Economic Power Dispatching from Distributed Generations: Review of Optimization Techniques

In the increasingly decentralized energy environment,economical power dispatching from distributed generations(DGs)is crucial to minimizing operating costs,optimizing resource utilization,and guaranteeing a consistent and sustainable supply of electricity.A comprehensive review of optimization techniques for economic power dispatching from distributed generations is imperative to identify the most effective strategies for minimizing operational costs while maintaining grid stability and sustainability.The choice of optimization technique for economic power dispatching from DGs depends on a number of factors,such as the size and complexity of the power system,the availability of computational resources,and the specific requirements of the application.Optimization techniques for economic power dispatching from distributed generations(DGs)can be classified into two main categories:(i)Classical optimization techniques,(ii)Heuristic optimization techniques.In classical optimization techniques,the linear programming(LP)model is one of the most popular optimization methods.Utilizing the LP model,power demand and network constraints are met while minimizing the overall cost of generating electricity from DGs.This approach is efficient in determining the best DGs dispatch and is capable of handling challenging optimization issues in the large-scale system including renewables.The quadratic programming(QP)model,a classical optimization technique,is a further popular optimization method,to consider non-linearity.The QP model can take into account the quadratic cost of energy production,with consideration constraints like network capacity,voltage,and frequency.The metaheuristic optimization techniques are also used for economic power dispatching from DGs,which include genetic algorithms(GA),particle swarm optimization(PSO),and ant colony optimization(ACO).Also,Some researchers are developing hybrid optimization techniques that combine elements of classical and heuristic optimization techniques with the incorporation of droop control,predictive control,and fuzzy-based methods.These methods can deal with large-scale systems with many objectives and non-linear,non-convex optimization issues.The most popular approaches are the LP and QP models,while more difficult problems are handled using metaheuristic optimization techniques.In summary,in order to increase efficiency,reduce costs,and ensure a consistent supply of electricity,optimization techniques are essential tools used in economic power dispatching from DGs.

通信限制下多DG接入配网的新型电流差动保护

差动保护是解决分布式电源(distributed generation, DG)接入下配电网保护难题的有效手段,然而配网现有通信建设水平很大程度上制约了差动保护的构建。首先,融合电流相位与相量差动保护思想,同时将电流相位信息进行变换,实现通信信息降容。应用递推最小二乘法实现短路电流相位参数的快速估计,提出了短路电流相位修正策略,以应对CT饱和与直流分量对保护的干扰。最后,提出适用于含多DG配网的新型电流差动保护构建原则与保护判据。基于PSACD/EMTDC平台搭建仿真模型,验证了所提出的电流相位参数预测方法的精度与新型差动保护的性能。算例结果表明:所提电流相位参数预测方法速度快、精度高,具有良好的抗CT饱和能力;所提新型差动保护原理具有良好的性能。

含高间歇性DG的配电网储能优化配置方法研究

高间歇性的分布式电源(DG)具有较大的随机性,并网发电后会对配电网运行的稳定性产生较大影响。为了保证配电网运行的电能质量和消纳能力,研究含高间歇性DG的配电网储能优化配置方法。首先,估算DG最大准入容量,分析配电网的消纳能力;接着,选取负荷控制目标,消除储能系统中存在的负荷毛刺。然后,基于需求侧响应协调规划配电网储能,以控制储能系统的发电和用电平衡。最后,建立含高间歇性DG的配电网储能优化配置模型,使电压趋近或保持在优化区间内。经试验论证分析,所提方法可以使负荷曲线的波动范围缩小到250~350 kW,对负荷具有更好的控制能力。该方法能够有效地解决电压越线的问题,具有较好的电压调节效果。

考虑DG无功调节和不确定性的配电网新能源消纳容量评估

为充分考虑分布式电源不确定性和控制多样性对配电网运行的影响,提出了一种考虑分布式电源无功调节和不确定性配电网新能源消纳容量的评估方法。首先分析了分布式电源对配电网电压分布的影响、分布式电源无功调节能力以及分布式电源出力的不确定模型;其次,以最大化新能源消纳容量和最小网损为优化目标,以计及分布式电源无功调节和不确定性的有功-无功作为重要约束,建立配电网新能源消纳容量评估模型;然后,以分布式电源和无功补偿装置的出力为优化变量,通过快速非支配排序遗传算法进行求解,实现了新能源消纳容量的准确评估;最后通过应用实例进行验证。结果表明,所提评估方法实现了配电网新能源消纳容量的可靠评估。

Optimal Location and Sizing ofMulti-Resource Distributed Generator Based onMulti-Objective Artificial Bee Colony Algorithm

Distribution generation(DG)technology based on a variety of renewable energy technologies has developed rapidly.A large number of multi-type DG are connected to the distribution network(DN),resulting in a decline in the stability of DN operation.It is urgent to find a method that can effectively connect multi-energy DG to DN.photovoltaic(PV),wind power generation(WPG),fuel cell(FC),and micro gas turbine(MGT)are considered in this paper.A multi-objective optimization model was established based on the life cycle cost(LCC)of DG,voltage quality,voltage fluctuation,system network loss,power deviation of the tie-line,DG pollution emission index,and meteorological index weight of DN.Multi-objective artificial bee colony algorithm(MOABC)was used to determine the optimal location and capacity of the four kinds of DG access DN,and compared with the other three heuristic algorithms.Simulation tests based on IEEE 33 test node and IEEE 69 test node show that in IEEE 33 test node,the total voltage deviation,voltage fluctuation,and system network loss of DN decreased by 49.67%,7.47%and 48.12%,respectively,compared with that without DG configuration.In the IEEE 69 test node,the total voltage deviation,voltage fluctuation and system network loss of DN in the MOABC configuration scheme decreased by 54.98%,35.93%and 75.17%,respectively,compared with that without DG configuration,indicating that MOABC can reasonably plan the capacity and location of DG.Achieve the maximum trade-off between DG economy and DN operation stability.

Optimal Placement and Sizing of Distributed Generations for Power Losses Minimization Using PSO-Based Deep Learning Techniques

The integration of distributed generations (DGs) into distribution systems (DSs) is increasingly becoming a solution for compensating for isolated local energy systems (ILESs). Additionally, distributed generations are used for self-consumption with excess energy injected into centralized grids (CGs). However, the improper sizing of renewable energy systems (RESs) exposes the entire system to power losses. This work presents an optimization of a system consisting of distributed generations. Firstly, PSO algorithms evaluate the size of the entire system on the IEEE bus 14 test standard. Secondly, the size of the system is allocated using improved Particles Swarm Optimization (IPSO). The convergence speed of the objective function enables a conjecture to be made about the robustness of the proposed system. The power and voltage profile on the IEEE 14-bus standard displays a decrease in power losses and an appropriate response to energy demands (EDs), validating the proposed method.

Application of DSAPSO Algorithm in Distribution Network Reconfiguration with Distributed Generation

With the current integration of distributed energy resources into the grid,the structure of distribution networks is becoming more complex.This complexity significantly expands the solution space in the optimization process for network reconstruction using intelligent algorithms.Consequently,traditional intelligent algorithms frequently encounter insufficient search accuracy and become trapped in local optima.To tackle this issue,a more advanced particle swarm optimization algorithm is proposed.To address the varying emphases at different stages of the optimization process,a dynamic strategy is implemented to regulate the social and self-learning factors.The Metropolis criterion is introduced into the simulated annealing algorithm to occasionally accept suboptimal solutions,thereby mitigating premature convergence in the population optimization process.The inertia weight is adjusted using the logistic mapping technique to maintain a balance between the algorithm’s global and local search abilities.The incorporation of the Pareto principle involves the consideration of network losses and voltage deviations as objective functions.A fuzzy membership function is employed for selecting the results.Simulation analysis is carried out on the restructuring of the distribution network,using the IEEE-33 node system and the IEEE-69 node system as examples,in conjunction with the integration of distributed energy resources.The findings demonstrate that,in comparison to other intelligent optimization algorithms,the proposed enhanced algorithm demonstrates a shorter convergence time and effectively reduces active power losses within the network.Furthermore,it enhances the amplitude of node voltages,thereby improving the stability of distribution network operations and power supply quality.Additionally,the algorithm exhibits a high level of generality and applicability.

基于多Agent的含DG智能配电网差动保护自愈方法

含DG智能配电网中的潮流方向随分布式发电的变化而变化,导致配电网故障自愈的效果难以保障,因此,提出基于多Agent的含DG智能配电网差动保护自愈方法。通过构建基于多Agent的MAS体系结构,将其应用于含DG智能配电网差动保护和自愈的控制,在MAS体系结构的数据处理层完成差动保护,并在MAS体系结构的协调控制层实现故障自愈。结果表明,该设计方法不仅可以恢复配电网故障区域的电力,而且在操作次数、线损及功率因数方面可达到较理想的效果。

分层模型与改进IA的含DG配电网故障定位研究

常规的含分布式发电(DG)装置的配电网故障定位方法忽略了配电网馈线节点数量的影响,导致定位结果精度不高。因此,将分层模型与改进免疫算法(IA)相结合,设计了分层模型与改进IA的含DG配电网故障定位方法。首先,构建三层含DG配电网故障分层模型,并分析单节点故障信息。然后,通过改进基础IA的抗体间相似度,优化算法的期望繁殖度。最后,基于改进后的IA优化分层模型的节点搜索路径,建立世界坐标系并融合DG开关状态得到最终的故障定位信息。试验结果表明:应用该方法定位的故障节点距离与真实的故障节点距离最大差值仅为0.013 km。该方法表现出的适应度值曲线与最优适应度值曲线高度接近,定位精度较高,能够满足含DG配电网故障运维工作的现实需求。

Comprehensive Benefit Evaluation of SZ Distributed Photovoltaic Power Generation Project Based on AHP-Matter-Element Extension Model

With the introduction of the“dual carbon goals,”there has been a robust development of distributed photovoltaic power generation projects in the promotion of their construction.As part of this initiative,a comprehensive and systematic analysis has been conducted to study the overall benefits of photovoltaic power generation projects.The evaluation process encompasses economic,technical,environmental,and social aspects,providing corresponding analysis methods and data references.Furthermore,targeted countermeasures and suggestions are proposed,signifying the research’s importance for the construction and development of subsequent distributed photovoltaic power generation projects.

含DG的配网系统中性点接地方式设计研究

电力系统中性点接地方式是一个重要的综合性问题,对于电网正常运行具有重要意义。在当前的技术背景下,配网系统中性点接地方式主要包括大电流接地、小电流接地两种,并不存在统一的标准,不同接地方式适用于不同工作需求。文章通过对相关文献进行查阅,以含分布式电源(Distributed Generation,DG)的配网系统中性点接地为研究对象,设计含DG的配网系统中性点接地方式。为证实研究的有效性,结合仿真软件进行中性点接地方案仿真建模。最终发现,文章研究内容可以在架空线路、电缆线路2个场景中发挥出较为优越的技术效果,具有一定的实际应用价值。

基于变异系数和支持向量机的含DG台区线损智能诊断研究

分布式电源的接入改变了台区潮流,增加了台区线路高损概率。为找出引起台区线路高损成因,提出一种基于变异系数法和支持向量机的分布式电源接入台区线损智能诊断方法。首先利用变异系数法对分布式电源接入台区特征指标进行关联性分析;其次,采用支持向量机算法衡量线损预测数据与真实数据相对误差,进而筛选出线损异常台区;然后,基于变异系数法得到的各指标权重更新异常台区数据,诊断线路高损成因;最后,采用25节点台区案例,进行方法验证。试验结果验证了所提方法的有效性。

城市配电网DG消纳能力曲线的计算方法与分析应用

为了完整描述城市配电网的分布式发电(DG)消纳能力(TAC),探究DG TAC曲线的提升措施,提出一种城市配电网DG TAC曲线的计算方法。介绍安全域和安全边界;建立考虑馈线负荷实际情况和电压约束的TAC曲线模型,该模型利用日负荷曲线确定状态空间,通过对边界点进行电压校验得到TAC曲线。算例验证了所提方法的有效性。通过分析TAC曲线的负荷影响因素发现,只有瓶颈馈线段(组)下游负荷对TAC曲线有影响,提出增加瓶颈馈线段(组)下游负荷和瓶颈馈线段(组)扩容2种TAC曲线提升措施。提出TAC曲线在指导DG和负荷接入、导线更换方面的应用方法。

Research on Coordinated Development and Optimization of Distribution Networks at All Levels in Distributed Power Energy Engineering

The uncertainty of distributed generation energy has dramatically challenged the coordinated development of distribution networks at all levels.This paper focuses on the multi-time-scale regulation model of distributed generation energy under normal conditions.The simulation results of the example verify the self-optimization characteristics and the effectiveness of real-time dispatching of the distribution network control technology at all levels under multiple time scales.

Allocation of Hybrid Distributed Generations and Energy Management in Radial Electrical Systems

This paper presents a method for optimal sizing of a Micro grid connected to a hybrid source to ensure the continuity and quality of energy in a locality with a stochastically changing population. The hybrid system is composed of a solar photovoltaic system, a wind turbine, and an energy storage system. The reliability of the system is evaluated based on the voltage level regulation on IEEE 33-bus and IEEE 69-bus standards. Power factor correction is performed, despite some reliability and robustness constraints. This work focuses on energy management in a hybrid system considering climatic disturbances on the one hand, and on the other hand, this work evaluates the energy quality and the cost of energy. A combination of genetic algorithms of particle swarm optimization (CGAPSO) shows high convergence speed, which illustrates the robustness of the proposed system. The study of this system shows its feasibility and compliance with standards. The results obtained show a significant reduction in the total cost of production of this proposed system.

基于BAS-PSO算法的含DG配电网故障区段定位

分布式电源(DG)的大规模接入电网使得线路潮流方向变得复杂,当线路发生故障时,利用传统粒子群(PSO)算法定位故障区段的准确性不高。针对此问题,提出一种基于天牛须改进粒子群(BAS-PSO)算法的故障定位方法。首先,引入自适应的惯性权重加快算法收敛速度,并利用Tent混沌映射将种群初始化,避免其陷入局部最优解;然后,建立了开关函数和适应度函数,以定位含DG配电网故障;最后,通过Matlab对IEEE 33节点的含DG配电网故障模型进行仿真。结果表明:该算法在含DG配电网故障区段定位中搜索速度和精度更高,并且在信号发生畸变的情况下拥有良好的容错性。

基于IGDT-机会约束的配电网最大DG可开放容量评估

为应对大规模分布式电源DG(distribution generation)接入给配电网带来的挑战,考虑DG出力的不确定性以及电网储能投资成本的有限性,提出基于信息间隙决策理论IGDT(information gap decision theory)-机会约束的配电网最大DG可开放容量评估方法。首先,以最大化DG可开放容量为目标,综合考虑储能投资成本以及节点电压和线路容量机会约束等约束,建立基于IGDT-机会约束的配电网最大DG可开放容量评估模型;其次,对IGDT模型中的max项、机会约束以及网络重构等相关约束进行转化,并利用Cplex求解器对转化后的混合整数线性规划模型进行求解;最后,通过某地区有源中压配电网实例分析,验证了所提方法的有效性。

Optimal Configuration for Distributed Generations in Micro-grid System Considering Diesel as the Main Control Source

This paper proposes an optimal configuration of the distributed hybrid renewable generations based on the stand-alone micro-grid system, considering the diesel as the main control source. Due to the natural sources and load of user changes randomly and the non-tinearity of the power output by renewable generations, an intelligent optimization method based on the improvement of the genetic algorithm and the control strategy are discussed. The instance analysis is compared with the optimization result of the hybrid system based on HOMER （hybrid optimization of multiple energy resources） and GA （genetic algorithm） method on Matlab software. The simulation result of the optimal configuration showed the new hybrid renewable system and would improve the power supply situation which decreased the cost of energy greatly compared with the conventional form of power supply system which was operated only by diesel. The conclusion of the comparing result between HOMER and GA method shows the advantages of the strategy for the diesel as main control sources.

Analysis and Power Quality Improvement in Hybrid Distributed Generation System with Utilization of Unified Power Quality Conditioner

This paper presents a comprehensive study that includes the sizing and power flow by series and parallel inverters in a distributed generation system(DGs)that integrates the system of hybrid wind photovoltaic with a unified power quality conditioner(UPQC).In addition to supplying active power to the utility grid,the system of hybrid wind photovoltaic functions as a UPQC,compensating reactive power and suppressing the harmonic load currents.Additionally,the load is supplied with harmonic-free,balanced and regulated output voltages.Since PVWind-UPQC is established on a dual compensation scheme,the series inverter works like a sinusoidal current source,while the parallel inverter works like a sinusoidal voltage source.Consequently,a smooth alteration from interconnected operating modes to island operating modes and vice versa can be achieved without load voltage transients.Since PV-Wind-UPQC inverters handle the energy generated through the hybrid wind photovoltaic system and the energy demanded through the load,the converters should be sized cautiously.A detailed study of the flow of power via the PV-Wind-UPQC is imperative to gain a complete understanding of the system operation and the proper design of the converters.Thus,curves that allow the sizing of the power converters according to the power flow via the converters are presented and discussed.Simulation results are presented to assess both steady state and dynamic performances of the grid connected hybrid system of PV-Wind-UPQC.This investigation is verified by simulating and analyzing the results with Matlab/Simulink.

Energy Loss Analysis of Distributed Rooftop Photovoltaics in Industrial Parks

The analysis of the loss of distributed photovoltaic power generation systems involves the interests of energy users,energy-saving service companies,and power grid companies,so it has always been the focus of the industry and society in some manner or another.However,the related analysis for an actual case that considers different cooperative corporations’benefits is lacking in the presently available literature.This paper takes the distributed rooftop photovoltaic power generation project in an industrial park as the object,studies the analysis and calculation methods of line loss and transformer loss,analyzes the change of transformer loss under different temperatures and different load rates,and compares the data and trend of electricity consumption and power generation in industrial parks before and after the photovoltaic operation.This paper explores and practices the analysis method of the operating loss of distributed photovoltaic power generation and provides an essential reference for the benefit analysis and investment cost estimation of distributed photovoltaic power generation systems in industrial parks.The analyzed results reveal that the change loss is stable after the photovoltaic is connected,and there is no additional transformer loss.And before and after the photovoltaic system installation,there was no significant change in the total monthly data difference between the total meter and the sub-meter.