Sizing Of DG Research Articles

Strategic DG placement and sizing in developing nations' power systems using ISNT and modified forward-backward sweep

The power sector in many developing nations faces challenges in meeting consumers’ demands for a reliable electricity supply due to increased load demand, primarily driven by population growth. Urban areas receive 24 h power, while extensive losses within the system limit coverage. Setting up centralised stations offers a temporary solution, but the capacity of the ageing transmission lines is uncertain. This study proposes integrating distributed generators (DG) into the power system, using Inherent Structural Network Topology (ISNT) for DG siting and a modified Forward-Backward Sweep model for sizing. Voltage Stability Index (VPI) assesses network stability. The model considers voltage profile and line losses, optimizing DG sites and sizes. Results demonstrate the model’s efficacy, offering insights for optimal DG planning to minimize losses and enhance voltage profiles. The study informs power system engineers for future planning, aiding decisions on DG location and size, potentially reducing line losses and improving voltage profiles, thus assisting in network upgrades or expansions.

Hybrid design of optimal reconfiguration and DG sizing and siting using a novel improved salp swarm algorithm

Hybrid design of optimal reconfiguration and DG sizing and siting using a novel improved salp swarm algorithm

Optimal allocation of Combined DG and DSTATCOM for Improving Voltage Stability and Economical Benefits of Distribution System

In the vertically integrated power sector, the distribution system serves as the link between customers and the transmission network. Different load models, including industrial, residential, and commercial, are taken into account within the distribution systems. The loading pattern of these load models varies with a large range according to the peak hours. During peak load conditions, the voltage magnitude of some nodes exceeds the permissible limit of voltage value. It affects the voltage stability of the distribution system, leading to decreased reliability, heightened power losses, diminished voltage stability, and other safety concerns. Optimal placement of capacitors, applying DGs, using FACTS devices, and Distribution Network reconfigurations are possible to reduce the power loss. This paper focuses on reducing power loss and enhancing the voltage profile and stability of the system. It addresses the technical, economic, and environmental benefits of the distribution system through appropriate placement and sizing of DG and DSTATCOM units in a coordinated manner. The issue is approached as a Multi-Objective Optimization Problem (MOP) and is tackled through the application of the Group Teaching Optimization (GTO) algorithm, an innovative metaheuristic method. A numerical illustration utilizing an IEEE 69-node system is examined, and the simulated outcomes are presented in tabular form. These results are then juxtaposed with findings from comparable methodologies outlined in existing literature.

Techno-economic optimization for isolated hybrid PV/wind/battery/diesel generator microgrid using improved salp swarm algorithm.

The main objective of this study is to develop a new method for solving the techno-economic optimization problem of an isolated microgrid powered by renewable energy sources like solar panels, wind turbines, batteries, and diesel generators while minimizing greenhouse gas emissions. An Improved Salp Swarm Algorithm (ISSA) with a position adaptation mechanism for the salp leader that involves a leader salp that moves about depending on both food availability and its previous position has been proposed to overcome the convergence problem. In the original SSA, as the approach converges, it can no longer find optimal solutions and becomes trapped in a local minimum. Three Microgrid System (MS) configurations are discussed: PV/WT/BESU/DG, PV/BESU/DG, and WT/BESU/DG. The proposed method seeks to find a middle ground between technical criteria and environmental concerns when deciding on PV, WT, BESU, and DG sizes. The findings indicate that the proposed ISSA approach gives superior results compared to other well-known algorithms like the original SSA, the Ant Lion Optimizer (ALO), the Dragonfly Approach (DA), and the Moth-Flame Optimization Algorithm (MFO), which, after significant investigation, has been proven to help determine the appropriate microgrid size. With PV sizes of 10, 9 WT, 24 BESU, and 3 DG, the PV/WT/BESU/DG configuration offers the highest level of cost-effectiveness with Cost of Energy (COE) of 0.2109 $/kWh, Net Present Cost (NPC) of 376,063.8 $, Loss of Power Supply Probability (LPSP) of 4%, Renewable Energy Fraction (REF) of 96%, and CO2 emission of 12.4457 tons/year. ISSA is brought up as a possible solution to both the problem of rising energy prices and the difficulties inherent in microgrid design.

Artificial Intelligence for Optimal Sizing and Location of DG in Power Systems

Artificial Intelligence for Optimal Sizing and Location of DG in Power Systems

A New Framework for Active Loss Reduction and Voltage Profile Enhancement in a Distributed Generation-Dominated Radial Distribution Network

In recent times, a significant amount of power loss and system instability due to high voltage deviation experienced by modern power systems, in addition to the pressing issues challenging the power industry such as pollution—especially the emission of greenhouse gases—and aging infrastructures, have posed a serious threat to system operations. Distributed generation has been identified as one main solution capable of reducing pollution when solar and wind power are used and, hence, rejuvenating dilapidated infrastructures and redeeming climatic changes. This paper presents a novel two-stage approach for the identification of suitable locations for DG placement and the sizing of DG for loss reduction and voltage stability enhancement. The first stage explored the use of a network structure to develop a coupling factor (CF) approach that was non-iterative in nature to determine suitable DG locations. In the second stage, the size of the DG was determined using the particle swarm optimization (PSO) algorithm. The main objective was to obtain an optimal voltage profile of the system under consideration while lowering the power loss in the system and ensuring network stability amidst DG incorporation. The model design, optimization and simulation were carried out using the MATLAB 2016a environment and the IEEE 33-bus test system, in which DG was integrated. The influence of increasing the level of DG placement in the system was then investigated. The forward/backward sweep method was applied to monitor the optimization process. The voltage profiles for both the base case when no DG was integrated and the case of incremental DG integration were considered. The results obtained for both single and multiple DG integration are compared with those obtained using the existing methods. The results show the efficiency and applicability of the new non-iterative scheme in the quick identification of DG locations for voltage profile enhancement and network real power loss reduction in radial distribution networks.

Optimal Placement and Sizing of DG for Loss Reduction,Voltage Profile Improvement and Voltage Sag Mitigation

Increasing trend in using distributed generation has motivated power sector planners to consider approaches that result in benefiting the most from investments in this field. Meanwhile subjects such as power loss reduction, voltage profile improvement and voltage sag mitigation has significant role in lessoning imposed expenditures to utility companies. Loss reduction is important for utility companies as it directly increases company benefit in a competitive electricity market, beside reaching power quality standards is too important as it has vital effect on customer orientation. In this paper an optimization algorithm is developed to gain these goals all together. In order to evaluate sag mitigation capability of the proposed algorithm, voltage in voltage sensitive buses is investigated. An existing 20KV network has been chosen as test network. Results show the efficiency of the proposed algorithm in reducing power loss, improving voltage profile and mitigating voltage sags in voltage sensitive buses.

Colossal permittivity and excellent temperature stability of BaTiO3 based fine ceramics with controlled grain growth

Dielectric materials with colossal permittivity (CP, εr > 104) have attracted the increasing interest of researchers due to their enormous potential in the fields of sensor, capacitor, energy storage, etc. However, for the explored CP materials, their grains are too large to apply. To control grain growth, the sintering aids of MgO–Al2O3–SiO2 (MAS) cordierite glass and common suppression grain growth of MgO have been introduced to BaTiO3-0.004Y2O3-0.006MnO2 ceramics derived from the commercial BaTiO3 powder with the average grain size of 300 nm. After controlling grain growth, the fine grains with the average grain size of dg ∼300 nm and CP are achieved in BaTiO3 based ceramics sintered in reducing atmosphere. Notably, excellent temperature stability with Δεr/εr25°C lower than 17 % is gained for the present BaTiO3 based ceramics in the temperature range of −60 to 155 °C, meeting the X8S specification (ΔC/C25°C ≤±22 %, −55 °C–150 °C). Based on the X-ray photoelectron spectroscopy (XPS) and Raman spectra, the outstanding dielectric properties of the present BaTiO3 based ceramics is ascribed to the electron-pinned defect-dipole (EPDD) effect induced by YTi′−YBa∙, TiTi′−Vo∙∙−TiTi′ and YTi′−Vo∙∙−TiTi′ defect dipoles. The present BaTiO3 based fine ceramics with colossal permittivity (∼2.9 × 104), low loss (∼0.03) at 1 kHz and room temperature, excellent temperature stability and high resistivity of 3.54 × 109 Ω cm is a promising candidate for the multilayer ceramics capacitor (MLCC).

Enhancement of Technical, Economic and Environmental Benefits of RDN Using Jaya Algorithm Considering Renewables Uncertainties

Due to a larger R/X ratio, distribution networks experience active power losses that are higher than those in transmission networks. Natural resources based on fossil fuels are becoming depleted as a result of rising load demand, which is of great concern to network operators. Besides, a major threat to the environment is the harmful emissions from fossil fuels. So, in order to address the rising demand for energy during this energy crisis, renewable energy sources like solar and wind power are excellent alternatives. This research presents a comparative evaluation of the enhancement of a constrained weighted-sum multi-objective function comprising voltage profile, economic, and environmental improvement factors using the Jaya algorithm for a PV and wind energy integrated radial distribution network. The outcomes of various combinations of PV and wind-based distributed generator integration at single, double, and triple points of typical IEEE 33 and 141 bus test systems have been compared with those of several promising methods. The novelty of the work lies in the fact that simultaneous analyses of technical, economic, and environmental impacts during optimal sizing and sitting of DG have not yet been reported in the literature. The highest relative improvements in overall objective are up to 4.05 and 2.02 times for IEEE 33 and 141 buses, respectively, considering the corresponding worst cases as references. The maximum reduction in the active power losses reported are 47.11% and 43.09% for IEEE 33 and 141 buses, respectively.

Optimal allocation and sizing of DG and FCL units in distribution networks to ensure protection coordination and cost reduction

Optimal allocation and sizing of DG and FCL units in distribution networks to ensure protection coordination and cost reduction

A comprehensive review of recent advances in optimal allocation methods for distributed renewable generation

AbstractDistributed generation (DG) has a key role in enlarging the implementation of renewable energy resources (RES). However, the intermittent and uncontrollable nature of RES can lead to several severe power quality‐related issues. Therefore, many efforts have been made to overcome these issues by optimizing DG sizes and locations. Hence, optimal DG allocation (ODGA) is significant for DG performance and provides advantages to the power system, such as improved power quality, voltage stability, reliability, and profitability. This study reviews recent ODGA studies eliminating the main DG integration problems. Often used ODGA methods have been categorized, and the main differences have been discussed, giving the details of features of optimization methods such as convergence performance and computational burden. A deep analysis for categorizing the objectives of ODGA has been done. In addition, optimization methods applied in ODGA studies have been presented by comparing the superiorities of algorithms and validated test network models. The objectives and significant findings of the ODGA applications are summarized with the advantages and disadvantages. It can be concluded that ODGA has a critical role in RES integration on the DG side and in reducing carbon emissions. This paper leads and provides a perspective for researchers working on recent ODGA methods.

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.

Positioning and Sizing of PV-Based DG and Capacitor in Realistic Distribution Network and Verification through ETAP Simulation

Distributed generation offers a bright future for electric networks, but requires optimal allocation of dispersed resources and an acceptable optimization technique. This article proposes optimal integration of DGs and capacitor banks to optimize distribution network parameters. Imperialist competitive algorithm (ICA) has been used to optimize the distribution network parameters such as optimal location and capacity of Photo Voltaic Distributed Generator ((PVDG) & capacitor. Loss reduction, declination in emission, and an enhanced voltage profile are major advantages of positioning DGs into the distributive topology. The proposed model has been validated and tested on IEEE-33 and Indian real system of 130 bus of Jaipur City for different load patterns. Furthermore, the results obtained from ICA have been verified by simulating the test systems on ETAP software.

Multi-Objective Optimal Siting and Sizing of Distributed Generators and Shunt Capacitors Considering the Effect of Voltage-Dependent Nonlinear Load Models

Load modeling is essential to distribution system analysis, planning, and control. Therefore, in this work, effect of non-linear load models has been considered for the optimal site and size of DG and SC allocation. A new and efficient modified branch and bus ordering-based forward-backward load flow method has been applied to solve load flow problem in radial distribution system. Recently implemented several state-of-the-art evolutionary algorithms (EAs) are employed to solve optimal site and size of DG and SC allocation problems and it is shown that performance of multi-operator/multimethod is better than other algorithms that are based on a single operator and/or algorithm. Therefore, a new hybrid EA based on various state-of-the-art operators such as GA, DE, and PSO is designed and applied to solve optimal site and size of DG and SC allocation problems. Various technical objective functions (index of active and reactive power loss and voltage deviation index) are considered to show the impacts of non-linear load models. From the simulation results, it is shown that DG and SC allocation problem is multi-objective. Therefore, further weighted sum multi-objective technical, economic, and environmental functions are formulated to find the solution to DG and SC allocation problems. The gathered results demonstrate that the proposed methodology significantly minimizes the cost of energy supplied by grid, total operating cost, and active and reactive power losses. Consequently, it can be stated that the suggested methodology has considerable economic and technological benefits and may be used to address many optimization issues in various distribution networks.

Modified Satin Bowerbird for Distributed Generation in Remotely Controlled Voltage Bus

The distributed generators in the radial distribution network are to improve the Grid performance and its efficiency. These Distributed Generators control the PV bus; it is converted as a remote controlled PVQ bus. This PVQ bus reduces the power loss and reactive power. Initially, the distributed generators were placed in the system using mathematical modelling or the optimization. This approach improves the efficiency but it has no effect in loss minimization. To minimize the loss the reconfigured network with Genetic algorithm based Distributed generator placement proposed as existing work. This approach minimizes the loss effectively; but the genetic algorithm takes more time for DG placement. Hence, in this, the network reconfiguration is performed using a modified Satin bower bird algorithm after DG placement and DG sizing. Initially, the sensitive analysis applied the load flow analysis to identify the optimal placement for the distributed generator. Then, the modified Satin Bowerbird (SBO) used for the network reconfiguration. This approach minimizes the loss of effectively by combining the network reconfiguration process. The proposed modified SBO-based network reconfiguration implemented on standard bus systems 33 and 69 using MATLAB R2021b version under Windows 10 environment. The proposed approach compared with the existing work in terms of real power loss and loss reduction.

Multi-Objective Decision Approach Integrated with Loadability and Weight Factor Analysis for Reconfiguration with DG Sizing and Allocation Including Tap Changer

Multi-Objective Decision Approach Integrated with Loadability and Weight Factor Analysis for Reconfiguration with DG Sizing and Allocation Including Tap Changer

An optimal placement and sizing of type-IV DG with reactive power support using UPQC in an unbalanced distribution system using particle swarm optimization

An optimal placement and sizing of type-IV DG with reactive power support using UPQC in an unbalanced distribution system using particle swarm optimization

Analysis of multi-distributed generation systems based on solar/biomass/natural gas/diesel energy resources for off-grid application

This study presents the analysis of multi-distributed generation systems for 20 off-grid homes in Ogun State based on the techno-environmental analysis planning (TEAP) approach. The technical aspect includes the load, DG capacities, energy generation/year, and the unmet energy demand (UED. The paper considers and compares different energy configurations such as the PV-based DG, the hybrid DGs: PV/biogas, PV/biogas/natural gas, PV/biogas/diesel, PV/diesel, and the diesel-based DGs. The environmental aspect examines the emissions produced by the DGs compared to a diesel-based DG system. The paper also examines the effect of temperature on the performance of the PV system. The simulation is based on a total daily demand of 99.04 kWh/d, and the solar, ambient temperature and the biomass data in Hybrid Optimization of Multiple Energy Resources (HOMER) environment. The size of the PV-based DG obtained is 36.9 kW, which generates 54,565 kWh/yr without temperature effect. Result shows that this value reduced to 48,268 kWh/yr with temperature effect and the value of UED is 7.84 %. The biogas, natural gas and diesel generators have the same size of 13.2 kW. The hybrid DGs achieve a UED of 0% implying 100 % system availability. Results further demonstrate that the mentioned hybrid DGs have CO2 emissions that range between 2.21 and 15, 448 kg/yr, compared to a value of 40, 273 kg/yr obtained when the homes are entirely run on a diesel-based DG. The study can help to understand energy systems analysis.

Power loss minimization and voltage profile improvement of radial and mesh distribution network using sine cosine optimization based DG allocation

Due to the increasing population and emerging technologies, energy requirements are increasing progressively. Distributed generation (DG) is an excellent option to handle the increased power demand. A well optimized DG can help to reduce power losses, CO2 emission and improve voltage profiles. This paper uses sine cosine algorithm to find the optimal location and best size ofDG with power loss minimization as its objective function. It presents the comparison of power loss reduction and voltage profile enhancement due to allocation of DGoperating at 0.85, 0.95 power factor lag andthe optimal power factor that has been obtained by sine cosineoptimization. IEEE 15, 69 bus radial and 33, 69 bus weakly meshed systems with five tie lines are used for power loss analysis. Annual energy saving due to allocating DG with different power factors have been analyzed. All the results are simulated in MATLAB 2021a.

Feasibility of integrated photovoltaic and mechanical storage systems for irrigation purposes in remote areas: Optimization, energy management, and multicriteria decision-making

Remote and rural areas are suffering from the lack of electricity, which makes electrical power needed for irrigated pumps one of the challenges in those regions. This paper proposed a hybrid system consisting of photovoltaic and different sizes of diesel generators as the main energy production source, flywheel, and batteries as storage systems. HOMER software is used to determine the optimum configuration of the proposed system, as well as to analyze its economic and environmental impact. The investigation was conducted on twelve alternatives that include different energy management strategies and sizes of diesel generators. Seven criterions involving technical, economic, and environmental metrics are considered during the assessment process. Multicriteria decision-making (MCDM) based on; no priority, CRITIC and Entropy as different approaches of weight has been applied to identify the best alternative. Alternative A8 which includes 750 kW DG size and combined LF–CC energy management is ranked as the first, followed by alternative A4 which comprises 500 kW size of DG and applies LF management strategy. Alternative A11 which includes DG of 750 kW and predictive control energy management is ranked as the worst one. The case study was conducted and simulated based on the weather of Atbara, Sudan.