DG Units Research Articles

Swarm intelligence and bio-inspired algorithms based active power loss reduction in microgrids using optimal placement and sizing of renewable distributed generators

Renewable energy sources now play a crucial role in meeting the world's growing energy needs sustainably. These sources, such as solar and wind energy, help reduce carbon emissions and protect the environment, making them an essential component of future energy strategies. In this paper, one of swarms’ intelligences algorithms called particle swarm optimization (PSO) and one of the most general bio-inspired metaheuristic methods called BAT algorithm are applied to determine the optimal placement and sizing of renewable distributed generators (OPSRDG) in distributed network. The focus is on enhancing energy efficiency and reduced dependency on the main grid by reducing power losses, improved voltage profile, enhanced reliability, stability enhancing the overall system stability and performance of the grid. Compared with recently published results, the obtained results are promising and demonstrate the effectiveness and robustness of the proposed approach to solve OPSRDG problems. When the DG units are optimally integrated into the system, the power loss reductions ranged from 48.23% to 71.57%. This represents a significant improvement over conventional methods, making it a promising contribution to society and academia.

Optimal allocation of electric vehicle charging stations and distributed generation in radial distribution networks

The widespread spread of electric vehicles requires the establishment of charging stations (EVCSs), and this is considered a large load on the network. This gives priority to distributing the stations in a way that reduces the load on the network, and in parallel, re-planning the network and supplying it with the necessary energy to maintain energy efficiency and power quality. Total energy loss minimization, voltage deviation minimization, and voltage stability index improvement are the considered power quality indices in the multi-objective function. Vehicle to grid (V2G) feature, distributed generation units (DG), and capacitor banks are used for improving system performance, by injecting the required active and reactive power. In addition, the initial and running costs of V2G, DG units, and capacitor banks are considered in the multi-objective function. The optimal sizing and allocation of charging stations, V2G, DG units, and capacitor banks are performed using a proposed Self-Adaptive Multi-Population Elitist JAYA (SAMPE-JAYA) algorithm and checked using the genetic algorithm (GA). The proposed algorithm is tested using various scenarios, two standard IEEE test systems. To emphasize the effectiveness and applicability of the proposed algorithm, it is applied on a real-world distribution system. To accommodate the optimal allocation of EVCS, which constitute 80.7 % and 78.9 % of the base active load for the IEEE 33 and 69 bus systems, respectively. Integrating DG amounting to 17.35 % and 18.25 % of the base load is necessary. Additionally, capacitor banks, contributing 36.84 % and 31.166 % of the reactive power load, are also required for effective voltage support and system reliability in each respective case.

A novel algorithm for optimizing genset operations to minimize fuel consumption in remote diesel-RES microgrids

This paper addresses the challenge of reducing fuel consumption in Diesel-RES (Renewable Energy Sources) isolated microgrids, particularly focusing on Diesel Genset’s (DG) operation. The study introduces a basic rule based energy management system that serves as a platform to test out various DG operational strategies with a novel approach. Two optimization strategies—load dispatch optimization and unit commitment optimization—are explored to unequally distribute loads among different grid-connected DGs and sequence their start/stop based on predictive demand profiles respectively. Additionally, the integration of a spinning reserve-providing battery is investigated to alleviate DGs from their spinning reserve constraint, resulting in higher operational loads and consequently higher efficiency. The proposed model is applied on a case study of the Tahitian power system, demonstrating reductions in fuel consumption. The combined application of the proposed DG load dispatch and unit commitment optimizations, along with the integration a spinning-reserve-providing battery, yielded a 2.6 % reduction in fuel consumption and 6kt decrease in CO2 emissions over a year compared to a basic DG operation without a battery.

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.

An AQ-SCS Optimization Assisted Optimal Expansion Planning with Fixed and Switchable Capacitors for Distribution System

Distribution System has given renewable-based DGs like Solar PV and Wind turbines a lot of attention because of growing worries about global warming and the depletion of fossil fuels. This work proposes a unique hybridized optimization technique for a distribution system expansion plan utilizing an innovative theoretical framework. Two stages are used to tackle the issue with the distribution system expansion plan: master optimization and sub-optimization for every state of the system. The developed Aquila based Sand Cat Swarm (Aq-SCS) optimization method considers the distribution system factors, like DG type, size/capacity, location, PQ power, fixed capacitor, switchable capacitor, and the SPV/wind capacity with load demand uncertainties. The sub-algorithm is employed in conjunction with the DG allocation strategy produced by the master algorithm to deduce the state-dependent operating tactics for each individual DG unit with respect to active and reactive power. The suggested Aq-SCS optimization approach is created by combining the properties of the SCSO with the AOA models. The main objective of achieving the minimal possible cost for the DSEP is verified, and the cycle continues unless the best outcome (least cost) is reached. The analysis of the suggested approach is carried out in 4 cases, such as (i) Without DG and capacitor (ii) With capacitor and no DG (iii) With DG and no capacitor (iv) With both capacitor and DG. The analysis is made in IEEE 33 bus system. The Aq-SCS approach outperforms the conservative approaches SSI-CS, WHO, AQO, and SCSO, according to the analysis conducted in MATLAB/Simulink utilizing an IEEE-33 bus system with five system states.

Optimal Planning of Battery Swapping Stations Incorporating Dynamic Network Reconfiguration Considering Technical Aspects of the Power Grid

In order to drive electric vehicle adoption and bolster grid stability, the incorporation of battery swapping stations (BSSs) into the power grid is imperative. Conversely, network reconfiguration plays a crucial role in optimizing energy exchange within the power network, ensuring its economical and safe operation. Therefore, this study proposes an optimal planning method for battery swapping stations that integrates dynamic power distribution network reconfiguration while addressing technical aspects of the grid. The proposed method aims to concurrently optimize the placement and capacity of battery swapping stations, along with power distribution network reconfiguration, to enhance grid reliability and efficiency. The optimization model accounts for various factors including power quality, technical considerations, grid limitations, and operational expenses. A multi-objective optimization framework is devised to simultaneously reduce system losses, improve voltage stability, and mitigate environmental impacts of the power distribution network incorporating DG units. Case studies are conducted to illustrate the efficacy of the proposed approach in enhancing overall grid performance while accommodating the integration of battery swapping stations. The findings underscore the significance of considering technical factors and grid reconfiguration in battery swapping station planning to achieve optimal system operation and maximize benefits for electric vehicle users and grid operators alike.

A fast multi-objective pelican optimizer for optimal coordination of DGs and DSTATCOM considering risk penetration level of wind

In this study, a new variant, the fast pelican optimizer (FPO), is proposed to improve the performance of the radial distribution network (RDEN). The proposed variant is characterized by creating a dynamic interaction between two phases, exploration and exploitation, during the search process. The modifications introduced within the standard algorithm allow the proposed new variant, namely FPO, to be fast and adaptive to efficiently solve various complex optimization problems. In the first stage, the proposed FPO is newly adapted and applied to solve the optimal locations of various types of distributed generation based renewable sources and multi shunt compensators, namely the DSTATCOM devices based FACTS technology, and in the second stage, the proposed FPO is applied to optimize the active power of DG units in coordination with the reactive power of multi DSTATCOM. Three objective functions, such as the total power losses, the total voltage deviation, and the margin stability, are optimized individually and in coordination to enhance the performances of the practical radial distribution network (RDEN) 33-bus. A deep comparative study in terms of solution quality and convergence accuracy based statistical analysis is elaborated to demonstrate the competitive aspect of the proposed FPO.

A Hybrid Energy System Based Ev Charging Station with Advanced Controller for Grid Power Quality Regulation

A solar photovoltaic array, battery energy storage, diesel generator, grid-based island are four sources and electric vehicles (EVs) are loads in grid-connected and DG-connected modes are continuously charged. There is a Charging Station (CS)/Battery charger. The primary function of Charging Station is to charge an EV battery using a solar PV array and Battery energy storage (BES). The Charging Station will intelligently utilise the energy from the grid or DG set even if the battery is empty and the power of the PV system is not accessible. The power of DG units is constantly pulled to run at 80%–85% load in order to ensure excellent fuel efficiency at all load circumstances. In the absence of a mechanical governor, CS also regulates the voltage and frequency of the generator and accumulator. Additionally, it ensures that even with non-linear loads, the power taken from the mains or DG set has unity power factor. The grid/generator voltage and the common link voltage are synced to provide continuous charging. A PI, fuzzy logic controller and ANN is also used to analyse and reduce overall harmonic distortion on the Grid. Charging Station also manages active/reactive power transfers from cars to the grid, residences, and other vehicles to increase operational efficiency. There are tools for CS operation analysis and simulation.

Interaction of fault ride through requirements and loss of mains protection

The strongly growing DG capacity is raising concerns related to unintentional islanding. Unintentional islanding is prohibited due to the associated safety risks, and it is therefore mandatory to equip all DG units with some kind of loss of mains (LOM) protection. However, large amounts of unnecessary tripping of DG units cannot be tolerated anymore as the share of DG has already reached a significant share of the total installed power generation in certain regions. Certain grid codes thus require DG units to be able to ride through remote faults and support the power system. It is generally known that grid codes and LOM protection objectives are of somewhat controversial. However, it appears that no papers have studied the relation of LOM protection performance and fault ride through requirements thoroughly with simulations. This paper aims to fill this gap by providing extensive simulations which show how exactly the grid code requirements affect the performance of LOM protection. The studies are performed in a unique simulation environment consisting of two different types of real time simulators and a real LOM relay.

Optimal allocation of DG units in distribution system considering variation in active power load

Optimal allocation of DG units in distribution system considering variation in active power load

Intelligent Fault Detection and Classification for an Unbalanced Network With Inverter-Based DG Units

Intelligent Fault Detection and Classification for an Unbalanced Network With Inverter-Based DG Units

Identification of Sphere of Influence of Single and Multiple DG Units in Distribution Networks: A Visualisation Approach Involving Sankey Diagrams and Geospatial Mapping

Identification of Sphere of Influence of Single and Multiple DG Units in Distribution Networks: A Visualisation Approach Involving Sankey Diagrams and Geospatial Mapping

Recursive Secondary Controller for Voltage Profile Improvement Based on Primary Virtual Admittance Control

This paper proposes a recursive, virtual admittance based, secondary controller for DG units that improves the voltage profile in distribution networks. First, the adaptation of the virtual admittance concept for the goal of voltage regulation is explained. Then, a recursive secondary controller is developed to periodically update the virtual admittance gains. The controller is formulated as an optimization problem with current and stability limitations as constraints. Measurements across the grid, transmitted through low-bandwidth communications, are used to simplify the calculations, resulting in a recursive algorithm. Weight vectors are included in the objective function to allow participation flexibility of each converter. Results show that the primary virtual admittance controller is able to mitigate over- and under-voltages in steady state and under transient conditions. Subsequently, the secondary controller is shown to further improve the voltage profiles across the grid. Experimental results obtained from a laboratory environment, comprising three DG units and a grid emulator, validate the functionality of the complete control structure.

New Passive Loss of Mains Detection Scheme Using Characteristics of Differential Impedance of Series Inductor

Nowadays, renewable energy sources (RESs) are widely used as distributed generation sources, leading to issues such as unintentional islanding, protection concerns, and reverse power flow. Unintentional islanding is dangerous because it can endanger utility workers, damage DG units, and jeopardize grid stability. To overcome these issues, Researchers are developing islanding detection schemes. This article proposes a novel passive technique for islanding detection of multi-bust test systems, based on the differential impedance of a series inductor. The differential impedance changes during islanding and non-islanding events. However, in grid-connected mode, the voltage and frequency of the microgrid are handled by the utility grid. Therefore, no significant changes in differential impedance occur. The voltage and frequency of the microgrid are not handled by the power grid while in islanded mode. Therefore, the differential impedance varies significantly. The islanding is detected if the value of differential impedance is greater than the predefined threshold. This scheme detects islanding in 24 ms at zero mismatch power, has no impact on power quality, and is computationally simple. The proposed approach easily discriminates between islanding and non-islanding events. The distribution test system is simulated in MATLAB/Simulink environment. Additionally, the novel passive technique has been validated on an OPAL-RT real-time platform.

Economic Operation of Multi-terminal Interlinking Microgrid Based on the Decentralized Protocol

This paper develops a decentralized control strategy based on an interlinking converter to realize the global economic optimal operation of a multi-terminal interlinking microgrid (MG). The control objective is to minimize the total generation cost (TGC) of the interlinking microgrid system. The proposed control is composed of local and global controllers, which deal with sub-MG and interlinking MG systems respectively. The local controller regulates the incremental cost (IC) value matching in the sub-microgrid based on the nonlinear dynamic droop control with equal IC to achieve the optimal load power distribution in the local DG units. The global controller controls BIC through the bus voltage signal to match the IC value of the entire interlinking MG system in a decentralized form, which significantly improves the reliability and scalability of the system and achieves the global optimal economic optimal operation under the condition of meeting the power demand and production constraints. The feasibility and superiority of the proposed controller are verified by PLECS under various test cases.

A simple closed-loop interphase power controller for cascaded H-bridge converter-based DG units in islanded microgrids with imbalanced loads

A simple closed-loop interphase power controller for cascaded H-bridge converter-based DG units in islanded microgrids with imbalanced loads

Evaluation of Over Current Relay Settings Optimization for Multi-infeed DG-connected-grid

Increasing the short-circuit current magnitude and bidirectional flow in a multi-infeed DG-connected grid have significant impacts on protection systems based on over-current relays (OCRs). An adaptive protection scheme based on defining the optimal setting of a directional OCR (DOCR) has recently been introduced as a solution for mis-coordination and false tripping issues associated with DG penetration increase. In this paper, this approach is highlighted, and its performance in different operating modes of the DG-connected grid is evaluated. Genetic algorithm (GA), and gray wolf optimization (GWO) have been used to provide optimized values of the time multiplier setting (TMS) of the DOCR scheme. Different faults at different locations with different DG locations and sizes are studied. The international electrotechnical commission (IEC) micro-grid benchmark and different DG units are modeled with MATLAB Simulink and ETAP software to carry out and test all these operating modes and evaluate this scheme. The ability of this scheme to maintain the coordination between the forward and reverse main and backup relays for each fault location is focused on in this study.

Optimal Allocation of Hybrid Renewable Distributed Generation with Battery Energy Storage System Using MOEA/D-DRA Algorithm

The need for energy and environmental sustainability drives the adoption of renewable energy systems to reduce greenhouse gas emissions. Efficient planning of energy sources is crucial for a reliable distribution network. This article solves the optimal allocation of hybrid energy sources (i.e., Renewable Distribution Generators (RDGs) and Battery Energy Storage System (BESS)) problem, aiming to minimize the annual energy loss and investment costs simultaneously. The proposed formulation includes the uncertainties such as forced outages of RDG’s, intermittence in RDG power generation, Expected Energy Not Served (EENS) by DG units, and time-varying demand altogether in the existing formulation. To evaluate the effectiveness of the proposed formulation, a Multi-Objective Evolutionary Algorithm based on Decomposition with Dynamic Resource Allocation (MOEA/D-DRA) is used. Simulation studies are conducted on IEEE 33-node and TNEB 84-node Radial Distribution Systems (RDSs), comparing results with the Rider Optimization Algorithm (ROA) and Hybrid Nelder Mead-Particle Swarm Optimization (HNMPSO) respectively. The proposed formulation for a Multi-objective Optimization of Hybrid Energy Sources allocation problem solved by the MOEA/D-DRA algorithm provides improved benefits like minimum annual energy loss, investment cost, CO2 emission, EENS by the DG units, and enhanced system voltage stability and voltage profile.

Control Design of Grid-Forming and Grid-Following Inverters with a seamless transition in Microgrid

The development of renewable energy resources has grown significantly in recent years. These distributed energy resources are typically connected to the grid through power converters, which can be operated in "grid-forming" or "grid-following" mode. But the large-scale integration of DG units has serious repercussions on the stability of the power system due to their low inertia compared to the synchronous generator. However, an appropriate control guarantees a dynamic, smooth, and fast converter behaviour in an island configuration and voltage-frequency support in grid-connected mode. This paper presents a control system for Grid-Following and Grid-Following converters for a grid-connected MG. The aim is to achieve a seamless transition between the Microgrid and the main grid, appropriate load sharing between distributed energy sources, and an improvement of system stability. The developed grid-connected battery storage system inverter has been designed to be able to operate in two different modes: grid formation mode and grid injection mode. The control strategy considers the control loops of Voltage/current, Frequency, and active/reactive power. The proposed control technique is presented and simulated under the MATLAB/Simulink tool. The simulation results demonstrate the efficiency and performance of the proposed control technique in eliminating voltage, current, and frequency fluctuations and also guarantee a seamless transition between the two modes.

Effective Deterministic Methodology for Enhanced Distribution Network Performance and Plug-in Electric Vehicles

The rapid depletion of fossil fuel motivates researchers and policymakers to switch from the internal combustion engine (ICE) to plug-in electric vehicles (PEVs). However, the electric power distribution networks are congested, which lowers the accommodation of PEVs and produces higher power losses. Therefore, the study proposes an effective deterministic methodology to maximize the accommodation of PEVs and percentage power loss reduction (%PLR) in radial distribution networks (RDNs). In the first stage, the PEVs are allocated to the best bus, which is chosen based on the loading capacity to power loss index (LCPLI), and the accommodation profile of PEVs is developed based on varying states of charge (SoC) and battery capacities (BCs). In the second stage, the power losses are minimized in PEV integrated networks with the allocation of DG units using a recently developed parallel-operated arithmetic optimization algorithm salp swarm algorithm (AOASSA). In the third stage, the charging and discharging ratios of PEVs are optimized analytically to minimize power losses after planning PEVs and DGs. The outcomes reveal that bus-2 is the most optimal bus for accommodation of PEVs, as it has the highest level of LCPLI, which is 9.81 in the 33-bus system and 28.24 in the 69-bus system. The optimal bus can safely accommodate the largest number of electric vehicles, with a capacity of 31,988 units in the 33-bus system and 92,519 units in the 69-bus system. Additionally, the parallel-operated AOASSA mechanism leads to a reduction in power losses of at least 0.09% and 0.25% compared with other algorithms that have been previously applied to the 33-bus and 69-bus systems, respectively. Moreover, with an optimal charging and discharging ratio of PEVs in the IEEE-33-bus radial distribution network (RDN), the %PLR further improved by 3.08%, 4.19%, and 2.29% in the presence of the optimal allocation of one, two and three DG units, respectively. In the IEEE-69-bus RDN, the %PLR further improved by 0.09%, 0.09%, and 0.08% with optimal charge and discharge ratios in the presence of one, two, and three DG units, respectively. The proposed study intends to help the local power distribution companies to maximize accommodation of PEV units and minimize power losses in RDNs.