems

This paper describes the performance, generated power flow distribution and redistribution for each power plant on the grid based on adapting load and weather forecasting data. Both load forecasting and weather forecasting are used for collecting predicting data which are required for optimizing the performance of the grid. The stability of each power systems on the grid highly affected by load varying, and with the presence of the wind power systems on the grid, the grid will be more exposed to lowering its performance and increase the instability to other power systems on the gird. This is because of the intermittence behavior of the generated power from wind turbines as they depend on the wind speed which is varying all the time. However, with a good prediction of the wind speed, a close to the actual power of the wind can be determined. Furthermore, with knowing the load characteristics in advance, the new load curve can be determined after being subtracted from the wind power. Thus, with having the knowledge of the new load curve, and data that collected from SACADA system of the status of all power plants, the power optimization, load distribution and redistribution of the power flows between power plants can be successfully achieved. That is, the improvement of performance, more reliable, and more stable power grid.

Intelligent Load Shedding Using TCP/IP for Smart Grids

Computerized power management system with fast and optimal communication network overcomes all major discrepancies of undue or inadequate load relief that were present in old conventional systems. This paper presents the basic perception and methodology of modern and true intelligent load shedding scheme in micro grids topology by employing TCP/IP protocol for fast and intelligent switching. The network understudy performs load management and power distribution intelligently in a unified network. Generated power is efficiently distributed among local loads through fast communication system of server in the form of source and clients in the form of loads through TCP/IP. The efficient use of information between server and clients enables to astutely control the load shedding in a power system of micro grids system. The processing time of above stated system comes out to be 10 ms faster than others which ensure very less delay as compared to conventional methods. The Micro Grids system operating through TCP/IP control has been implemented in MATLAB/SIMULINK and results have been verified.

园区受端新型电力系统电力电量再平衡方法

我国工业园区电能消耗占据了较高的比例,针对依托新型电力系统促进工业园区绿色低碳发展的需要,提出了一种面向工业园区受端新型电力系统的电力电量再平衡方法。首先,开展电力和电量需求预测并进行电力电量初平衡;然后,基于受端源网荷储协同作用并充分考虑园区节能、电能替代、各类分布式电源、储能和需求响应能力的作用进行电力电量再平衡,由此确定园区年度外调电和区内自产电的比例,进一步建立包含低碳效应和电力系统规模变化在内的量化指标评价体系,对电力电量再平衡带来的变配电容量缩减规模和降碳效用进行评价。以我国南方某工业园区新型电力系统的电力电量再平衡为例对以上方法进行了验证,结果表明:该园区2030年变配电规划容量可缩减10.1%,用电综合碳排放因子由0.60 kg/(kW·h)降至0.54 kg/(kW·h);2060年变配电规划容量可缩减9.57%,电能替代实现减碳5.85万t/a,可为受端新型电力系统的电力电量平衡提供有力的理论支撑。

附加阻尼控制下风电机组机网耦合载荷建模及分析

针对附加阻尼控制下风电机组机械载荷问题,开展风电机组机网耦合载荷建模及载荷特性分析研究。采用FAST与Matlab/Simulink软件联合方法,建立综合考虑机组机械特性和电气特性的并网风电机组机网耦合载荷模型。采用所建模型开展附加阻尼控制对机组机械载荷影响的仿真分析,并复现附加阻尼控制下风电机组机械系统与电力系统的机网共振现象。结果表明,所建模型能够表征附加阻尼控制下风电机组机械系统与电力系统的耦合互作用,系统低频振荡会导致机组关键结构出现明显振动载荷,且系统振荡频率与机组机械结构固有振动频率接近时两者共振会急剧加大机组振动载荷。

含电动汽车和光伏的配电网演化动态博弈调度策略

针对大规模电动汽车的无序充电行为可能导致电网出现的三相不平衡问题,基于演化动态博弈模型,提出一种考虑三相负荷平衡和光伏消纳的电动汽车充电调度策略。首先,基于电动汽车接入时段的主观性以及光伏出力和负荷的不确定性,引入游牧集群和定居集群之间的演化动态博弈方程;然后,考虑用户侧和电网侧双方利益关系,设计以最小化电动汽车充电费用、三相负荷不平衡度和无功需求为目标的调度优化模型;最后,通过对某商业区配电网算例进行仿真求解,对比分析三相有功曲线、三相无功曲线以及荷电状态曲线的变化趋势。算例结果表明,该调度策略可有效降低三相不平衡度,满足无功补偿的需求以及改善用户充电成本。

基于分层事件触发的混合微电网集中控制策略

针对混合微电网集中控制对中央控制器依赖严重、通信需求量大、扰动调节能力差的问题,提出一种微电网中央控制器(microgrid central control,MGCC)参与的分层事件触发控制策略,有效降低分布式集群的冗余通信并减少中央控制器计算负担,改进策略可靠性。该策略将控制系统分为2层,其中,设备层为本地控制层,采用分布式协同控制,所设计的本地控制器可就地控制更新输出状态,实现混合微电网的分散自治运行;另外,在控制层建立微电网控制层,引入事件触发策略,协调MGCC获取混合微电网的全局信息,从而向本地控制器发出预定义的调控指令,实现“源网荷储”灵活调度,尤其是应对突发事件而引发的电网振荡。最后,采用Matlab搭建混合微电网模型并进行仿真,利用Stateflow模块实现了事件触发算法,验证控制策略在满足并网/孤岛模式可靠性、稳定性的前提下,系统通信量可降低56.4%。

基于预期动态方程的含高比例可再生能源孤岛运行微电网负荷频率控制

针对高比例可再生能源并入微电网带来的负荷频率控制问题,提出基于预期动态方程的比例-积分-微分(PID)控制策略.在分析微电网负荷频率控制模型和控制难点的基础上,设计基于预期动态方程的PID控制策略,采用单一变量法分析控制器参数对控制效果的影响,总结了简单、实用的参数整定流程,并在微电网负荷频率控制系统中应用.在不同工况下与多种控制器进行仿真对比,结果表明:所提控制策略能够在保证鲁棒性的前提下取得最佳控制效果,展现出很高的工程应用价值.

台风灾害下考虑多类型故障不确定性的源网荷协同弹性提升模型

针对现有弹性提升模型系统故障不确定性刻画不充分、源网荷弹性提升措施未协同的问题,提出了一种台风灾害下计及多类型故障不确定性的源网荷协同弹性提升模型。首先,构建了多类型故障概率分布不确定集,以刻画台风灾害下最严重、最可能、连锁故障3类典型故障的概率分布不确定性。接着,基于分布鲁棒优化思想,提出了长短期结合、源网荷协同的分布鲁棒弹性提升措施模型:针对台风灾害下最恶劣多类型故障概率分布场景,在灾前通过输电网扩展规划、快/慢机开机组合、输电网结构优化进行预防,灾中通过差异化切负荷和发电机调度进行抵御和响应。结合模型数学结构特征,基于Benders分解和列与约束生成思想,设计原始-对偶并行分解算法完成模型求解。最后,以IEEE-30节点和中国某区域261节点系统为例,研究了源网荷协同措施的弹性提升效果,验证了所提方法的有效性。

Intelligent Load Management Scheme for a Residential Community in Smart Grids Network Using Fair Emergency Demand Response Programs

In the framework of liberalized deregulated electricity market, dynamic competitive environment exists between wholesale and retail dealers for energy supplying and management. Smart Grids topology in form of energy management has forced power supplying agencies to become globally competitive. Demand Response (DR) Programs in context with smart energy network have influenced prosumers and consumers towards it. In this paper Fair Emergency Demand Response Program (FEDRP) is integrated for managing the loads intelligently by using the platform of Smart Grids for Residential Setup. The paper also provides detailed modelling and analysis of respective demands of residential consumers in relation with economic load model for FEDRP. Due to increased customer’s partaking in this program the load on the utility is reduced and managed intelligently during emergency hours by providing fair and attractive incentives to residential clients, thus shifting peak load to off peak hours. The numerical and graphical results are matched for intelligent load management scenario.

考虑源网荷效益的峰谷电价与峰谷时段双层优化模型

用户响应行为测算需求解峰谷时段与峰谷电价之间的双线性项,目前仅考虑负荷曲线的数值大小对峰谷时段进行单独划分,分时电价实行效果受限。提出峰谷时段与峰谷电价的双层优化模型,考虑风电不确定性下的规划成本与发电成本,反映分时电价的实际经济效用;考虑用户响应的不确定性,保证分时电价实行后的源网荷效益在一定范围内变化;峰谷时段划分与峰谷电价设计均以系统成本最低为目标优化得到,充分考虑峰谷时段划分、峰谷电价设计和用户响应行为之间的交互机理。仿真结果表明,与单独划分峰谷时段的模型相比,所提模型能够制定更优、科学性更强的峰谷时段和峰谷电价,进一步降低系统总成本。