Different Types Of Distributed Generation Units Research Articles

Oppositional based artificial rabbits optimization applied for optimal allocation of nonlinear DG in distribution networks considering total harmonic distortion limit

This paper proposes a new optimization approach to identify the optimal placement and sizes of distributed generation (DG) units in a radial distribution network (RDN). Inverter-based DG also known as nonlinear DG (NLDG) units inject nonlinear current into the system, which can cause harmonic distortion. This harmonic distortion can limit the penetration of DG in the system by affecting the stability and reliability of the power system. Therefore, it is essential to consider harmonic distortion when identifying the optimal placement and sizes of DG units in RDNs to ensure DG’s safe and effective integration into the power system. The aim of the proposed work is to minimize real power loss, voltage deviation (VD), and total harmonic distortion limit (THD), and improve the voltage stability index (VSI) by integrating the search strategies of opposition-based learning and artificial rabbits optimization (ARO) to achieve better performance. The proposed algorithm, called opposition-based artificial rabbits optimization (OARO), considers different types of DG units like DG TYPE I and DG TYPE III and is suggested for two familiar RDNs: IEEE 33-bus, and 118-bus systems. The Pareto optimality concept has been introduced to solve the multi-objective problems of the systems. The simulation outcomes have been analyzed by comparing several optimization techniques in various cases. OARO has been shown to produce high-quality results with minimal iterations, reducing the time needed to solve the issue and conserving energy. Overall, the proposed approach offers a promising solution for identifying DG units’ optimal placement and sizes in RDNs while considering various operating scenarios.

An improved hybrid approach for the simultaneous allocation of distributed generators and time varying loads in distribution systems

Distributed Generation (DG) studies are generally conducted considering a single type of DG units integrated with the Distribution System (DS). However, these studies may not evaluate optimum benefits offered by the DG integration. This paper presents a novel framework for individual and simultaneous allocation of different types of DG units in DS while considering varying load demand and probabilistic generation of DG units. A Salp Swarm Algorithm (SSA) and Particle Swarm Optimization (PSO) based new hybrid method that utilizes a single controlling parameter is proposed for simultaneous allocation of DG units, aiming to minimize a multi-objective index. The strength of the proposed SSA-PSO hybrid approach is validated on seventeen benchmark functions and the performance of the novel framework for optimal allocation of DG units is validated through implementation on the 69-bus system. The results demonstrate that the proposed hybrid approach performs better as compared to other meta-heuristics techniques. Moreover, simultaneous allocation significantly reduces the multi-objective index as compared to individual DG units’ integration.

Optimal Planning of Electric Vehicle Charging Station along with Multiple Distributed Generator Units

Saving energy through the minimization of power losses in a distribution system is a key activity for efficient operation. Distributed Generation (DG) is one of the most efficient approaches to minimize losses. With increase in installation of Electric Vehicle Charging Stations (EVCSs) for Electrical Vehicles (EVs) in larger scale, optimal planning of EVCSs becomes a major challenge for distribution system operator. With increased EV load penetration in the electricity system, generation-demand mismatch and power losses increases. This results in poor voltage level, and deterioration in voltage stability margin. To mitigate the adverse impacts of increasing EV load penetration on Radial Distribution Systems (RDS), it is essential to integrate EVCSs at appropriate locations. The EVs integration into smart distribution systems involves Grid-to-Vehicle (G2V) and Vehicle-to-Grid (V2G) in charging and discharging modes of operation respectively for exchange of power with the grid thus resulting in energy management. The inappropriate planning of EVCSs causes a negative impact on the distribution system such as voltage deviation and an increase in power losses. In order to minimize this, DG units are integrated with EVCSs. The DGs assist in keeping the voltage profile within limitations, resulting in reduced power flows and losses, thereby enhancing power quality and reliability. Therefore, the DGs should be optimally allocated and sized along with the EVCS to avoid problems such as protection, voltage rise, and reverse power flow problems. This paper showcases a method to minimize losses using optimal location and sizing of multiple DGs and EVCS operating in G2V and V2G modes. The sizing and location of different types of DG units including renewables and non-renewables along with EV charging station is proposed in this study. This methodology overall reduces the power losses and also improves voltages of the network. The implementation is done by using the Simultaneous Particle Swarm Optimization technique (PSO) for IEEE 15, 33, 69 and 85 bus systems. The results indicate that the proposed optimization technique improves efficiency and performance of the system by optimal planning and operation of both DGs and EVs.

Combined Firm and Renewable Distributed Generation and Reactive Power Planning

The benefits of integrating Distributed Generation (DG) into the distribution networks depend on the characteristics of different types of DG units, loads and Reactive Power Sources (RPS). These benefits can be optimized if the firm DG units such as biomass energy and renewable DG units such as photovoltaic (PV) and wind system are optimally sized, located and coordinated with reactive power sources. In this paper, by assuming that the Distribution System Operator (DSO) has got the ownership and operation of DG units and RPS, a new planning strategy is proposed for determining the optimal placement and rating of DG units and RPS. This strategy overcomes the challenge of intermittency of renewable production in order that this planning will assist the system operators in defining the better integration strategies of firm and intermittent energy systems and reactive power sources in distribution networks. The proposed planning is based on single objective optimization so that it optimizes one of the following objective functions every time: the system energy losses, voltage stability margin, self-adequacy of microgrids defined on the distribution system and exchange of active and reactive powers between the distribution system and upstream network. The proposed technique accounts for the uncertainties associated with solar irradiance, wind speed and demand through a probabilistic optimization. The formulation of each planning problem is presented and applied to the 69-bus distribution system. The results of different planning strategies are compared and analyzed. Furthermore, the impact of the planning with each objective function on other indices is evaluated.

Optimal Allocation of Distributed Generation Considering Protection

The integration of distributed generation (DG) into the power grid has increased in recent years due to its techno-economic benefits for utilities and consumers. However, due to the fact that distribution systems were not originally designed to accommodate such DG units, many challenges are being faced by utilities to seamlessly integrate them into their systems. One of the critical challenges is their effect on protection system settings and coordination. The DG units will affect the pickup current settings of the protection relays, coordination between the primary and secondary relays, and even the direction of the fault current. Failing to consider DG’s effect on the protection system may lead to serious equipment damage or system failure, causing huge financial setbacks for utilities. To that end, this work proposes a new dynamic approach to optimally allocate different types of DG units over the planning horizon. The objective is to minimize the overall costs of the system while taking into consideration the intermittent nature of renewable DG and the impacts on the protection system. Simulation results have been developed on a typical distribution system to prove the effectiveness of the proposed approach.

Optimal DG Deployment Based on Technical and Economic Considerations with Daily Load Variation

The concept of distributed generation (DG) has been developed as a hopeful solution to meet the demand increase in distribution systems. The optimal DG deployment in the distribution system can improve the technical benefits. This study presents a framework to find the optimum location and size for different types of DG units to enhance the voltage stability index (VSI), improve the voltage regulation and reduce the daily energy losses. The emission effect and cost function (environment and economic benefits) are augmented in the multi-objective function. Combinations of DG types are introduced to obtain the best benefits from each one. The daily load variations and dynamic output of each DG type are considered in the problem formulation. The genetic algorithm (GA) technique is used to find the optimal allocation for different cases. The typical IEEE 33-bus system is utilized to evaluate the proposed framework.

Analytical and particle swarm optimization algorithms for optimal allocation of four different distributed generation types in radial distribution networks

In this paper, two algorithms, analytical and particle swarm optimization (PSO), are introduced and compared with each other for optimal allocation of distributed generation (DG) units in radial distribution networks (RDNs) to minimize the total loss in real power. Four different types of DG units are considered in this work. The two algorithms make use of a backward / forward load flow method for the load flow analysis of the RDN by which the node voltages and the total active power loss of the network are determined. The introduced algorithms are tested on the IEEE 41 bus radial distribution system and the results are obtained using MATLAB. Discussions are provided based on the results of case studies

Ant Lion optimization algorithm for optimal sizing of renewable energy resources for loss reduction in distribution systems

This paper mainly focused on the impact of distributed generation (DG) placement on distribution system. The integration of DG is transforming the traditional radial distribution system into a multi-source system. Distributed generation is a term that refers to the production of electricity near the consumption place. The effects of distributed generation are short circuit levels are increased, load losses change, reliability change and voltage profiles change along the network. The above advantages can be accomplished by ideal position and sizing of DG units. The ideal positions are obtained from index vector method. Ant Lion Optimization (ALO), a novel meta heuristic algorithm is used to determine the optimal DG size. ALO is modeled based on the unique hunting behavior of ant lions. The ALO algorithm is evaluated on IEEE 15, 33, 69 and 85-bus test systems. ALO algorithm was compared with different types of DG units and other evolutionary algorithms. When compared with other algorithms the ALO algorithm gives better results. From the analysis best results have been achieved from type III DG operating at 0.9pf.

Optimal dispatchable DG allocation in a distribution network considering load growth with a mixed-PSO algorithm

In recent years, one of the major issues faced by distribution utilities is integrating distributed generation (DG) units in distribution networks. This paper proposes a population-based method called particle swarm optimization (PSO) for optimal planning of the location and sizing of different types of DG units in the distribution network, considering different loading conditions. The objective of this application is power loss minimization. In order tond the optimal location and size of DG units, continuous and discrete forms of PSO are deployed, respectively (mixed PSO). In addition, the optimal locations and sizes of the DG units are determined in the areas of signicant feeder load growth. This meta- heuristic approach makes little or no assumption about the issue being optimized and can search large spaces of possible solutions. The presented method is tested on the standard IEEE 33-bus and IEEE 69-bus test systems. In order to show the effectiveness of the proposed methodology, the results are compared with another method of DG allocation and another loss minimization technique.

To Study the Adequacy Assessment of Chitradurga distribution substation using MCS

Power system has dynamic behavior as it faces various disturbances like sudden variation in load, sudden variation in generation and different faults. Due to the variation of load demand, the operation, maintenance and control of power system have become a challenging task. To meet the load requirements, many noticeable research activities are going on in the field of deregulation, restructuring of power system, utilization of renewable energy sources and installing small generators at the load centre referred to as Distributed Generation (DG) etc. Furthermore, among many different types of DG units, renewable DG units are widely accepted. In this paper, adequacy evaluation of the 220kV distribution system with DG has been proposed. This concept deals with installation of additional capacity with the existing capacity for supplying load, which is provided by renewable DG units. Reliability index such as average unsupplied load (AUL) is calculated using Monte Carlo simulation (MCS).

Study on the Impact of Distributed Generation on Distribution Power Losses

The impact of distributed generation (DG) on distribution power losses is closely related to DG technologies and load distribution. DG units are modeled as PQ, PQ(V) and PV nodes in power flow calculation. A revised back/forward power flow method is employed to calculate distribution power flow with various types of DG units. Power losses are computed when different types of DG units are connected to heavy load, general load and light load area apart. Simulation on IEEE 33-bus distribution network shows that connecting DG to heavy load area helps to maximize the loss reduction. And the installation of DG consuming reactive power will increase network losses unless reactive power compensation device is installed accordingly.

Experimental validation of a real-time energy management system using multi-period gravitational search algorithm for microgrids in islanded mode

Both performance optimization and scheduling of the distributed generation (DG) are relevant implementing an energy management system (EMS) within Microgrid (MG). Furthermore, optimization methods need to be applied to achieve maximum efficiency, improve economic dispatch as well as acquiring the best performance. This paper proposes an optimization method based on gravitational search algorithm to solve such problem in a MG including different types of DG units with particular attention to the technical constraints. This algorithm includes the implementation of some variation in load consumption model considering accessibility to the energy storage (ES) and demand response (DR). The proposed method is validated experimentally. Obtained results show the improved performance of the proposed algorithm in the isolated MG, in comparison with conventional EMS. Moreover, this algorithm which is feasible from computational viewpoint, has many advantages as peak consumption reduction, electricity generation cost minimization among other.

A combined practical approach for distribution system loss reduction

This paper investigates the loss reduction potential of primary distribution systems with distributed generation (DG) units, capacitors and network reconfiguration. A methodology is proposed to combine different types of DG units and capacitors for minimising losses. A combination of reconfiguration, DG and capacitor placement to obtain high loss reduction is also presented. The results obtained on a 33-bus test distribution system with constant load condition and a 687-bus real distribution system with varying load conditions show significant loss reduction using the proposed approach. The combination of type 1 DG (i.e. DG capable of delivering real power only) and capacitor placement or reconfiguration with type 1 DG and capacitor placement can be viable for minimising losses.

Long term scheduling for optimal allocation and sizing of DG unit considering load variations and DG type

This paper proposes a new long term scheduling for optimal allocation and sizing of different types of Distributed Generation (DG) units in the distribution networks in order to minimize power losses. The optimization process is implemented by continuously changing the load of the system in the planning time horizon. In order to make the analysis more practical, the loads are linearly changed in small steps of 1% from 50% to 150% of the actual value. In each load step, the optimal size and location for different types of DG units are evaluated. The proposed approach will help the distribution network operators (DNOs) to have a long term planning for the optimal management of DG units and reach the maximum efficiency. On the other hand, since the optimization process is implemented for the entire time period, the short term scheduling is also possible. The proposed method is applied to IEEE 33-bus test system using both the analytical approach and particle swarm optimization (PSO) algorithm. The simulation results show the effectiveness and acceptable performance of the proposed method.

Optimal planning of dispatchable and non-dispatchable distributed generation units for minimizing distribution system's energy loss using particle swarm optimization

Distribution Companies (DisCos) play a pivotal role in developing new planning strategies for maintaining the proper operation and efficiency of distribution networks. Moreover, power system deregulation, demand increasing, shortage of transmission capacities and interests in renewable sources have led to the increased studies on integration of distributed generation (DG) into the distribution systems. Hence, proper planning of DG units is important for obtaining their maximum potential benefits from the perspective of DisCos. This paper aims to present a new DG planning model. This new model would help planners to find optimal planning of different types of DG units, dispatchable or non-dispatchable, in distribution systems for minimizing system's annual energy loss. The planning problem is formulated to determine the optimal hourly production profile, power factor and penetration of DG units. A particle swarm optimization algorithm, implemented in MATLAB software, is used for finding the optimal solution of planning problem. The proposed approach has been evaluated on 69-Bus Test System in matpower 4.0, with different scenarios in view of DG units' combination. The results show that a significant reduction in energy loss is achieved and the constraints including voltage limits and the feeders' capacity are satisfied. Copyright © 2012 John Wiley & Sons, Ltd.

Influence of converter - connected distributed generation on distribution network losses

Distributed generation (DG) is predicted to play an increasing role in the electric power system of the near future. There are different types of DG units from the constructional and technological points of view, which have a different influence on the distribution network. The impact of DG on the network is considered, with a more extensive discussion on the influence of DG on the network losses. The calculation of these network losses is applied in several optimisation programs to quantify an optimal size and location of the DG unit. In these programs the power quality can be taken into account but harmonic losses are rarely considered, although it is known that several DG topolo- gies can have a negative influence on the total harmonic distor- tion and thus on the harmonic losses. Therefore, this paper will investigate the influence of converter-connected DG units on fun- damental and harmonic losses in the distribution network.