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...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.展开更多
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...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.展开更多
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 an...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.展开更多
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 ar...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.展开更多
Reconfiguration,as well as optimal utilization of distributed generation sources and capacitor banks,are highly effective methods for reducing losses and improving the voltage profile,or in other words,the power quali...Reconfiguration,as well as optimal utilization of distributed generation sources and capacitor banks,are highly effective methods for reducing losses and improving the voltage profile,or in other words,the power quality in the power distribution system.Researchers have considered the use of distributed generation resources in recent years.There are numerous advantages to utilizing these resources,the most significant of which are the reduction of network losses and enhancement of voltage stability.Non-dominated Sorting Genetic Algorithm II(NSGA-II),Multi-Objective Particle Swarm Optimization(MOPSO),and Intersect Mutation Differential Evolution(IMDE)algorithms are used in this paper to perform optimal reconfiguration,simultaneous location,and capacity determination of distributed generation resources and capacitor banks.Three scenarios were used to replicate the studies.The reconfiguration of the switches,as well as the location and determination of the capacitor bank’s optimal capacity,were investigated in this scenario.However,in the third scenario,reconfiguration,and determining the location and capacity of the Distributed Generation(DG)resources and capacitor banks have been carried out simultaneously.Finally,the simulation results of these three algorithms are compared.The results indicate that the proposed NSGAII algorithm outperformed the other two multi-objective algorithms and was capable of maintaining smaller objective functions in all scenarios.Specifically,the energy losses were reduced from 211 to 51.35 kW(a 75.66%reduction),119.13 kW(a 43.54%reduction),and 23.13 kW(an 89.04%reduction),while the voltage stability index(VSI)decreased from 6.96 to 2.105,1.239,and 1.257,respectively,demonstrating significant improvement in the voltage profile.展开更多
The setting work of backup protection using steady-state current is tedious,and mismatches occasionally occur due to the increased proportion of distributed generations(DGs)connected to the power grid.Thus,there is a ...The setting work of backup protection using steady-state current is tedious,and mismatches occasionally occur due to the increased proportion of distributed generations(DGs)connected to the power grid.Thus,there is a practical need to study a backup protection technology that does not require step-by-step setting and can be adaptively coordinated.This paper proposes an action sequence adaptive to fault positions that uses only positive sequence fault component(PSFC)voltage.Considering the influence of DGs,the unified time dial setting can be obtained by selecting specific points.The protection performance is improved by using the adjacent upstream and downstream protections to meet the coordination time interval in the case of metallic faults at the near-and far-ends of the line.Finally,the expression and implementation scheme for inverse-time backup protection(ITBP)based on the unified characteristic equation is given.Simulation results show that this scheme can adapt to DG penetration scenarios and can realize the adaptive coordination of multi-level relays.展开更多
To improve location speed,accuracy and reliability,this paper proposes a fault location method for distribution networks based on the time matrix of fault traveling waves.First,an inherent time matrix is established a...To improve location speed,accuracy and reliability,this paper proposes a fault location method for distribution networks based on the time matrix of fault traveling waves.First,an inherent time matrix is established according to the normalized topology of the target distribution network,and a post-fault time matrix is obtained by extracting the head data of initial waves from traveling wave detection devices.A time determination matrix is then obtained using the difference operation between the two matrices.The features of the time determination matrix are used for fault section identification and fault distance calculation,to accurately locate faults.The method is modified by considering economic benefits,through the optimal configuration of detection devices of traveling waves when calculating fault distances.Simulation results show that the proposed method has good adaptation with higher fault location accu-racy than two other typical ones.It can deal with faults on invalid branches,and the error rate is under 0.5%even with connected DGs.展开更多
This study proposes a new method which aims to optimally install tie-lines and distributed generations simultaneously.This is done to optimize the post-outage reconfiguration and minimize energy losses and energy not ...This study proposes a new method which aims to optimally install tie-lines and distributed generations simultaneously.This is done to optimize the post-outage reconfiguration and minimize energy losses and energy not supplied of distribution systems.The number and location of tie-lines,as well as the number,size,and location of DGs,are pinpointed through teaching the learning-based optimization(TLBO)method.The objective function in the current research is to minimize the costs pertaining to the investment,operation,energy losses,and energies not supplied.In addition to the normal operational condition,fault operational condition is also evaluated.Therefore,the optimal post-fault reconfigurations for fault occurrences in all lines are established.Moreover,the operational constraints such as the voltage and line current limits are taken into account in both normal and post-fault operational modes.Finally,the modified IEEE 33-bus and 69-bus distribution test systems are selected and tested to demonstrate the effectiveness of the simultaneous placement of DGs and tie-line technique proposed in this paper.展开更多
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 p...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.展开更多
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 t...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.展开更多
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 comprehen...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.展开更多
To integrate different renewable energy resources effectively in a microgrid, a configuration optimization model of a multi-energy distributed generation（DG） system and its auxiliary equipment is proposed. The model...To integrate different renewable energy resources effectively in a microgrid, a configuration optimization model of a multi-energy distributed generation（DG） system and its auxiliary equipment is proposed. The model mainly consists of two parts, the determination of initial configuration schemes according to user preference and the selection of the optimal scheme. The comprehensive evaluation index（CEI）, which is acquired through the analytic hierarchy process（AHP） weight calculation method, is adopted as the evaluation criterion to rank the initial schemes. The optimal scheme is obtained according to the ranking results. The proposed model takes the diversity of different equipment parameters and investment cost into consideration and can give relatively suitable and economical suggestions for system configuration.Additionally, unlike Homer Pro, the proposed model considers the complementation of different renewable energy resources, and thus the rationality of the multi-energy DG system is improved compared with the single evaluation criterion method which only considers the total cost.展开更多
This paper introduces an optimized planning approach for integrating photovoltaic as distributed generation (PV-DG) into the radial distribution power systems, utilizing exhaustive load flow (ELF), loss sensitivity fa...This paper introduces an optimized planning approach for integrating photovoltaic as distributed generation (PV-DG) into the radial distribution power systems, utilizing exhaustive load flow (ELF), loss sensitivity factor (LSF), genetic algorithms (GA) methods, and numerical method based on LSF. The methodology aims to determine the optimal allocation and sizing of multiple PV-DG to minimize power loss through time series power flow analysis. An approach utilizing continuous sensitivity analysis is developed and inherently leverages power flow and loss equations to compute LSF of all buses in the system towards employing a dynamic PV-DG model for more accurate results. The algorithm uses a numerical grid search method to optimize PV-DG placement in a power distribution system, focusing on minimizing system losses. It combines iterative analysis, sensitivity assessment, and comprehensive visualization to identify and present the optimal PV-DG configurations. The present-ed algorithms are verified through co-simulation framework combining MATLAB and OpenDSS to carry out analysis for 12-bus radial distribution test system. The proposed numerical method is compared with other algorithms, such as ELF, LSF methods, and Genetic Algorithms (GA). Results show that the proposed numerical method performs well in comparison with LSF and ELF solutions.展开更多
This paper presents an optimized strategy for multiple integrations of photovoltaic distributed generation (PV-DG) within radial distribution power systems. The proposed methodology focuses on identifying the optimal ...This paper presents an optimized strategy for multiple integrations of photovoltaic distributed generation (PV-DG) within radial distribution power systems. The proposed methodology focuses on identifying the optimal allocation and sizing of multiple PV-DG units to minimize power losses using a probabilistic PV model and time-series power flow analysis. Addressing the uncertainties in PV output due to weather variability and diurnal cycles is critical. A probabilistic assessment offers a more robust analysis of DG integration’s impact on the grid, potentially leading to more reliable system planning. The presented approach employs a genetic algorithm (GA) and a determined PV output profile and probabilistic PV generation profile based on experimental measurements for one year of solar radiation in Cairo, Egypt. The proposed algorithms are validated using a co-simulation framework that integrates MATLAB and OpenDSS, enabling analysis on a 33-bus test system. This framework can act as a guideline for creating other co-simulation algorithms to enhance computing platforms for contemporary modern distribution systems within smart grids concept. The paper presents comparisons with previous research studies and various interesting findings such as the considered hours for developing the probabilistic model presents different results.展开更多
The literature on multi-attribute optimization for renewable energy source(RES)placement in deregulated power markets is extensive and diverse in methodology.This study focuses on the most relevant publications direct...The literature on multi-attribute optimization for renewable energy source(RES)placement in deregulated power markets is extensive and diverse in methodology.This study focuses on the most relevant publications directly addressing the research problem at hand.Similarly,while the body of work on optimal location and sizing of renewable energy generators(REGs)in balanced distribution systems is substantial,only the most pertinent sources are cited,aligning closely with the study’s objective function.A comprehensive literature review reveals several key research areas:RES integration,RES-related optimization techniques,strategic placement of wind and solar generation,and RES promotion in deregulated powermarkets,particularly within transmission systems.Furthermore,the optimal location and sizing of REGs in both balanced and unbalanced distribution systems have been extensively studied.RESs demonstrate significant potential for standalone applications in remote areas lacking conventional transmission and distribution infrastructure.Also presents a thorough review of current modeling and optimization approaches for RES-based distribution system location and sizing.Additionally,it examines the optimal positioning,sizing,and performance of hybrid and standalone renewable energy systems.This paper provides a comprehensive review of current modeling and optimization approaches for the location and sizing of Renewable Energy Sources(RESs)in distribution systems,focusing on both balanced and unbalanced networks.展开更多
With the widespread implementation of distributed generation(DG)and the integration of soft open point(SOP)into the distribution network(DN),the latter is steadily transitioning into a flexible distribution network(FD...With the widespread implementation of distributed generation(DG)and the integration of soft open point(SOP)into the distribution network(DN),the latter is steadily transitioning into a flexible distribution network(FDN),the calculation of carbon flow distribution in FDN is more difficult.To this end,this study constructs a model for low-carbon optimal operations within the FDN on the basis of enhanced carbon emission flow(CEF).First,the carbon emission characteristics of FDNs are scrutinized and an improved method for calculating carbon flow within these networks is proposed.Subsequently,a model for optimizing low-carbon operations within FDNs is formulated based on the refined CEF,which merges the specificities of DG and intelligent SOP.Finally,this model is scrutinized using an upgraded IEEE 33-node distribution system,a comparative analysis of the cases reveals that when DG and SOP are operated in a coordinated manner in the FDN,with the cost of electricity generation was reduced by 40.63 percent and the cost of carbon emissions by 10.18 percent.The findings indicate that the judicious optimization of areas exhibiting higher carbon flow rates can effectively enhance the economic efficiency of DN operations and curtail the carbon emissions of the overall network.展开更多
This paper presents a control strategy of a hybrid fuel cell/battery distributed generation (HDG) system in distribution systems. The overall structure of the HDG system is given, dynamic models for the solid oxide fu...This paper presents a control strategy of a hybrid fuel cell/battery distributed generation (HDG) system in distribution systems. The overall structure of the HDG system is given, dynamic models for the solid oxide fuel cell (SOFC) power plant, battery bank and its power electronic interfacing are briefly described, and controller design methodologies for the power conditioning units and fuel cell to control the power flow from the hybrid power plant to the utility grid are presented. To distribute the power between the fuel cell power plant and the battery energy storage, a neuro-fuzzy controller has been developed. Also, for controlling the active and reactive power independently in distribution systems, the current control strategy based on two fuzzy logic controllers has been presented. A Matlab/Simulink simulation model is developed for the HDG system by combining the individual component models and their controllers. Simulation results show the overall system performance including load-following and power management of the HDG system.展开更多
Distributed energy resources have been proven to be an effective and promising solution to enhance power system resilience and improve household-level reliability.In this paper,we propose a method to evaluate the reli...Distributed energy resources have been proven to be an effective and promising solution to enhance power system resilience and improve household-level reliability.In this paper,we propose a method to evaluate the reliability value of a photovoltaic(PV)energy system with a battery storage system(BSS)by considering the probability of grid outages causing household blackouts.Considering this reliability value,which is the economic profit and capital cost of PV+BSS,a simple formula is derived to calculate the optimal planning strategy.This strategy can provide household-level customers with a simple and straightforward expression for invested PV+BSS capacity.Case studies on 600 households located in eight zones of the US for the period of 2006 to 2015 demonstrate that adding the reliability value to economic profit allows households to invest in a larger PV+BSS and avoid loss of load caused by blackouts.Owing to the differences in blackout hours,households from the 8 zones express distinct willingness to install PV+BSS.The greater the probability of blackout,the greater revenue that household can get from the PV+BSS.The simulation example shows that the planning strategy obtained by proposed model has good economy in the actual operation and able to reduce the economic risk of power failure of the household users.This model can provide household with an easy and straightforward investment strategy of PV+BSS capacity.展开更多
With development of distributed generation(DG),configuration of optimization equipment is crucial for absorbing excess electricity and stabilizing fluctuations.This study proposes a two-layer configuration strategy co...With development of distributed generation(DG),configuration of optimization equipment is crucial for absorbing excess electricity and stabilizing fluctuations.This study proposes a two-layer configuration strategy coordinates active cyber control and the physical energy storage(ES)system.First,an upper economic model is developed.Based on chance-constrained programming,an operation model accounts for inherent uncertainty are then developed.Under constraint of voltage risk level,a lower operation model is developed.Finally,a solution based on differential evolution is provided.An IEEE 33 bus system simulation was used to validate efficacy of model.The effects of risk level,equipment price,and chance-constrained probability were analyzed,providing a foundation for power consumption and expansion of cyber-physical systems.展开更多
The penetration rate of distributed generation is gradually increasing in the distribution system concerned.This is creating new problems and challenges in the planning and operation of the system.The intermittency an...The penetration rate of distributed generation is gradually increasing in the distribution system concerned.This is creating new problems and challenges in the planning and operation of the system.The intermittency and variability of power outputs from numerous distributed renewable generators could significantly jeopardize the secure operation of the distribution system.Therefore,it is necessary to assess the hosting capability for intermittent distributed generation by a distribution system considering operational constraints.This is the subject of this study.An assessment model considering the uncertainty of generation outputs from distributed generators is presented for this purpose.It involves different types of regulation or control functions using on-load tap-changers(OLTCs),reactive power compensation devices,energy storage systems,and the reactive power support of the distributed generators employed.A robust optimization model is then attained It is solved by Bertsimas robust counterpart through GUROBI solver.Finally,the feasibility and efficiency of the proposed method are demonstrated by a modified IEEE 33-bus distribution system.In addition,the effects of the aforementioned regulation or control functions on the enhancement of the hosting capability for intermittent distributed generation are examined.展开更多
文摘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.
文摘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.
文摘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.
文摘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.
文摘Reconfiguration,as well as optimal utilization of distributed generation sources and capacitor banks,are highly effective methods for reducing losses and improving the voltage profile,or in other words,the power quality in the power distribution system.Researchers have considered the use of distributed generation resources in recent years.There are numerous advantages to utilizing these resources,the most significant of which are the reduction of network losses and enhancement of voltage stability.Non-dominated Sorting Genetic Algorithm II(NSGA-II),Multi-Objective Particle Swarm Optimization(MOPSO),and Intersect Mutation Differential Evolution(IMDE)algorithms are used in this paper to perform optimal reconfiguration,simultaneous location,and capacity determination of distributed generation resources and capacitor banks.Three scenarios were used to replicate the studies.The reconfiguration of the switches,as well as the location and determination of the capacitor bank’s optimal capacity,were investigated in this scenario.However,in the third scenario,reconfiguration,and determining the location and capacity of the Distributed Generation(DG)resources and capacitor banks have been carried out simultaneously.Finally,the simulation results of these three algorithms are compared.The results indicate that the proposed NSGAII algorithm outperformed the other two multi-objective algorithms and was capable of maintaining smaller objective functions in all scenarios.Specifically,the energy losses were reduced from 211 to 51.35 kW(a 75.66%reduction),119.13 kW(a 43.54%reduction),and 23.13 kW(an 89.04%reduction),while the voltage stability index(VSI)decreased from 6.96 to 2.105,1.239,and 1.257,respectively,demonstrating significant improvement in the voltage profile.
基金supported in part by the National Natural Science Foundation of China(NSFC-UKRI_EPSRC)(No.52061635105)in part by the Science and Technology Program of SGCC(No.5100-202040327A-0-0-00).
文摘The setting work of backup protection using steady-state current is tedious,and mismatches occasionally occur due to the increased proportion of distributed generations(DGs)connected to the power grid.Thus,there is a practical need to study a backup protection technology that does not require step-by-step setting and can be adaptively coordinated.This paper proposes an action sequence adaptive to fault positions that uses only positive sequence fault component(PSFC)voltage.Considering the influence of DGs,the unified time dial setting can be obtained by selecting specific points.The protection performance is improved by using the adjacent upstream and downstream protections to meet the coordination time interval in the case of metallic faults at the near-and far-ends of the line.Finally,the expression and implementation scheme for inverse-time backup protection(ITBP)based on the unified characteristic equation is given.Simulation results show that this scheme can adapt to DG penetration scenarios and can realize the adaptive coordination of multi-level relays.
基金funded by grants from the National Natural Science Foundation of China (61703345)the Chunhui Project Foundation of the Education Department of China (Z201980)the Open Research Subject of Key Laboratory of Fluid and Power Machinery (Xihua University),Ministry of Education (szjj2019-27).
文摘To improve location speed,accuracy and reliability,this paper proposes a fault location method for distribution networks based on the time matrix of fault traveling waves.First,an inherent time matrix is established according to the normalized topology of the target distribution network,and a post-fault time matrix is obtained by extracting the head data of initial waves from traveling wave detection devices.A time determination matrix is then obtained using the difference operation between the two matrices.The features of the time determination matrix are used for fault section identification and fault distance calculation,to accurately locate faults.The method is modified by considering economic benefits,through the optimal configuration of detection devices of traveling waves when calculating fault distances.Simulation results show that the proposed method has good adaptation with higher fault location accu-racy than two other typical ones.It can deal with faults on invalid branches,and the error rate is under 0.5%even with connected DGs.
文摘This study proposes a new method which aims to optimally install tie-lines and distributed generations simultaneously.This is done to optimize the post-outage reconfiguration and minimize energy losses and energy not supplied of distribution systems.The number and location of tie-lines,as well as the number,size,and location of DGs,are pinpointed through teaching the learning-based optimization(TLBO)method.The objective function in the current research is to minimize the costs pertaining to the investment,operation,energy losses,and energies not supplied.In addition to the normal operational condition,fault operational condition is also evaluated.Therefore,the optimal post-fault reconfigurations for fault occurrences in all lines are established.Moreover,the operational constraints such as the voltage and line current limits are taken into account in both normal and post-fault operational modes.Finally,the modified IEEE 33-bus and 69-bus distribution test systems are selected and tested to demonstrate the effectiveness of the simultaneous placement of DGs and tie-line technique proposed in this paper.
基金This research is supported by the Science and Technology Program of Gansu Province(No.23JRRA880).
文摘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.
文摘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.
文摘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.
基金The National Natural Science Foundation of China(No.51377021)the Science and Technology Project of State Grid Corporation of China(No.SGTJDK00DWJS1600014)
文摘To integrate different renewable energy resources effectively in a microgrid, a configuration optimization model of a multi-energy distributed generation（DG） system and its auxiliary equipment is proposed. The model mainly consists of two parts, the determination of initial configuration schemes according to user preference and the selection of the optimal scheme. The comprehensive evaluation index（CEI）, which is acquired through the analytic hierarchy process（AHP） weight calculation method, is adopted as the evaluation criterion to rank the initial schemes. The optimal scheme is obtained according to the ranking results. The proposed model takes the diversity of different equipment parameters and investment cost into consideration and can give relatively suitable and economical suggestions for system configuration.Additionally, unlike Homer Pro, the proposed model considers the complementation of different renewable energy resources, and thus the rationality of the multi-energy DG system is improved compared with the single evaluation criterion method which only considers the total cost.
文摘This paper introduces an optimized planning approach for integrating photovoltaic as distributed generation (PV-DG) into the radial distribution power systems, utilizing exhaustive load flow (ELF), loss sensitivity factor (LSF), genetic algorithms (GA) methods, and numerical method based on LSF. The methodology aims to determine the optimal allocation and sizing of multiple PV-DG to minimize power loss through time series power flow analysis. An approach utilizing continuous sensitivity analysis is developed and inherently leverages power flow and loss equations to compute LSF of all buses in the system towards employing a dynamic PV-DG model for more accurate results. The algorithm uses a numerical grid search method to optimize PV-DG placement in a power distribution system, focusing on minimizing system losses. It combines iterative analysis, sensitivity assessment, and comprehensive visualization to identify and present the optimal PV-DG configurations. The present-ed algorithms are verified through co-simulation framework combining MATLAB and OpenDSS to carry out analysis for 12-bus radial distribution test system. The proposed numerical method is compared with other algorithms, such as ELF, LSF methods, and Genetic Algorithms (GA). Results show that the proposed numerical method performs well in comparison with LSF and ELF solutions.
文摘This paper presents an optimized strategy for multiple integrations of photovoltaic distributed generation (PV-DG) within radial distribution power systems. The proposed methodology focuses on identifying the optimal allocation and sizing of multiple PV-DG units to minimize power losses using a probabilistic PV model and time-series power flow analysis. Addressing the uncertainties in PV output due to weather variability and diurnal cycles is critical. A probabilistic assessment offers a more robust analysis of DG integration’s impact on the grid, potentially leading to more reliable system planning. The presented approach employs a genetic algorithm (GA) and a determined PV output profile and probabilistic PV generation profile based on experimental measurements for one year of solar radiation in Cairo, Egypt. The proposed algorithms are validated using a co-simulation framework that integrates MATLAB and OpenDSS, enabling analysis on a 33-bus test system. This framework can act as a guideline for creating other co-simulation algorithms to enhance computing platforms for contemporary modern distribution systems within smart grids concept. The paper presents comparisons with previous research studies and various interesting findings such as the considered hours for developing the probabilistic model presents different results.
文摘The literature on multi-attribute optimization for renewable energy source(RES)placement in deregulated power markets is extensive and diverse in methodology.This study focuses on the most relevant publications directly addressing the research problem at hand.Similarly,while the body of work on optimal location and sizing of renewable energy generators(REGs)in balanced distribution systems is substantial,only the most pertinent sources are cited,aligning closely with the study’s objective function.A comprehensive literature review reveals several key research areas:RES integration,RES-related optimization techniques,strategic placement of wind and solar generation,and RES promotion in deregulated powermarkets,particularly within transmission systems.Furthermore,the optimal location and sizing of REGs in both balanced and unbalanced distribution systems have been extensively studied.RESs demonstrate significant potential for standalone applications in remote areas lacking conventional transmission and distribution infrastructure.Also presents a thorough review of current modeling and optimization approaches for RES-based distribution system location and sizing.Additionally,it examines the optimal positioning,sizing,and performance of hybrid and standalone renewable energy systems.This paper provides a comprehensive review of current modeling and optimization approaches for the location and sizing of Renewable Energy Sources(RESs)in distribution systems,focusing on both balanced and unbalanced networks.
基金supported in part by National Natural Science Foundation of China under Grant 52007026.
文摘With the widespread implementation of distributed generation(DG)and the integration of soft open point(SOP)into the distribution network(DN),the latter is steadily transitioning into a flexible distribution network(FDN),the calculation of carbon flow distribution in FDN is more difficult.To this end,this study constructs a model for low-carbon optimal operations within the FDN on the basis of enhanced carbon emission flow(CEF).First,the carbon emission characteristics of FDNs are scrutinized and an improved method for calculating carbon flow within these networks is proposed.Subsequently,a model for optimizing low-carbon operations within FDNs is formulated based on the refined CEF,which merges the specificities of DG and intelligent SOP.Finally,this model is scrutinized using an upgraded IEEE 33-node distribution system,a comparative analysis of the cases reveals that when DG and SOP are operated in a coordinated manner in the FDN,with the cost of electricity generation was reduced by 40.63 percent and the cost of carbon emissions by 10.18 percent.The findings indicate that the judicious optimization of areas exhibiting higher carbon flow rates can effectively enhance the economic efficiency of DN operations and curtail the carbon emissions of the overall network.
文摘This paper presents a control strategy of a hybrid fuel cell/battery distributed generation (HDG) system in distribution systems. The overall structure of the HDG system is given, dynamic models for the solid oxide fuel cell (SOFC) power plant, battery bank and its power electronic interfacing are briefly described, and controller design methodologies for the power conditioning units and fuel cell to control the power flow from the hybrid power plant to the utility grid are presented. To distribute the power between the fuel cell power plant and the battery energy storage, a neuro-fuzzy controller has been developed. Also, for controlling the active and reactive power independently in distribution systems, the current control strategy based on two fuzzy logic controllers has been presented. A Matlab/Simulink simulation model is developed for the HDG system by combining the individual component models and their controllers. Simulation results show the overall system performance including load-following and power management of the HDG system.
基金supported by National Natural Science Foundation of China(Project 51907064)in part by China State Key Lab.of Power System(SKLD19KM09)in part by State Grid Corporation of China(1400202024222A-0-0-00)
文摘Distributed energy resources have been proven to be an effective and promising solution to enhance power system resilience and improve household-level reliability.In this paper,we propose a method to evaluate the reliability value of a photovoltaic(PV)energy system with a battery storage system(BSS)by considering the probability of grid outages causing household blackouts.Considering this reliability value,which is the economic profit and capital cost of PV+BSS,a simple formula is derived to calculate the optimal planning strategy.This strategy can provide household-level customers with a simple and straightforward expression for invested PV+BSS capacity.Case studies on 600 households located in eight zones of the US for the period of 2006 to 2015 demonstrate that adding the reliability value to economic profit allows households to invest in a larger PV+BSS and avoid loss of load caused by blackouts.Owing to the differences in blackout hours,households from the 8 zones express distinct willingness to install PV+BSS.The greater the probability of blackout,the greater revenue that household can get from the PV+BSS.The simulation example shows that the planning strategy obtained by proposed model has good economy in the actual operation and able to reduce the economic risk of power failure of the household users.This model can provide household with an easy and straightforward investment strategy of PV+BSS capacity.
基金supported by the National Key R&D Plan(2017YFB0903100)State Grid Electric Power Co.,Ltd.science and technology project(2021JBGS-03).
文摘With development of distributed generation(DG),configuration of optimization equipment is crucial for absorbing excess electricity and stabilizing fluctuations.This study proposes a two-layer configuration strategy coordinates active cyber control and the physical energy storage(ES)system.First,an upper economic model is developed.Based on chance-constrained programming,an operation model accounts for inherent uncertainty are then developed.Under constraint of voltage risk level,a lower operation model is developed.Finally,a solution based on differential evolution is provided.An IEEE 33 bus system simulation was used to validate efficacy of model.The effects of risk level,equipment price,and chance-constrained probability were analyzed,providing a foundation for power consumption and expansion of cyber-physical systems.
基金the Scientific and Technological Project of SGCC Headquarters entitled“Smart Distribution Network and Ubiquitous Power Internet of Things Integrated Development Collaborative Planning Technology Research”(5400-201956447A-0-0-00).
文摘The penetration rate of distributed generation is gradually increasing in the distribution system concerned.This is creating new problems and challenges in the planning and operation of the system.The intermittency and variability of power outputs from numerous distributed renewable generators could significantly jeopardize the secure operation of the distribution system.Therefore,it is necessary to assess the hosting capability for intermittent distributed generation by a distribution system considering operational constraints.This is the subject of this study.An assessment model considering the uncertainty of generation outputs from distributed generators is presented for this purpose.It involves different types of regulation or control functions using on-load tap-changers(OLTCs),reactive power compensation devices,energy storage systems,and the reactive power support of the distributed generators employed.A robust optimization model is then attained It is solved by Bertsimas robust counterpart through GUROBI solver.Finally,the feasibility and efficiency of the proposed method are demonstrated by a modified IEEE 33-bus distribution system.In addition,the effects of the aforementioned regulation or control functions on the enhancement of the hosting capability for intermittent distributed generation are examined.
