Different Types Of Distributed Generation Research Articles

Enhancement of Active Distribution Network Performance with Multiple Distributed Generators and DSTATCOMs using Reptile Search Algorithm

The integration of multiple DGs can introduce power quality issues and instability in the (DN) due to their intermittent and fluctuating nature. Distributed Static Compensators (DSTATCOMs) are devices that effectively manage and regulate both active and reactive powers, thereby maintaining the desired levels of reactive power in the DNs. This paper investigates the problem of determining the optimal number and placement of multiple DSTATCOMs within active DNs with multiple Distributed Generators (DGs) connected to them. To achieve the optimal sizing and allocation of multiple DSTATCOMs, a novel heuristic method called the reptile search algorithm (RSA) is introduced in this study. A combination of the RSA method and the loss sensitivity factor (LSF) are utilized to identify the optimal number, sizes, and locations of DSTATCOMs to enhance the performance of active DNs with different types of DGs and loads. The desired improvements include mitigating voltage deviation at nodes, minimizing system power losses, and alleviating overloading in feeders. The effectiveness of the algorithm is evaluated using an IEEE-33 bus DN, which is modified to incorporate different DGs and load types. To assess the efficiency of the proposed method, a modified particle swarm optimization (MPSO) algorithm is used for comparison. The results demonstrate that the RSA approach presented in this paper is robust in obtaining optimal solutions, offers fast and easy implementation, can be applied to large DNs, and outperforms the MPSO algorithm.

Optimal placement and sizing of multiple distributed generators in power distribution networks

The primary objective of power systems is to meet the total power requirement, as well as to retain system reliability and security with the economic operation of the system. In recent years, exponential growth in power demand, lack of investments in up-gradation of electrical infrastructure, shortage in power generation and environmental concerns have been the key factors for unreliable and poor operation of the power systems. To tackle these problems, there is a need to rely on supplementary sources of generation and fortification of transmission capacity. Whereas, installation of large scale new generating units is not economical. An adequate number of small generating units incorporated is a more effective solution to meet the growing power demand. This research work focuses on the enhancement of voltage profiles while curtailing power loss by the optimal sizing and optimal placement of multiple distributed generators (DGs) at different buses. Different types of DG sizing and placement are carried out at 100%, 120% and 140% loading conditions.

Allocation of distributed generator in power networks through an enhanced jellyfish search algorithm

This study presents the Jellyfish Search Optimizer (JS), a novel metaheuristic optimization algorithm, for the efficient allocation of multi-type distributed generations (DGs) in distribution power systems. To further enhance the performance of the original JS algorithm, a leader-based mutation-selection approach called LJS is proposed to circumvent local optima. The effectiveness of LJS is evaluated with various benchmark problems and compared with other competitive optimization algorithms. Moreover, LJS is utilized to allocate different types of DGs (Type I, Type II, and Type III) in standard IEEE and practical Portuguese distribution systems. The optimization problem of the DG allocation is performed to minimize the power loss and enhance the voltage profile by minimizing the voltage deviation (VD) and maximizing the voltage stability index (VSI) as single- and multi-objectives optimization problems. The results obtained demonstrate the superior performance of LJS in achieving optimal solutions for benchmark problems as well as for the allocation of multi-type DGs. Notably, the integration of DG Type III leads to a remarkable reduction in total power loss, achieving a reduction of 94.44 %, 98.10 % and 96.07 in IEEE 33-bus,IEEE 69-bus and 94 bus systems, respectively.

Weighted Minkowski distance-based differential protection for active distribution networks considering the uncertainty of frequency-domain characteristics

With the increasing use of DGs (distributed generators) in the power system, the distribution network is becoming more and more complicated. The rapid change of DG output power and the diversity of DG location make the computing calculation of relay protection difficult, bringing severe challenges to the current protection based on single-end electrical volume. Therefore, double-end-based protection is a good choice in view of the DG uncertainty and the network complexity. However, the power frequency offset after fault and the uncertainty of DG fault current result in uncertainty in the frequency-domain characteristics, which can also negatively affect the differential protection. In view of this, a new differential protection method based on the weighted Minkowski distance algorithm is proposed in this paper. First, the Minkowski distance algorithm is used to describe the similarity of both currents considering the uncertainty in the frequency-domain characteristics. Second, each current similarity including the phase current, the positive current, and the negative current is calculated separately to increase the protection sensitivity. Through the weighted algorithm distribution, the weight is assigned. Furthermore, a high-performance protection mechanism is designed to improve the protection sensitivity. This method is suitable for the active distribution network with different penetration rates of DGs and different types of DGs. The simulations show that the proposed method has good feasibility and high superiority.

Effects of Integration of Multi Type DGs on Voltage stability and Loss Minimization in the Distribution System

In recent days in distribution system the more importance is giving to Loss minimization techniques since electricity demand is continuously increasing and utility companies are struggling to meet this rapid increase in load due constraints on energy resource to increase the generation. Furthermore, voltage instability phenomena is also playing important role in distribution systems and caused a major blackout in the network. To solve the above problem new technology that is drawing more attention is Distributed Generation (DG). Placing DG in the distribution system inherently reduces the power loss and improves the system voltage. The selection of type of DG, proper placement and sizing of DG plays an important role. This paper presents an effective methodology to identify the optimum location of multi type DG in the distribution system in order to reduce the losses and improve the voltage. In this work the IEEE 33-Bus system is simulated in Power World Simulator (PWS) and the voltage stability and system losses are analyzed with different types of DGs and combination of different types of DGs are studied. Simulation result shows that optimal placement and sizing of DG will reduce the system losses and improve the voltage profile within the acceptable limits and the loss reduction and voltage profile improvement are depending on the types of DGs and combination of DGs placed in the distribution system. Index Terms: Distributed generation, Optimum size, Optimum location, Power loss, Power world simulator, Sensitivity analysis, Types of DG, Voltage stability.

Optimal DG Placement in Power Systems Using a Modified Flower Pollination Algorithm

There is a huge requirement for power systems to reduce power losses. Adding distributed generators (DGs) is the most common approach to achieving lower power losses. However, several challenges arise, such as determining the ideal size as well as location of the utilized distributed generators. Most of the existing methods do not consider the variety of load types, the variety and size of the utilized DGs besides reducing the convergence time and enhancing the optimization results. The paper performed an optimization algorithm that integrated a golden search-based flower pollination algorithm and fitness-distance balance (FDB) to find out the optimal size as well as the location of the distributed generators. It was then compared with different optimization methods to determine the best optimization technique, and it was determined to be the best technique. In addition, different types of DGs are considered, including solar energy, wind energy, and biogas, along with optimizing the size of the utilized DGs to reduce the system cost. Testing with different types of bus systems, and different types of DGs in a radial distribution system was done to reveal that the modified flower pollination with golden section search was superior in comparison to others with regards to convergence and power loss reduction.

A Novel Hybrid Fuzzy-Metaheuristic Strategy for Estimation of Optimal Size and Location of the Distributed Generators

Optimal size and location of the distributed generators (DGs) has become a new avenue applied to achieve a proper design and to provide a better performance for the distribution system. A hybrid Fuzzy-Metaheuristic strategy has been proposed in this work to provide an optimal design for sizing and placement of different types of DGs. In the introduced strategy, the fuzzy logic based adaptive weights subroutine has been combined with a metaheuristic optimizer in conjunction with a power system model, load flow software, input/output software modules and three proposed approaches software modules suitable for various types of DGs. Minimizing active and reactive power losses as well as enhancing the voltage characteristics over the whole system using a multi objective function with dynamic adjustment of weights has been introduced in this work. Furthermore, a novel approach of variable power factor has been established and investigated as well as the previously published constant power factor and unity power factor approaches. To prove the validity of the new strategy and the novel approach, IEEE distribution systems of 33 and 66 buses have been used to test the efficiency and accuracy of the proposed strategy. A novel hybrid optimization strategy named Hybrid Fuzzy Equilibrium Optimizer (HFEO) is established to estimate the optimal size and location of three DGs inserted in the selected distribution systems. The hybrid technique is based on merging fuzzy logic to adapt the weights of the objective function dynamically with a newly developed metaheuristic Algorithm named equilibrium optimizer to achieve a better performance in the optimization process. For fair verification of the proposed technique, its results have been compared with that of five algorithms presented in literature to prove its superiority and reliability over the other state of art. For intensive comparisons, some statistical analysis has been established to show the minimum objective function, the highest speed of convergence, the least execution time and the most consistent results.

Optimal Sizing and Allocation of Distributed Generation in the Radial Power Distribution System Using Honey Badger Algorithm

There is increasing growth in load demands and financial strain to upgrade the present power distribution system. It faces challenges such as power losses, voltage deviations, lack of reliability and voltage instability. There is also a sense of responsibility in the wake of environmental and energy crises to adopt distributed renewable resources for power generation. These challenges can be resolved by optimally allocating distributed generators (DGs) at different suitable locations in the radial power distribution system. Optimal allocation is a non-linear problem which is solved by powerful metaheuristic optimization algorithms. In this work, an objective function is introduced to optimally size four different types of DGs by utilizing honey badger algorithm (HBA), and comparison is drawn with grey wolf optimization (GWO) and whale optimization algorithm (WOA). The objective is to boost the voltage profile and minimize the power losses of the standard IEEE 33bus and 69-bus radial power distribution system. It is observed from the simulation results that honey badger algorithm is faster than grey wolf optimization and whale optimization algorithm in reaching accurate and optimum results in a mere one and two iterations for IEEE 33-bus and 69-bus systems, respectively. Additionally, power losses are reduced to 71% and 70% for IEEE 33-bus and 69-bus, respectively.

A Novel Approach Based on Honey Badger Algorithm for Optimal Allocation of Multiple DG and Capacitor in Radial Distribution Networks Considering Power Loss Sensitivity

Recently, the integration of distributed generators (DGs) in radial distribution systems (RDS) has been widely evolving due to its sustainability and lack of pollution. This study presents an efficient optimization technique named the honey badger algorithm (HBA) for specifying the optimum size and location of capacitors and different types of DGs to minimize the total active power loss of the network. The Combined Power Loss Sensitivity (CPLS) factor is deployed with the HBA to accelerate the estimation process by specifying the candidate buses for optimal placement of DGs and capacitors in RDS. The performance of the optimization algorithm is demonstrated through the application to the IEEE 69-bus standard RDS with different scenarios: DG Type-I, DG Type-III, and capacitor banks (CBs). Furthermore, the effects of simultaneously integrating single and multiple DG Type-I with DG Type-III are illustrated. The results obtained revealed the effectiveness of the HBA for optimizing the size and location of single and multiple DGs and CBs with a considerable decline in the system’s real power losses. Additionally, the results have been compared with those obtained by other known algorithms.

A novel unbalanced power flow analysis in active AC-DC distribution networks considering PWM convertors and distributed generations

Recent major achievements in power electronic technologies have expedited the development and proliferation of small-scale distributed generations (DGs). AC-DC distribution network creates a novel paradigm to attain the utmost benefits through smoothing the operation of different types of DGs. However, due to the asymmetrical electrifying of single-phase loads with different consumptions, variations in output power of the small-scale DGs connected to each phase, and disparate line parameters of the network, operation under unbalanced condition is inevitable. Therefore, performing AC-DC load flow analysis considering an unbalanced condition is indispensable to estimate the system states. In this paper, a novel direct approach based on backward-forward sweep (BFS) algorithm is proposed for power flow analysis in AC-DC distribution networks that applies Clarke’s transformation to model the operation of pulse width modulation (PWM) converters at unbalanced operation condition. Different control strategies including input power control (IPC), input output power control (IOPC), and output power control (OPC) are considered in the proposed formulation. Furthermore, to investigate the impacts of DGs on AC-DC distribution networks, an effective approach based on sensitivity matrix calculation is proposed to approximately update the outputs of DGs in each iteration. To evaluate the performance of the approach and examine its efficiency, the proposed formulations are applied to a hypothetical 123-bus AC-DC test system, containing different type of DGs and power converters, and compared with a heuristic method. The simulation results verify the effectiveness and applicability of the proposed method in load flow analysis of AC-DC distribution networks in unbalanced condition.

Optimal siting and sizing of multiple type DGs for the performance enhancement of Distribution System using Differential Evolution Algorithm

The necessity of Distributed Generation (DG) in the modern power system has increased greatly. Optimal placement and sizing of DGs have a significant impact on the objectives of voltage stability enhancement, real and reactive power loss minimization and power system security and reliability. Different types of DGs such as Type I, Type II, Type III and Type IVare placed. The optimal placement of these DGs is found using Voltage Stability Index (VSI). The optimal sizing of these DGs is done using Differential Evolution (DE) algorithm. MATLAB simulation is carried out in standard IEEE 33-bus test system. The test is performed for various combinations of different types of DG. The results show that the voltage stability index along with Differential Evolution algorithm provides better voltage profile and power loss minimization as compared to the system without DG.

Network loss reduction and voltage improvement by optimal placement and sizing of distributed generators with active and reactive power injection using fine-tuned PSO

<span>Minimization of real power loss and improvement of voltage authenticity of the network are amongst the key issues confronting power systems owing to the heavy demand development problem, contingency of transmission and distribution lines and the financial costs. The distributed generators (DG) has become one of the strongest mitigating strategies for the network power loss and to optimize voltage reliability over integration of capacitor banks and network reconfiguration. This paper introduces an approach for the optimizing the placement and sizes of different types of DGs in radial distribution systems using a fine-tuned particle swarm optimization (PSO). The suggested approach is evaluated on IEEE 33, IEEE 69 and a real network in Malaysian Context. Simulation results demonstrate the productiveness of active and reactive power injection into the electric power system and the comparison depicts that the suggested fine-tuned PSO methodology could accomplish a significant reduction in network power loss than the other research works.</span>

Optimal integration of different types of DGs in radial distribution system by using Harris hawk optimization algorithm

The probable availability of renewable power sources is unexceptionable, and the government of India is setting high goals for the use of renewable energy. Renewable distributed generation (DG) red...

Multiple distributed generations placement and sizing based on voltage stabilityindex and power loss minimization

This paper proposes a rapid analytical method to determine the locations and sizes of multiple distributed generations (DGs) inside a distribution network. DGs locations are chosen with the aim of enhancing voltage stability and their sizes are picked so as to minimize system power losses. To evaluate the effect of the DG's nature on the system's performance, the proposed DG allocation method is tested for all DG types and the impact of the combination of different types of DGs is equally investigated, which offers a guide to designing an optimal hybrid network.

Islanding detection in distributed generation system using intrinsic time decomposition

This study introduces the implementation of intrinsic time decomposition (ITD) based passive islanding detection technique for distributed generation (DG) system. The proposed method utilises voltage signals and decomposes it into a baseline signal and residual signal. The performance index in terms of energy computed from baseline signal is defined to discriminate between islanding and non-islanding events. The proposed ITD based technique for islanding detection has been analysed on different types of DGs connected to the system. The performance of the proposed technique is validated via simulation of distribution system modelled in EMTDC/PSCAD. The different critical operating conditions: lower end active and reactive power mismatch and events like capacitor switching, load switching, inception of fault, have been simulated to test the performance of the proposed scheme. The obtained results suggest that the proposed technique exhibits high reliability and has quick response time to detect islanding situation as compared to other passive islanding detection methods.

Optimal Coordination of Double-Inverse Overcurrent Relays for Stable Operation of DGs

Due to the increasing penetration of distributed generations (DGs) in distribution networks, the performance of protective relays is becoming more critical to maintain the stability of the DGs especially during fault conditions. Among different types of DGs, squirrel cage induction generators (SCIGs) and synchronous DGs are sensitive to faults and might become unstable even after fault clearance. Since the fault clearing time depends on the overcurrent relays (OCRs) characteristic curves, this paper proposes a double-inverse OCR (DIOCR) characteristic to provide proper coordination while maintaining DGs stability. The proposed method defines the critical clearing time curve for each DG and combines them with DIOCRs curves and coordination time interval constraints for finding optimal DIOCRs settings. The proposed method is simulated on the IEEE 33-bus distribution network equipped with SCIG- and synchronous-based DGs. The obtained results highlight the capability of DIOCRs in protecting distribution system with DGs considering stability constraints.

Service restoration to critical loads using microgrids considering dynamic performance of DGs

When an extreme weather event strikes a distribution system, it is helpful to use microgrids to restore the interrupted critical loads. Due to the relatively small capacity and low inertia of distributed generators (DGs), the switching operations during the restoration process may cause severe fluctuations in voltage, current, and frequency, leading to prime-mover stalling or triggering protection relays. It is essential to investigate the dynamic characteristics of DGs during the restoration procedure. The dynamic models of different types of DGs are developed to analyse the dynamic characteristics. Analytical constraints on the dynamic performance of DGs are obtained from the simulation results, which can be incorporated into the optimisation models of critical load restoration problems. The modified IEEE 32-bus test feeder is simulated to validate the effectiveness of the proposed method.

An adaptive directional current protection scheme for distribution network with DG integration based on fault steady-state component

In view of the low reliability of traditional protection in the distribution network caused by the massive integration of DGs (distributed generation), an adaptive directional current protection scheme based on fault steady-state component is proposed in this paper. First, by analyzing the fault transient characteristics and fault equalization methods of different types of DGs, the components of system short circuit current are calculated, and the relationship between three phase components of the short circuit current is revealed. On this basis, according to the fault boundary conditions, the fault steady-state components are obtained. And then, combined with the measured voltage and measured current at the relaying point, the equivalent voltage and equivalent impedance at the backside of protection are calculated. Thus the adaptive directional current protection criteria for different fault types are formed. Simulation results demonstrate that, the proposed scheme is not affected by the type and power output of DG and the system operation mode, and could effectively prevent the protection from refusing to operate due to voltage drop.

Application of Hybrid Meta-Heuristic Techniques for Optimal Load Shedding Planning and Operation in an Islanded Distribution Network Integrated with Distributed Generation

In a radial distribution network integrated with distributed generation (DG), frequency and voltage instability could occur due to grid disconnection, which would result in an islanded network. This paper proposes an optimal load shedding scheme to balance the electricity demand and the generated power of DGs. The integration of the Firefly Algorithm and Particle Swarm Optimization (FAPSO) is proposed for the application of the planned load shedding and under frequency load shedding (UFLS) scheme. In planning mode, the hybrid optimization maximizes the amount of load remaining and improves the voltage profile of load buses within allowable limits. Moreover, the hybrid optimization can be used in UFLS scheme to identify the optimal combination of loads that need to be shed from a network in operation mode. In order to assess the capabilities of the hybrid optimization, the IEEE 33-bus radial distribution system and part of the Malaysian distribution network with different types of DGs were used. The response of the proposed optimization method in planning and operation were compared with other optimization techniques. The simulation results confirmed the effectiveness of the proposed hybrid optimization in planning mode and demonstrated that the proposed UFLS scheme is quick enough to restore the system frequency without overshooting in less execution time.

Two-level planning for coordination of energy storage systems and wind-solar-diesel units in active distribution networks

The optimal operation strategy of active distribution networks is investigated by this paper. The energy storage system (ESS) and distributed generation (DG) are utilized in the proposed planning. The paper presents two-level planning including short term and long term planning. The long term planning installs ESSs and diesel DGs on the network and the short term one determines an hourly optimal operation strategy for ESSs and diesel DGs. Different types of DG including solar photovoltaic (PV), wind, and diesel are studied at the same time. The objective function of the planning is to minimize annual operation cost of distribution network subject to security constraints of the network. The uncertainty of solar-wind units is estimated by many scenarios and stochastic programming is carried out to solve the problem. The proposed problem is expressed as a nonlinear mixed integer programming and solved by modified PSO algorithm. In order to cope with the real conditions, reactive power of ESSs and diesel DGs are included in the problem. Depth of discharge is also considered as a design variable and optimized for ESSs. The planning optimizes a large number of design variables at the same time including size and location of ESSs and diesel DGs, daily operation of diesel DGs, daily charging-discharging pattern of ESSs, and optimal depth of discharge for ESSs. The results demonstrate that the proposed two-level planning can effectively reduce cost and losses as well as increase efficiency and performance of the network.