Sizing Of DG Units Research Articles

A hybrid chaotic bat algorithm for optimal placement and sizing of dg units in radial distribution networks

Appropriate location and sizing of distributed generation (DG) units in a radial distribution system (RDS) play a significant role in the improvement of its overall performance. Indeed, proper DG placement and sizing help in maintaining the balance between power supply and demand, decreasing energy losses and enhancing voltage profile. Within this context, this paper presents an effective approach for the determination of the optimal location and the appropriate capacity of a photovoltaic distributed generation (PVDG) unit in RDSs. In the suggested approach, the best position of the PVDG is selected using the loss sensitivity factor (LSF). Meanwhile, a new optimization technique incorporating chaos, bats’ self-adaptive compensation, and Doppler effect into the original bat algorithm (BA) is developed to find the optimal size of the PVDG unit. The optimal PVDG size is optimally determined in such a way that total active power losses of the RDS is reduced and voltage profile is enhanced. The performance of the proposed optimization technique, symbolized by (CSA-DC)BA, is evaluated using various benchmark functions. Moreover, the applicability and effectiveness of the suggested approach are verified on the IEEE 33-bus and the IEEE 69-bus RDSs. Obtained results revealed that the proposed (CSA-DC)BA outperforms the comparison optimization techniques.

A Novel Integration Technique for Optimal Location & Sizing of DG Units With Reconfiguration in Radial Distribution Networks Considering Reliability

A Novel Integration Technique for Optimal Location & Sizing of DG Units With Reconfiguration in Radial Distribution Networks Considering Reliability

Reliability Assessment Based on Optimal DGs Planning in the Distribution Systems

Due to increased load demands, distribution systems suffer from high power losses, low voltage levels, high current, and low reliability. To solve these problems, integrate distributed generator units (DG) into the distribution system. DG units are among the most popular methods of improving distribution system reliability, power losses, and bus voltage improvement through the placement and selection of distributed generator units in an optimal location and size. This work proposed Enhanced Particle Swarm Optimization (EPSO) technology to find the optimum location and size of DG units to reduce power losses, improve bus voltage level, and employed the Transient Electricity Analyzer (ETAP) to evaluate the reliability of the distribution system network. ETAP is a programming tool for modeling, analysis, design, optimization, operation, and control of electrical power systems. These findings may be useful in conducting reliability assessments and correctly utilizing dispersed generation sources for future power system growth by power utilities and power producer companies. The proposed method was employed on the Iraqi distribution system (AL-Abasia distribution network (F10 feeder)). After adding three DG units to the distribution system, theer adding three DG units to the distribution system, the obtained simulation results showed a significant reduction in power losses, voltage levels, and reliability enhancement.

Reducing LMP and resolving the congestion of the lines based on placement and optimal size of DG in the power network using the GA-GSF algorithm

One of the important factors in the discussion of power transmission is filling the capacity of network lines, which limits the transmission of power and increases the locational marginal price (LMP) in the network. Today, one of the techniques for resolving congestion and reducing LMP is to install DG units in the network, taking into account two factors: place and optimal size of DG based on operating costs and network constraints, all of which depend on the awareness of the capacity of network lines. In this article, in the first step, using the GA-GSF algorithm, identifying the network's weaknesses such as the lines that have reached their maximum capacity, and then by considering three terms and two scenarios condition of the buses connected to the filled lines will be discussed and we review and extract the best places for installing DG on the network. Then, considering the cost of operating DG and applying it to the objective function of the problem, by positively denoting DG profit and reducing line congestion, the optimization problem is solved by GA-GSF algorithm, and finally, the algorithm output including place and optimal size of DG unit in the network is minimized by line congestion and LMP, and DG installation is economically justified. Finally, the proposed algorithm was tested on the IEEE 14-BUS network for seven different DG types, and the results were such that out of these seven DGs, three DGs were able to reduce the total capacity of the network lines to less than the full capacity of the lines and the price of LMP has been raised to the price of UMP, and the other four DGs have managed to lower the price of LMP compared to their cost function.

REVIEW ON OPTIMIZATION TECHNIQUES EMPLOYED IN DISTRIBUTION GENERATION

Distributed Generators are playing a vital role and had achieve lot of attention due to their greater impact on various distribution systems. This approach encourages small scale technologies to produce electricity to the need at consumer end by utilizing the renewable energy sources. Power quality and reliability of distributed power can be attained by proper placing of Distributed Generators at appropriate location. Optimization tools were predominantly increasing their importance in integration of distributed generation. This paper proposes various reviews on recent optimization techniques being used over the years to the problem solving and sizing of DG units. In contrast this paper analyses the economical, technological, environmental etc., which are rapidly growing interest on integration of distributed generation by overcoming all the challenges. At last it presents several optimization techniques of the integration of distribution generation from renewable energy sources.

Optimal Placement of Distribution Generation to Minimize Losses using Backward Forward Sweep Method in Distribution System

Nowadays, there is a large interest in the penetration of Distribution Generation Units in the Utility System. This penetration of Distribution Generation requires proper planning for the system while considering DG impact on the Distribution System. It requires attention towards DG location which place in the system and size of DG units. The proper location of DG should also be considered to reduce losses in the utility System. This Paper Proposes finding optimal site and size of DG in Distribution Systems and it is tested in IEEE 33 bus system. The loss reduction after placing DG is shown in the results.

Energy Management of Virtual Power Plant Considering Distributed Generation Sizing and Pricing

The energy management of virtual power plants faces some fundamental challenges that make it complicated compared to conventional power plants, such as uncertainty in production, consumption, energy price, and availability of network components. Continuous monitoring and scaling of network gain status, using smart grids provides valuable instantaneous information about network conditions such as production, consumption, power lines, and network availability. Therefore, by creating a bidirectional communication between the energy management system and the grid users such as producers or energy applicants, it will afford a suitable platform to develop more efficient vector of the virtual power plant. The paper is treated with optimal sizing of DG units and the price of their electricity sales to achieve security issues and other technical considerations in the system. The ultimate goal in this study to determine the active demand power required to increase system loading capability and to withstand disturbances. The effect of different types of DG units in simulations is considered and then the efficiency of each equipment such as converters, wind turbines, electrolyzers, etc., is achieved to minimize the total operation cost and losses, improve voltage profiles, and address other security issues and reliability. The simulations are done in three cases and compared with HOMER software to validate the ability of proposed model.

OPTIMAL DISTRIBUTED GENERATION PLACEMENT AND SIZING TO REDUCE ACTIVE POWER LOSS USING GA AND ACO ALGORITHM

In this paper, Genetic Algorithm (GA) and Ant colony Algorithm (ACO) optimization techniquesare proposed to find optimal sizing and location for distributed generation in electrical networks.The objective function of the work relies upon a linearized model to compute the active powerlosses as a function of power generators. This strategy based on a strong coupling between activepower and power flow taking into consideration the voltage angles. With the end goal to exhibitthe adequacy of the proposed method, the proposed strategy is applied on IEEE 30-bus standardsystems. Different maximum penetration level capacity of DG units with three ranges such as,10%, 20% and 30% of maximum power load and various possible places of DG units amongseveral types of DG (active, reactive or active and reactive power) are considered. Results showthat the optimization tools employing GA and ACO are effective in reducing active power lossesand cost loss by finding the optimal placement and sizing of DG units.

Optimal sizing and siting of renewable energy resources in distribution systems considering time varying electrical/heating/cooling loads using PSO algorithm

ABSTRACTDistributed Generation (DG) sources based on Renewable Energy (RE) can be the fastest growing power resources in distribution systems due to their environmental friendliness and also the limited sources of fossil fuels. In general, the optimal location and size of DG units have profoundly impacted on the system losses in a distribution network. In the present article, the Particle Swarm Optimization (PSO) algorithm is employed to find the optimal location and size of DG units in a distribution system. The optimal location and size of DG units are determined on the basis of a multi-objective strategy as follows: (i) the minimization of network power losses, (ii) the minimization of the total costs of Distributed Energy Resources (DERs), (iii) the improvement of voltage stability, and (iv) the minimization of greenhouse gas emissions. The related distribution system was assumed to be composed of the fuel cells, wind turbines, photovoltaic arrays, and battery storages. The electrical, cooling, and heating loads were also considered in this article. The heating and cooling requirements of the system consist of time varying water heating load, space heating load, and space cooling load. In this study, the waste and fuel cell were used to produce the required heating and cooling loads in the distribution system. In addition, the absorption chiller was used to supply the required space cooling loads. A detailed performance analysis was carried out on 13 bus radial distribution system to demonstrate the effectiveness of the proposed methodology.

Power Loss Minimization in Radial Distribution Networks Using Reconfiguration and DGs

A novel approach is proposed in this paper to achieve the objective of real power loss minimization and voltage profile enhancement. Network reconfiguration and allocation of various DG units are used to meet the objective. Selective particle swarm Optimization (SPSO) and novel analytical techniques are used to solve the problem of network reconfiguration and allocation of DG units simultaneously. A new constant, Power Voltage Sensitivity Constant (PVSC), has been proposed to solve the allocation problem. The formulated mathematical expression (PVSC) determines site and size of DG units. The level of DG penetration is considered in a range of 0–50% of total system load. A novel index is also proposed which incorporates level of DG penetration and % reduction in real power losses. Standard 69 bus system is used to validate the results obtained by proposed hybrid approaches. To show the efficacy and strength of the proposed hybrid approach, it has been compared with various techniques

Load variations impact on optimal DG placement problem concerning energy loss reduction

The Optimal Distributed Generation Placement problem (ODGP) towards energy loss minimization depends basically on the network's layout and its load composition. Under load variations, different load compositions result, for each one of them, is highly possible to come up with a different optimal solution regarding the optimal siting and sizing of DG units. This paper examines the impact of these variations in order to verify how optimal solution should adapt to any load composition. A Local Particle Swarm Optimization Variant algorithm is proposed as the solution algorithm and numerous load composition snapshots for the IEEE-33 bus system are examined. Moreover, a methodology is proposed in order to highlight the critical nodes that prove to have an essential role to the solution. Finally, the possibility for the determination of a fixed solution with fixed installation nodes and constant power output that could yield near optimal energy loss reduction is examined.

Integrated approach of network reconfiguration with distributed generation and shunt capacitors placement for power loss minimization in radial distribution networks

This article presents the significance of efficient hybrid heuristic search algorithm(HS-PABC) based on Harmony search algorithm (HSA) and particle artificial bee colony algorithm (PABC) in the context of performance enhancement of distribution network through simultaneous network reconfiguration along with optimal allocation and sizing of distributed generators and shunt capacitors. The premature and slow convergence over multi model fitness landscape is the main limitation in standard HSA. In the proposed hybrid algorithm the harmony memory vector of HSA is intelligently enhanced through PABC algorithm during the optimization process to reach the optimal solution within the search space. In hybrid approach, the exploration ability of HSA and the exploitation ability of PABC algorithm are integrated to blend the potency of both algorithms. The box plot and Wilcoxon rank sum tests are used to show the quality of the solution obtained by hybrid HS-PABC with respect to HSA.The computational results prove the integrated approach of the network reconfiguration problem along with optimal placement and sizing of DG units and shunt capacitors as an efficient approach with respect to power loss reduction and voltage profile enhancement. The results obtained on 69 and 118 node network by hybrid HS-PABC method and the standard HSA reveals the effeciency of the proposed approach which guarantees to achieve global optimal solution with less iteration.

Optimal allocation and sizing of DG units considering voltage stability, losses and load variations

Abstract This paper proposes a new index to determine the optimal size and location of DG units, in order to minimize active power losses and enhance voltage stability margin considering load variations. A modified form of Imperialistic Competitive Algorithm (ICA) method is used to solve the optimization problem. To provide a comprehensive perspective for network scheduling, the load variations are considered. The load linear changes are from 50% to 150% of the base load (in 1% steps). At each step, the optimal size and location of the DG unit are determined and then, general expressions for DG sizes as a function of load level are concluded through curve fitting technique. These general expressions can be used as a suitable tool for network planning. The proposed method is applied to 34-bus and 69-bus test systems and the results are compared with the results obtained from cuckoo search algorithm in order to validate the proposed methodology.

Analytical Approach for Loss Minimization in Distribution Systems by Optimum Placement and Sizing of Distributed Generation

Distributed Generation has drawn the attention of industrialists and researchers for quite a time now due to the advantages it brings loads. In addition to cost-effective and environmentally friendly, but also brings higher reliability coefficient power system. The DG unit is placed close to the load, rather than increasing the capacity of main generator. This methodology brings many benefits, but has to address some of the challenges. The main is to find the optimal location and size of DG units between them. The purpose of this paper is distributed generation by adding an additional means to reduce losses on the line. This paper attempts to optimize the technology to solve the problem of optimal location and size through the development of multi-objective particle swarm. The problem has been reduced to a mathematical optimization problem by developing a fitness function considering losses and voltage distribution line. Fitness function by using the optimal value of the size and location of this algorithm was found to be minimized. IEEE-14 bus system is being considered, in order to test the proposed algorithm and the results show improved performance in terms of accuracy and convergence rate.

Optimal Access Point and Capacity of Distributed Generators in Radial Distribution Systems for Loss Minimization Including Load Models

ABSTRACTDistributed generation (DG) sources are predicated to play major role in distribution systems due to the demand growth for electrical energy. Location and sizing of DG sources found to be important on the system losses and voltage stability in a distribution network. This article proposes, an approach to determine the optimal sizing of multiple distributed generators in radial distribution system at unspecified power factor considering different load models. It is shown that load models can significantly affect the optimal sizing of DG units in radial distribution systems. The prior objective is to minimize network power losses hence to improve the voltage profile. Various optimization techniques are applied on the objective function. A detailed performance analysis is carried out on 38-bus radial distribution systems to demonstrate the effectiveness of the proposed techniques. Performing multiple power flow analysis on 38-bus system, the effect of DG sources on the most sensitive buses to voltage...