Evaluation of Multi-Temporal-Spatial Scale Adjustment Capability and Cluster Optimization Operation Method for Distribution Networks with Distributed Photovoltaics

Themassive integration of high-proportioned distributed photovoltaics into distribution networks poses significant challenges to the flexible regulation capabilities of distribution stations.To accurately assess the flexible regulation capabilities of distribution stations,amulti-temporal and spatial scale regulation capability assessment technique is proposed for distribution station areas with distributed photovoltaics,considering different geographical locations,coverage areas,and response capabilities.Firstly,the multi-temporal scale regulation characteristics and response capabilities of different regulation resources in distribution station areas are analyzed,and a resource regulation capability model is established to quantify the adjustable range of different regulation resources.On this basis,considering the limitations of line transmission capacity,a regulation capability assessment index for distribution stations is proposed to evaluate their regulation capabilities.Secondly,considering different geographical locations and coverage areas,a comprehensive performance index based on electrical distance modularity and active power balance is established,and a cluster division method based on genetic algorithms is proposed to fully leverage the coordination and complementarity among nodes and improve the active power matching degree within clusters.Simultaneously,an economic optimization model with the objective of minimizing the economic cost of the distribution station is established,comprehensively considering the safety constraints of the distribution network and the regulation constraints of resources.This model can provide scientific guidance for the economic dispatch of the distribution station area.Finally,case studies demonstrate that the proposed assessment and optimization methods effectively evaluate the regulation capabilities of distribution stations,facilitate the consumption of distributed photovoltaics,and enhance the economic efficiency of the distribution station area.

A Distributed Photovoltaics Ordering Grid-Connected Method for Analyzing Voltage Impact in Radial Distribution Networks

In recent years,distributed photovoltaics(DPV)has ushered in a good development situation due to the advantages of pollution-free power generation,full utilization of the ground or roof of the installation site,and balancing a large number of loads nearby.However,under the background of a large-scale DPV grid-connected to the county distribution network,an effective analysis method is needed to analyze its impact on the voltage of the distribution network in the early development stage of DPV.Therefore,a DPV orderly grid-connected method based on photovoltaics grid-connected order degree(PGOD)is proposed.This method aims to orderly analyze the change of voltage in the distribution network when large-scale DPV will be connected.Firstly,based on the voltagemagnitude sensitivity(VMS)index of the photovoltaics permitted grid-connected node and the acceptance of grid-connected node(AoGCN)index of other nodes in the network,thePGODindex is constructed to determine the photovoltaics permitted grid-connected node of the current photovoltaics grid-connected state network.Secondly,a photovoltaics orderly grid-connected model with a continuous updating state is constructed to obtain an orderly DPV grid-connected order.The simulation results illustrate that the photovoltaics grid-connected order determined by this method based on PGOD can effectively analyze the voltage impact of large-scale photovoltaics grid-connected,and explore the internal factors and characteristics of the impact.

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.

The analysis of distributed photovoltaic access system schemes

As the share of photovoltaic power generation in power system has increased year by year, the optimization choice of access system schemes become one of the first and most important problems in grid before admitting photovoltaic power generation. Therefore, this article takes a proposed distributed photovoltaic as an example to research and analyze two kinds of high density multiple access points distributed photovoltaic access system schemes. The emphasis is making a comprehensive comparison and selection among the aspect of active power loss and economic benefit, etc. In the premise of ensuring the normal power generation of the photovoltaic system, it puts forward the recommended scheme that can help to spontaneous self-consumption, elimination on the spot, effectively decrease network loss and economic benefit.

Distributed Photovoltaic Real-Time Output Estimation Based on Graph Convolutional Networks

The rapid growth of distributed photovoltaic(PV)has remarkable influence for the safe and economic operation of power systems.In view of the wide geographical distribution and a large number of distributed PV power stations,the current situation is that it is dificult to access the current dispatch data network.According to the temporal and spatial characteristics of distributed PV,a graph convolution algorithm based on adaptive learning of adjacency matrix is proposed to estimate the real-time output of distributed PV in regional power grid.The actual case study shows that the adaptive graph convolution model gives different adjacency matrixes for different PV stations,which makes the corresponding output estimation algorithm have higher accuracy.

Cluster voltage control method for “Whole County” distributed photovoltaics based on improved differential evolution algorithm

China is vigorously promoting the “whole county promotion” of distributed photovoltaics (DPVs). However, the high penetration rate of DPVs has brought problems such as voltage violation and power quality degradation to the distribution network, seriously affecting the safety and reliability of the power system. The traditional centralized control method of the distribution network has the problem of low efficiency, which is not practical enough in engineering practice. To address the problems, this paper proposes a cluster voltage control method for distributed photovoltaic grid-connected distribution network. First, it partitions the distribution network into clusters, and different clusters exchange terminal voltage information through a “virtual slack bus.” Then, in each cluster, based on the control strategy of “reactive power compensation first, active power curtailment later,” it employs an improved differential evolution (IDE) algorithm based on Cauchy disturbance to control the voltage. Simulation results in two different distribution systems show that the proposed method not only greatly improves the operational efficiency of the algorithm but also effectively controls the voltage of the distribution network, and maximizes the consumption capacity of DPVs based on qualified voltage.

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.

Power quality enhancement and engineering application with high permeability distributed photovoltaic access to low-voltage distribution networks in Australia

Considering power quality problems such as overvoltage and three-phase unbalance caused by high permeability distributed photovoltaic access in low-voltage distribution networks,this paper proposes a comprehensive control scheme using a static var.generator(SVG),electric energy storage(EES),a phase switching device(PSD)and an intelligent terminal controller.The control strategies of transformer overload,bus over/under voltage,anticountercurrent,storage battery state of charge(SOC)maintenance,and three-phase unbalance are studied.The engineering application in the Greenvale low-voltage distribution networks in Australia with high permeability distributed photovoltaics is discussed.The results show that the intelligent terminal controller is able to improve the power quality of low-voltage distribution networks through coordination with EES,SVG and PSD.

Distributed photovoltaics with peer-to-peer electricity trading

Distributed electricity generation technologies,like solar photovoltaic(PV),have achieved rapid development in recent years,but are constrained by some problems such as low marketization and lag in public services.The peer-to-peer(P2P)electricity trading,which allows direct electricity transactions between local consumers and prosumers,has the potential to efficiently distribute the profits coming from self-consumption of PV electricity among all participants.This study proposes a three-layer P2P electricity trading system for communities with high penetration of household distributed PV.The trading system includes a physical layer based on the power grid,an information layer based on a virtual agent network,and a market layer based on a continuous double auction(CDA)mechanism combined with market clearing.By using simulation of trading experiments,a community with 60 houses and 50%PV occupancy is studied as a case.Results show that in one day,62.5%of the surplus PV electricity of all prosumers actually can be consumed within the community.Through P2P electricity trading of this part of electricity,total incomes of prosumers can increase by 11.5%,and total expense of all users decrease by 7.5%,resulting in that the net expenses of the whole community decrease by 13.8%.It is concluded that P2P electricity trading can unite the whole PV community as a bigger prosumer,and make every residential house in the community share the profits from local PV consumption,which could promote the subsidy-free development and grid parity of household distributed PV in the future.

DPV接入对电网调控运行的影响及解决措施

随着全球能源结构的转型和可再生能源技术的发展,分布式光伏(Distributed Photovoltaic,DPV)系统作为一种重要的绿色能源解决方案得到广泛使用,这种快速发展也给电力系统的调控运行带来新的挑战。文章通过概述DPV和电网调控,深入探讨DPV接入对电网调控运行的影响。最后,针对这些问题提出相应的解决措施,并提出基于DPV保护开关的防孤岛保护策略,以提升电网安全性,确保电网在DPV接入后能够稳定可靠运行。

Very Short-Term Forecasting of Distributed PV Power Using GSTANN

Photovoltaic(PV)power forecasting is essential for secure operation of a power system.Effective prediction of PV power can improve new energy consumption capacity,help power system planning,promote development of smart grids,and ultimately support construction of smart energy cities.However,different from centralized PV power forecasts,three critical challenges are encountered in distributed PV power forecasting:1)lack of on-site meteorological observation,2)leveraging extraneous data to enhance forecasting performance,3)spatial-temporal modelling methods of meteorological information around the distributed PV stations.To address these issues,we propose a Graph Spatial-Temporal Attention Neural Network(GSTANN)to predict the very short-term power of distributed PV.First,we use satellite remote sensing data covering a specific geographical area to supplement meteorological information for all PV stations.Then,we apply the graph convolution block to model the non-Euclidean local and global spatial dependence and design an attention mechanism to simultaneously derive temporal and spatial correlations.Subsequently,we propose a data fusion module to solve the time misalignment between satellite remote sensing data and surrounding measured on-site data and design a power approximation block to map the conversion from solar irradiance to PV power.Experiments conducted with real-world case study datasets demonstrate that the prediction performance of GSTANN outperforms five state-of-the-art baselines.

Design of Smart Home System Based on ZigBee Technology and R&D for Application

In this paper, a smart home system based on ZigBee technology is designed. The system includes home network, home server and mobile terminal. The program is highly scalable and cost-effective. This paper developed the home server-side application based on MFC technology and the mobile terminal application. The mobile client can remotely control home devices and query the running state, electric energy information and historical data of home devices. At the same time, the home server-side application can store electric energy information and electricity consumption of home devices. Combined with household distributed photovoltaic generation system, the system can be applied to home energy management system. Through running tests and application, the results show that the system has realized basic functions of smart home and achieved the desired design goals.

Low-carbon building heating system coupled with semiconductor radiation heating and distributed PV:A simulation analysis in two Chinese climate zones

Building is an important scenario for achieving global carbon peak and carbon neutrality goals,accounting for approximately 37%of global energy-related CO_(2) emissions in 2020.In the meanwhile,the construction and operation of buildings was responsible for 36%of global energy consumption,of which 30%energy was used for space heating.Therefore,this paper proposes a low-carbon building heating system that is coupled to a new semiconductor radiation heating unit and distributed rooftop photovoltaic to reduce carbon emissions.To reveal its building heating characteristics,a dynamic model of heat transfer based on semiconductor low-temperature radiant heating is first established by analyzing the heat conduction,convection,and radiation models,and the uncertainty from both the distributed rooftop photovoltaic and building heating demand is considered in the building heating operation strategy.Then,a simulation model of a low-carbon building heating system is built in MATLAB/SIMULINK for two different climate zones in China(Beijing and Wuhan).When building and using the low-carbon building heating system stable for 30 years,the payback period is 5.2–8.2 years in Beijing and 6.4–11.6 years in Wuhan.Compared with the traditional grid-powered heating system,the simulation revealed that the carbon emissions of Beijing and Wuhan during the heating season are reduced by 44.9%and 44.3%,respectively,and the corresponding building heating cost is saved by 62.1%and 57.8%.