As the large change of the grid load, many large capacity units of our country had to change the load in order to meet the gird need. When a thermal power plant receives a given load instruction from the grid, it is n...As the large change of the grid load, many large capacity units of our country had to change the load in order to meet the gird need. When a thermal power plant receives a given load instruction from the grid, it is necessary to set an optimal steam pressure to maintain the high efficiency of the plant. In the past optimization methods, during the process of calculation, the output of the turbine often changed, it was hard to maintain the output constant. Therefore, in combination with the theory of variable condition of turbine, calculation of governing stage and the matrix equation of thermal power system, an optimization method were put forward and an optimal solution was got in a given load.展开更多
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 foreca...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.展开更多
Optimization for the multi-chiller system is an indispensable approach for the operation of highly efficient chiller plants.The optima obtained by model-based optimization algorithms are dependent on precise and solva...Optimization for the multi-chiller system is an indispensable approach for the operation of highly efficient chiller plants.The optima obtained by model-based optimization algorithms are dependent on precise and solvable objective functions.The classical neural networks cannot provide convex input-output mappings despite capturing impressive nonlinear fitting capabilities,resulting in a reduction in the robustness of model-based optimization.In this paper,we leverage the input convex neural networks(ICNN)to identify the chiller model to construct a convex mapping between control variables and the objective function,which enables the NN-based OCL as a convex optimization problem and apply it to multi-chiller optimization for optimal chiller loading(OCL).Approximation performances are evaluated through a four-model comparison based on an experimental data set,and the statistical results show that,on the premise of retaining prior convexities,the proposed model depicts excellent approximation power for the data set,especially the unseen data.Finally,the ICNN model is applied to a typical OCL problem for a multi-chiller system and combined with three types of optimization strategies.Compared with conventional and meta-heuristic methods,the numerical results suggest that the gradient-based BFGS algorithm provides better energy-saving ratios facing consecutive cooling load inputs and an impressive convergence speed.展开更多
This paper proposes to use the power system simulation software CYME to plan, model and simulate for an actual distribution network for improving the reliability and efficiency, enhancing the efficiency and capacity, ...This paper proposes to use the power system simulation software CYME to plan, model and simulate for an actual distribution network for improving the reliability and efficiency, enhancing the efficiency and capacity, simulating the abnormal condition of distribution network, and presenting operation program of safe, reliable and having simulation record statements. The modeling simulation results show that the software module has lots of advantages including high accuracy, ideal reliability, powerful practicality in simulation and analysis of distribution network, it only need to create once model, the model can sufficiently satisfy multifarious types of simulation analysis required for the distribution network planning.展开更多
With certain controllability of various distribution energy resources (DERs) such as battery energy storage system (BESS), demand response (DR) and distributed generations (DGs), virtual power plant (VPP) can suitably...With certain controllability of various distribution energy resources (DERs) such as battery energy storage system (BESS), demand response (DR) and distributed generations (DGs), virtual power plant (VPP) can suitably regulate the powers access to the distribution network. In this paper, an optimal VPP operating problem is used to optimize the charging/discharging schedule of each BESS and the DR scheme with the objective to maximize the benefit by regulating the supplied powers over daily 24 hours. The proposed solution method is composed of an iterative dynamic programming optimal BESS schedule approach and a particle swarm optimization based (PSO-based) DR scheme approach. The two approaches are executed alternatively until the minimum elec-tricity cost of the whole day is obtained. The validity of the proposed method was confirmed with the obviously decreased supplied powers in the peak-load hours and the largely reduced electricity cost.展开更多
促使风电、光伏等分布式能源和电动汽车保有量快速增长。考虑电动汽车到电网(vehicle to grid,V2G)能量互动对多元化能源发电出力随机性及波动性的平抑作用,以及提升风/光电的消纳水平,采用虚拟电厂(virtual power plant,VPP)技术实现...促使风电、光伏等分布式能源和电动汽车保有量快速增长。考虑电动汽车到电网(vehicle to grid,V2G)能量互动对多元化能源发电出力随机性及波动性的平抑作用,以及提升风/光电的消纳水平,采用虚拟电厂(virtual power plant,VPP)技术实现对二者的统一协调管理,进而结合电动汽车全生命周期碳排放数量和分布式能源运行时碳排放数量,构建电动汽车参与的虚拟电厂整体多目标优化模型,采用粒子群优化算法对该模型进行求解,从而优化系统运行成本及碳排放成本。在结合真实数据配置的算例模型上进行实验分析,实验结果表明,提出的优化模型可以有效调度虚拟电厂各要素,充分发挥电动汽车V2G入网充放电带来的运行和碳排放收益,可以为低碳目标背景下电网系统的安全稳定运行提供技术参考。展开更多
随着可再生能源渗透率不断提高,电力系统运行灵活性不足的问题日益突出。虚拟电厂(virtual power plant,VPP)是一种融合先进通信与控制技术的分布式可控资源管理新模式,将多类型可控资源聚合为整体,对电力系统经济运行、调峰、调频、稳...随着可再生能源渗透率不断提高,电力系统运行灵活性不足的问题日益突出。虚拟电厂(virtual power plant,VPP)是一种融合先进通信与控制技术的分布式可控资源管理新模式,将多类型可控资源聚合为整体,对电力系统经济运行、调峰、调频、稳定控制等多方面进行支撑。从分布式资源聚合管控与运行优化视角,系统综述了VPP内涵、架构、资源聚合、运行优化等方面当前技术水平和研究现状。首先梳理虚拟电厂功能内涵与定位,总结基于端-边-网-云的分层聚合管控框架及各环节需要解决的关键技术问题;随后介绍各类资源物理建模方法及其聚合模型,并从“对外统一、对内协调”角度综述VPP内部资源优化控制及其整体参与电网互动的协同方法,总结了虚拟电厂未来的技术挑战与发展前景。展开更多
大型光伏电站经常面临严重的电压波动问题。传统的集中式控制方案采用中央控制器进行无功优化,以确保系统稳定运行。然而,这种方案存在计算负担过重、容易发生单点故障和网络安全问题的弊端。为了解决这些问题,分布式优化方法被提出并...大型光伏电站经常面临严重的电压波动问题。传统的集中式控制方案采用中央控制器进行无功优化,以确保系统稳定运行。然而,这种方案存在计算负担过重、容易发生单点故障和网络安全问题的弊端。为了解决这些问题,分布式优化方法被提出并应用于大型光伏电站。该方法将电站划分为多个子系统,并使用局部控制器分别解决每个子系统的优化问题。相邻子系统之间的信息交流较少,系统信息更加安全,同时也能处理规模更大的光伏电站。基于交替方向乘子法(alternating direction method of multipliers,ADMM),提出一种适用于大型光伏电站的分布式无功优化方案解决电站电压越限问题,并通过案例验证其有效性。此外,通过分析支路潮流模型约束的线性化处理对潮流求解的影响和罚函数系数对ADMM性能的影响,进一步提升优化参数,优化大型光伏电站的运行结果。展开更多
文摘As the large change of the grid load, many large capacity units of our country had to change the load in order to meet the gird need. When a thermal power plant receives a given load instruction from the grid, it is necessary to set an optimal steam pressure to maintain the high efficiency of the plant. In the past optimization methods, during the process of calculation, the output of the turbine often changed, it was hard to maintain the output constant. Therefore, in combination with the theory of variable condition of turbine, calculation of governing stage and the matrix equation of thermal power system, an optimization method were put forward and an optimal solution was got in a given load.
文摘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.
基金This work was supported by the Dalian Key Field Innovation Team Project(2020RT04)Airport Terminal Wisdom Environment Security and Energy Saving Laboratory of Guangdong Airport Baiyun Information Technology Co.,Ltd.in China.
文摘Optimization for the multi-chiller system is an indispensable approach for the operation of highly efficient chiller plants.The optima obtained by model-based optimization algorithms are dependent on precise and solvable objective functions.The classical neural networks cannot provide convex input-output mappings despite capturing impressive nonlinear fitting capabilities,resulting in a reduction in the robustness of model-based optimization.In this paper,we leverage the input convex neural networks(ICNN)to identify the chiller model to construct a convex mapping between control variables and the objective function,which enables the NN-based OCL as a convex optimization problem and apply it to multi-chiller optimization for optimal chiller loading(OCL).Approximation performances are evaluated through a four-model comparison based on an experimental data set,and the statistical results show that,on the premise of retaining prior convexities,the proposed model depicts excellent approximation power for the data set,especially the unseen data.Finally,the ICNN model is applied to a typical OCL problem for a multi-chiller system and combined with three types of optimization strategies.Compared with conventional and meta-heuristic methods,the numerical results suggest that the gradient-based BFGS algorithm provides better energy-saving ratios facing consecutive cooling load inputs and an impressive convergence speed.
文摘This paper proposes to use the power system simulation software CYME to plan, model and simulate for an actual distribution network for improving the reliability and efficiency, enhancing the efficiency and capacity, simulating the abnormal condition of distribution network, and presenting operation program of safe, reliable and having simulation record statements. The modeling simulation results show that the software module has lots of advantages including high accuracy, ideal reliability, powerful practicality in simulation and analysis of distribution network, it only need to create once model, the model can sufficiently satisfy multifarious types of simulation analysis required for the distribution network planning.
文摘With certain controllability of various distribution energy resources (DERs) such as battery energy storage system (BESS), demand response (DR) and distributed generations (DGs), virtual power plant (VPP) can suitably regulate the powers access to the distribution network. In this paper, an optimal VPP operating problem is used to optimize the charging/discharging schedule of each BESS and the DR scheme with the objective to maximize the benefit by regulating the supplied powers over daily 24 hours. The proposed solution method is composed of an iterative dynamic programming optimal BESS schedule approach and a particle swarm optimization based (PSO-based) DR scheme approach. The two approaches are executed alternatively until the minimum elec-tricity cost of the whole day is obtained. The validity of the proposed method was confirmed with the obviously decreased supplied powers in the peak-load hours and the largely reduced electricity cost.
文摘促使风电、光伏等分布式能源和电动汽车保有量快速增长。考虑电动汽车到电网(vehicle to grid,V2G)能量互动对多元化能源发电出力随机性及波动性的平抑作用,以及提升风/光电的消纳水平,采用虚拟电厂(virtual power plant,VPP)技术实现对二者的统一协调管理,进而结合电动汽车全生命周期碳排放数量和分布式能源运行时碳排放数量,构建电动汽车参与的虚拟电厂整体多目标优化模型,采用粒子群优化算法对该模型进行求解,从而优化系统运行成本及碳排放成本。在结合真实数据配置的算例模型上进行实验分析,实验结果表明,提出的优化模型可以有效调度虚拟电厂各要素,充分发挥电动汽车V2G入网充放电带来的运行和碳排放收益,可以为低碳目标背景下电网系统的安全稳定运行提供技术参考。
文摘随着可再生能源渗透率不断提高,电力系统运行灵活性不足的问题日益突出。虚拟电厂(virtual power plant,VPP)是一种融合先进通信与控制技术的分布式可控资源管理新模式,将多类型可控资源聚合为整体,对电力系统经济运行、调峰、调频、稳定控制等多方面进行支撑。从分布式资源聚合管控与运行优化视角,系统综述了VPP内涵、架构、资源聚合、运行优化等方面当前技术水平和研究现状。首先梳理虚拟电厂功能内涵与定位,总结基于端-边-网-云的分层聚合管控框架及各环节需要解决的关键技术问题;随后介绍各类资源物理建模方法及其聚合模型,并从“对外统一、对内协调”角度综述VPP内部资源优化控制及其整体参与电网互动的协同方法,总结了虚拟电厂未来的技术挑战与发展前景。
文摘大型光伏电站经常面临严重的电压波动问题。传统的集中式控制方案采用中央控制器进行无功优化,以确保系统稳定运行。然而,这种方案存在计算负担过重、容易发生单点故障和网络安全问题的弊端。为了解决这些问题,分布式优化方法被提出并应用于大型光伏电站。该方法将电站划分为多个子系统,并使用局部控制器分别解决每个子系统的优化问题。相邻子系统之间的信息交流较少,系统信息更加安全,同时也能处理规模更大的光伏电站。基于交替方向乘子法(alternating direction method of multipliers,ADMM),提出一种适用于大型光伏电站的分布式无功优化方案解决电站电压越限问题,并通过案例验证其有效性。此外,通过分析支路潮流模型约束的线性化处理对潮流求解的影响和罚函数系数对ADMM性能的影响,进一步提升优化参数,优化大型光伏电站的运行结果。