Optimal Allocation Of Distributed Generation Research Articles

Distributed Generation Effect on Distribution System

The idea about this proposed work, to know the Distributed Generation (DG) impact on distribution scheme. This is to improve the performance of the system using power loss reduction and voltage development. In this proposed work Wind Turbine (WT) and Photo-Voltaic (PV) units were taken for DGs and various algorithms are tested to get the effect of DG on network. In this paper one new hybrid algorithm is proposed to have optimal size and location of various types of DGs. Initially, active and reactive power losses of the test system and voltage at every bus of the test system were examined using Back and Forward (B/FW) Sweep technique. Similarly, Gravitational Search Analysis (GSA), BAT Analysis (BA) and Ant Lion Optimization (ALO) techniques were utilized to examine the parameters of the same test system. Finally, all the constraints were compared with projected hybrid approach. All the algorithms have tested on IEEE-33 and IEEE-69 standard test systems. Furthermore, the MATLAB simulation is used to get the optimal allocation of DGs.

Index-based optimal DG allocation for voltage quality improvement in an unbalanced network

Voltage quality is a one of the major concerns in distribution systems. Distributed Generations (DGs) have the potential to improve voltage quality, if optimally planned and operated. Considering the problem of DG siting and sizing, this paper aims at integrating technical factors, particularly voltage quality, in planning of DGs. Hence, a methodology is proposed which optimizes voltage quality in the presence of DGs and can be used as one of the objectives in a multi-objective problem or as an intermediate stage in usual DG planning. Modified voltage quality indices are proposed which consider factors including voltage profile, voltage variation due to DG disconnection, voltage regulation and voltage unbalance. The indices are defined in such a manner suitable for three-phase unbalanced networks. The system voltage quality is assessed by a new comprehensive voltage quality index. By applying this index, the DGs locating and penetration problem is formulated to improve system voltage quality. The method is tested on IEEE 13-bus feeder which is an inherently unbalanced network.

Index-based optimal DG allocation for voltage quality improvement in an unbalanced network

Index-based optimal DG allocation for voltage quality improvement in an unbalanced network

Optimal Allocation of DG and D-STATCOM in a Distribution System using Evolutionary based Bat Algorithm

In this work, a methodology to find the optimal allocation (i.e., sizing and location) of Distributed Generators (DGs) and Distribution-static compensators (D-STATCOM) in a radial distribution system (RDS) is proposed. Here, the voltage stability index (VSI) is utilized to find the optimal location for the D-STATCOM, and loss sensitivity factor (LSF) method is utilized to find the optimal location for distributed generation. In this work, the proposed work is formulated as a non-linear optimization problem and it is solved using the meta-heuristic/evolutionary-based algorithm. The evolutionary-based Bat algorithm is used to find optimal sizes of D-STATCOM and DGs in RDSs. To check the validity and feasibility and validity of the proposed optimal allocation approach, two standard IEEE 34 and 85 bus RDSs are considered in this paper. The simulation results show reduction in power losses and enhancement in bus voltages in the RDSs.

Optimal DG Allocation in Unbalanced Radial Distribution Systems Using Improved Grey Wolf Optimizer

Optimal DG Allocation in Unbalanced Radial Distribution Systems Using Improved Grey Wolf Optimizer

Optimal allocation of renewable distributed generators and shunt capacitors in distribution system using hybrid intelligent approach

Increased utilisation of naturally available energy sources in a distribution system (DS) is customary in recent years. These RES are intermittent in nature and impact the system performance significantly. In this paper, a methodology is utilised for bidding the lowest price to the consumer based on the availability of RES. A physical communication infrastructure between the utility and user is enabled to coordinate between the RES dominant utility and consumers. The main objectives of this communication enabled user utility interface system are to minimise power loss and enhance the voltage profile simultaneously. A multi-objective approach considering active power loss index (ALPI), voltage deviation index (VDI), and voltage stability index (VSI) are presented to solve the renewable distributed generation (RDG) and shunt capacitors (SCs) allocation problem. A combination of sensitivity analysis and random walk moth flame optimisation (RWMFO) is utilised for solving the aforementioned multi-objective function. IEEE 33 and 69 bus test systems are taken for analysis. Finally, the implemented method is compared with recent techniques available in the literature.

Optimal allocation of renewable distributed generators and shunt capacitors in distribution system using hybrid intelligent approach

Optimal allocation of renewable distributed generators and shunt capacitors in distribution system using hybrid intelligent approach

Meta-heuristic optimization methods applied to renewable distributed generation planning: A review

Due to its proven efficiency and computational speed, the most recent developed meta-heuristic optimization methods are widely used to better integrate renewable distributed generation (RDG) into the electricity grid. The main objective of this paper is to obtain a better knowledge of current trends in meta-heuristics applied to optimally integrate RDGs to the distribution network. This is a review of well known meta-heuristic approaches, used to solve the problem of optimal renewable distributed generation allocation planning (ORDGAP). In this context, some research gaps were mentioned, and recommendations were proposed to expand the scope of research in this field.

Оптимизация расположения и мощности возобновляемых распределенных источников энергии с использованием модифицированного метода роя частиц

The penetration of renewable distributed generations (RDGs) such as wind and solar energy into conventional power systems provides many technical and environmental benefits. These benefits include enhancing power system reliability, providing a clean solution to rapidly increasing load demands, reducing power losses, and improving the voltage profile. However, installing these distributed generation (DG) units can cause negative effects if their size and location are not properly determined. Therefore, the optimal location and size of these distributed generations may be obtained to avoid these negative effects. Several conventional and artificial algorithms have been used to find the location and size of RDGs in power systems. Particle swarm optimization (PSO) is one of the most important and widely used techniques. In this paper, a new variant of particle swarm algorithm with nonlinear time varying acceleration coefficients (PSO-NTVAC) is proposed to determine the optimal location and size of multiple DG units for meshed and radial networks. The main objective is to minimize the total active power losses of the system, while satisfying several operating constraints. The proposed methodology was tested using IEEE 14-bus, 30-bus, 57-bus, 33-bus, and 69- bus systems with the change in the number of DG units from 1 to 4 DG units. The result proves that the proposed PSO-NTVAC is more efficient to solve the optimal multiple DGs allocation with minimum power loss and a high convergence rate.

Atom Search Optimization Algorithm for Allocating Distributed Generators in Radial Distribution Systems

In recent years the use of renewable energy sources (RES) by many power grid companies worldwide has increased significantly. The trend towards RES use is mainly due to environmental issues and rising fuel prices associated with conventional electricity generation. This paper introduces a hybrid approach to find the optimal location and size of distributed generations (DG) in the radial distribution system (RDS). The proposed approach is based on the atom search optimization (ASO) technique to calculate the optimal allocation of DGs and power loss sensitivity (PLS) index to obtain the best buses for DGs installation in RDS. The presented approach is applied to IEEE 33-bus RDS to increase voltage profile and minimize the power losses. The results obtained prove that the developed approach can be highly effective in integrating DG into RDS compared to many other methods in the literature.

Multi-Objective Coordinated Optimal Allocation of DG and EVCSs Based on the V2G Mode

With the vigorous promotion of new energy sources and the development of vehicle-to-grid (V2G) technology, the influence of the V2G mode should be considered in the joint optimal allocation of Distributed Generation (DG) and electric vehicle charging stations (EVCSs). The timing characteristics of the intermittent output of DG, conventional demand for load, and charging load of the electric vehicle (EV) are considered, as is its participation in grid interaction to examine the construction of typical scenarios and the EV cluster dispatching strategy. From the perspective of comprehensively planning the coordination of the distribution network, a DG-EVCSs bi-level joint planning model is established under the peak and valley price mechanism, with the sub-objectives of obtaining a comprehensive profit and high quality of voltage, curbing system load fluctuations, and satisfactorily charging the EV. An improved harmony particle swarm optimization algorithm is proposed to solve the bi-level model. The proposed method was tested on the IEEE-33 and the PG&E-69 (Pacific Gas and Electric Company) bus distribution systems, and the results show that the optimized configuration model that considers the V2G mode can improve the overall performance of the planning scheme, promote the use of clean energy, smoothen the load fluctuations of the system, and improve the quality of voltage and charging satisfaction of EV users.

Power losses reduction of power transmission network using optimal location of low-level generation

Due to the growth of demand for electric power, electric power loss reduction takes great attention for the power utility. In this paper, a low-level generation or Distributed Generation (DG) has been used for transmission power losses reduction. Karbala city transmission network (which is the case study) has been represented by using MATLAB m-file to study the load flow and the power loss for it. The paper proposed the Particle Swarm Optimization (PSO) technique in order to find the optimal number and allocation of DG with the objective to decrease power losses as possible. The results show the effect of the optimal allocation of DG on power loss reduction.

Equilibrium optimization algorithm for network reconfiguration and distributed generation allocation in power systems

It is imperative to distribution system operators to provide quantitative as well as qualitative power demand and satisfy consumers’ satisfaction. So, it is important to address one of the most promising combinatorial optimization problems for the optimal integration of power distribution network reconfiguration (PDNR) with distributed generations (DGs). In this regard, this paper proposes an improved equilibrium optimization algorithm (IEOA) combined with a proposed recycling strategy for configuring the power distribution networks with optimal allocation of multiple distributed generators. The recycling strategy is augmented to explore the solution space more effectively during iterations. The effectiveness of the proposed algorithm is checked on 23 standard benchmark functions. Simultaneous integration of PDNR and DG are carried out considering the 33 and 69-bus distribution test systems at three different load levels and its superiority is established. Verification of the proposed technique on large scale distribution system with a variety of control variables is introduced on a 137-bus large scale distribution system. These simulations lead to enhanced distribution system performance, quality and reliability. While, the integration represents a challenge for complexity and disability to achieve optimal solutions of the considered problem especially for multi-objective framework. To solve this challenge, a multi-objective function is developed considering total active power loss and overall voltage enhancement with respecting the system limitations. The proposed algorithm is contrasted with harmony search, genetic, refined genetic, fireworks, and firefly optimization algorithms. The obtained results confirm the effectiveness and robustness of the proposed technique compared with the competitive algorithms.

Optimal network reconfiguration and DG allocation using adaptive modified whale optimization algorithm considering probabilistic load flow

The optimal DG allocation (ODGA) and network reconfiguration (NR) are significant tools to improve voltage stability and minimize power losses in a distribution network. In a real power distribution network loads are random variables, thus ODGA and NR processes are incorporated using a probabilistic load flow (PLF). The reactive power capability of DGs has a significant impact on the network parameters which can be studied using PLF. In the present work, an ODGA and NR processes have been incorporated to improve the voltage stability and loss profile of the distribution system considering probabilistic loads and DGs which are operated at varying pfs. The optimization problem has been solved using an adaptive modified whale optimization algorithm (A-MWOA). A novel technique based on depth first search algorithm has been employed to check radiality constraints. The effectiveness of proposed technique has been tested on two standard distribution networks.

Performance Assessment of Pareto and Non-Pareto Approaches for the Optimal Allocation of DG and DSTATCOM in the Distribution System

Performance Assessment of Pareto and Non-Pareto Approaches for the Optimal Allocation of DG and DSTATCOM in the Distribution System

Ɛ‐constraint multiobjective approach for optimal network reconfiguration and optimal allocation of DGs in radial distribution systems using the butterfly optimizer

In recent days, the optimal allocation of distributed generators (DGs) problem in the distribution system caught several reader's attention to improve the system efficiency, to meet the future load growth. In this article, a multiobjective approach is proposed to determine the optimal locations for DGs, optimal DGs sizes, optimal power factors of DGs in the presence of optimal network reconfiguration to maximize the maximum loadability (λmax), minimize the active power loss and maximize the loading margin factor (λv) of the system. Butterfly Optimization (BO) algorithm is implemented to optimize the desired objectives. The Ɛ-constraint method is used for multiobjective optimization, spanning tree technique is used for checking the radiality of the system and modified repetitive power flow using radial load flow algorithm is developed for finding theλmax, λv.The proposed approach is tested on 33 bus and 69 bus radial distribution test systems. Four scenarios are considered to achieve the desired objectives and each scenario consists of two cases: optimal allocation of DGs in the initial configured network, optimal allocation of DGs in the optimal reconfigured network. Results suggest that optimal allocation of DGs in scenario 4 gives a better improvement in maximum system loadability, loading margin factor, and active power loss reduction of the system. Obtained results compared with the suitable methods and algorithms that are available in the literature.

Optimal distributed generation allocation in unbalanced radial distribution networks via empirical discrete metaheuristic and steepest descent method

Loss minimization and voltage improvement through distributed generation (DG) planning is a well-established problem. However, a careful review of the literature shows that there is still room for the development of efficient algorithms for this purpose. In special, hybridization between optimization techniques is suitable for this complex problem, as it allows taking advantage of the positive features of different approaches. In this work, a novel empirical discrete metaheuristic (EDM) is presented and merged with the steepest descent method to solve the DG allocation problem. The allocation is broken into two subproblems: sitting the DGs and sizing them. The EDM deals with the first subproblem, while the second one is solved by the steepest descent method in an interchangeable optimization structure. The EDM tackles some key limitations of metaheuristic family methods. Relatively, it shows: low results variability in different executions; low initial conditions dependency; and few number parameters to tune. All simulations are performed in a communication scheme using the softwares Matlab and OpenDSS. The obtained results with IEEE 34-bus and IEEE 123-bus distribution test systems were compared to the literature and other metaheuristics, attesting the quality of the proposed approach.

Distributed cooperative control algorithm for optimal power sharing for AC microgrids using Cournot game theory

Research on the optimal power allocation of large-scale distributed generator (DG) units based on user power generation to access microgrids (MGs) in a multi-agent system framework has recently become the focus of modern grid and energy concerns. In this paper, according to the Cournot oligopoly game, the Nash equilibrium point between the power generation company and power generation user of the MG operating in island mode is obtained. According to the obtained Nash equilibrium point, the optimal ratio of power generated by the power generation company and by the power generation user in the model is calculated. At the same time, to achieve the maximum benefit and stable operation of the MG, a distributed cooperative control algorithm based on consensus theory is proposed. This control algorithm can cause each DG to generate power according to the total consumption load. The optimal power generation ratio distribution based on the Nash equilibrium point eliminates the steady-state frequency deviation of each DG in the MG, thereby ensuring the user’s power quality. The simulation results show that the control algorithm can achieve the above research goals.

A novel severity performance index for optimal allocation and sizing of photovoltaic distributed generations

Optimal allocation and sizing of the distributed generations (DGs) attract great attention of many researchers all over the world. In this study, the problems associated to optimal DGs allocation and sizing are divided into two sub-problems. One of them deals with the DGs allocation at the critical buses and the other aims to select the optimal size of these DGs. A novel severity performance index (SPI) is introduced to evaluate both the power system reliability and quality. The crow search (CS) is integrated with PSO not only to collect the merits of both CS and PSO but also to solve the optimal power flow problem including multi-DGs allocated at the critical buses for the IEEE 30-bus test system. Detailed comparisons of four distinct DGs allocation cases are presented, discussed, and analyzed. The simulation findings proved that the DGs allocated based on the multi-objectives (SPI, total fuel costs; FC; and power losses; PL) have a superior performance compared to other cases in terms of voltage profile, branches loading, power losses, and total costs. Therefore, the multi DGs is preferred to be allocated based on these multi-objectives (SPI, FC, and PL) in order to attain additional techno-economic benefits to the power system.

Allocation of PV unit in Distribution Network using Analytical Method

Inappropriate selection of location and corresponding size of Distributed Generator (DGs) in electrical network may have increased power losses in the system. Application of incorporating DG in system has eased the problem of high power losses, voltage stability, low reliability and poor power quality. This paper suggests a simple and efficient load flow technique known as direct load flow method to find the optimal allocation of Type-3 DG in the distribution system. The presented method was developed and tested in two distribution networks with varying size and complexities and the effect of size and location of DG with respect to real power losses while maintaining the voltage profile of system within limits is examined with verification and discussed in detail.