Distribution Companies Research Articles

The impact of management control on the performance of large distribution companies in Morocco

This study investigates the impact of management control on the managerial performance of large-scale retail companies in Morocco, addressing a research gap in the local literature. Despite the considerable growth of the Moroccan retail sector, there is limited research on management control practices within this context. The research focuses on the implementation and effects of management control systems in the Moroccan retail industry, specifically examining their contribution to enhancing managerial performance. Adopting a multidisciplinary approach drawing from management control, performance management, and the retail industry, the study centers on the case of Label'vie Group. Through empirical research, the aim is to elucidate how effective management control practices positively influence the managerial performance of Moroccan retail businesses. Anticipated findings are expected to offer valuable insights for scholars and industry professionals in the management control field, particularly in emerging economies like Morocco. Furthermore, this research addresses the literature gap in the Moroccan business landscape, highlighting the importance of understanding and implementing management control mechanisms in the dynamic realm of retail. The structured abstract aligns with the journal's requirements and provides a clear framework for readers to comprehend the purpose, methodology, expected findings, and practical implications of the study.

Design and analysis of optimal AGC regulator for multi‐area power systems with TCPS and energy storage unit in deregulated environment

AbstractIn today's electric power network, fast changes are the norm, and auxiliary services such as automatic generation control (AGC) play a crucial role in maintaining the quality of the power supply. AGC ensures a balance between power generation, demand, and losses to sustain frequency stability and variation in tie‐line power within a set limit, even when the load changes. To accomplish this, it is always beneficial to consider new approaches to controlling the situation. This paper introduces the design of new AGC regulators that consider deviation in DC tie‐line power as an extra control variable for the turbine controller. In this study, three different deregulated power systems (containing two control areas), namely three thermal generations, the combination of one thermal and two hydro generations, and three hydro generations, including two power distribution companies (DISCOs) in each control area. These optimal AGC regulators are implemented in the proposed thermal–thermal–thermal system to carry out the various power contracts. The results have shown that the dynamic outcomes meet the AGC standards. To improve further dynamic results and the proposed systems' stability margins by incorporating redox flow batteries (RFB). In actual operating conditions, the system parameters do not remain constant due to the aging effect, assumptions made in simplifying the mathematical model, etc. Thus, ±50% deviations in the nominal value of system parameters to assess how well the optimal AGC regulators perform in the system under investigation. The suggested realistic AGC system incorporates many parameter fluctuations and works well with the optimal AGC regulators developed for the proposed plans. This study expanded to include a two‐area, thermal‐hydro‐hydro (THH) system under a deregulated framework connected via an asynchronous transmission link with or without a thyristor‐controlled phase shifter (TCPS) and RFB. The genetic algorithm (GA) can solve many issues and has global search, flexibility to varied problem types, intrinsic parallelism, and the ability to handle massive, complex search spaces. Thus, a two‐area deregulated hydro‐hydro‐hydro system with parallel tie‐lines utilizes GA‐PID, GA‐FOPID, and GA‐(1 + PI)‐FOPID controllers. Moreover, a random load disturbance (RLD) is employed in each section of the offered approach to show the resilience and elite performance of the proposed control strategy. To produce various dynamic reactions in the plans, MATLAB software version R2013a is employed.

An Exact Approach to the Multi-Compartment Vehicle Routing Problem: The Case of a Fuel Distribution Company

Over the years, the vehicle routing problem has been studied by several authors, creating several extensions, such as the multi-compartment vehicle routing problem. Several studies in the literature have addressed this problem, but few have solved it through exact approaches owing to model convolution. In this way, a mathematical model is proposed for the multi-compartment vehicle routing problem with time windows, in which three types of fuel products are distributed to a set of customers using a limited homogeneous fleet. The model explicitly considers time windows, as well as regulatory rest times for the drivers and time limits for each trip and for working schedules, addressing a real company’s decision support requirements, which is scarce in the literature. The optimal solution determines, for each vehicle, the distribution route and time to carry out the deliveries with the corresponding loading of products to compartments, complemented by the calculation of carbon emissions. The main objective is to minimize the total distance traveled, which corresponds to the sum of the distances traveled by each one of the allocated vehicles. The results allow the assessment of the solution optimization applied to a set of instances for a Portuguese company to evaluate the performance and compare decision support improvements with current baseline company procedures.

Coordinated planning of DGs and soft open points in multi‐voltage level distributed networks based on the Stackelberg game

AbstractThere are significant differences in distributed generators (DGs) distribution and load characteristics between different voltage levels, which makes it difficult to match sources and loads. We focus on the problem of different consumption capacities at different voltage levels and the divergence of interests among investment entities, and propose a coordinated planning model for DGs and soft open points (SOPs) based on the Stackelberg game. Firstly, a model of a multi‐voltage level distribution networks (DNs) is constructed based on SOPs. Next, the source‐load matching degree is proposed as a measure of the degree of matching between sources and loads in the DN, and the source‐load consumption rate is selected as an indicator to evaluate the impact of the load on DG consumption. Following this, the interest demands of DG investors and distribution company (DisCo) in multi‐voltage levels DN are analyzed, a planning mode based on the Stackelberg game is proposed, and this is solved by combining the genetic algorithm with second‐order cone programming. Finally, the effectiveness of the planning model is tested and verified using an improved IEEE 28‐node system. The results show that the proposed model improves the DG consumption capacity of DNs with multiple voltage levels while protecting the interests of DG investors and DisCo.

Research on Lifecycle-based Financial Strategy on New Energy Enterprises: Take CATL as an Example

The emergence of energy security issues reflects the current global turmoil and division. The two energy crises and regional conflicts have put the global energy system in a severe winter. Energy security is not only the latest requirement for the high-quality development of countries under the "carbon neutrality" background but also an aspect of overall global progress. This study selects the leading enterprise in the new energy industry, Contemporary Amperex Technology Co., Limited (CATL), as the research object. Based on the life cycle theory and financial strategy theory, the paper analyzes the company's financing, investment, and profit distribution strategies and constructs a financial strategy matrix to study the problems existing in the company's current financial strategy. The research results show that there are issues such as unreasonable financing structure, insignificant investment benefits, and significant fluctuations in dividend distribution policies. Finally, targeted optimization suggestions are proposed, hoping to provide a reference value for peers.

An evaluation of 2013 privatization on Benin Electricity Distribution technical and workforce performance

Purpose This study aims to investigate the impact of the 2013 privatization of Nigeria’s energy sector on the technical performance of the Benin Electricity Distribution Company (BEDC) and its workforce. Design/methodology/approach This study used a questionnaire-based approach, and 196 participants were randomly selected. Analytical tools included standard deviation, Spearman rank correlation and regression analysis. Findings Before privatization, the energy sector, managed by the power holding company of Nigeria, suffered from inefficiencies in fault detection, response and billing. However, privatization improved resource utilization, replaced outdated transformers and increased operational efficiency. However, in spite of these improvements, BEDC faces challenges, including unstable voltage generation and inadequate staff welfare. This study also highlighted a lack of experience among the trained workforce in emerging electricity technologies such as the smart grid. Research limitations/implications This study’s focus on BEDC may limit its generalizability to other energy companies. It does not delve into energy sector privatization’s broader economic and policy implications. Practical implications The positive outcomes of privatization, such as improved resource utilization and infrastructure investment, emphasize the potential benefits of private ownership and management. However, voltage generation stability and staff welfare challenges call for targeted interventions. Recommendations include investing in voltage generation enhancement, smart grid infrastructure and implementing measures to enhance employee well-being through benefit plans. Social implications Energy sector enhancements hold positive social implications, uplifting living standards and bolstering electricity access for households and businesses. Originality/value This study contributes unique insights into privatization’s effects on BEDC, offering perspectives on preprivatization challenges and advancements. Practical recommendations aid BEDC and policymakers in boosting electricity distribution firms’ performance within the privatization context.

A multi‐layer–multi‐player game model in electricity market

AbstractHere, a novel tri‐level energy market model aimed at addressing the challenges posed by demand side management (DSM) in the electricity distribution company (EDC) is introduced. DSM has emerged as a new strategy employed by EDCs to manage and control electricity demand by encouraging end‐users to modify their electricity consumption patterns. This is achieved through the participation of demand response (DR) aggregators, which play a crucial role in assisting end‐users with strategies and technologies to reduce their electricity consumption during peak hours. The proposed tri‐level energy market model consists of four distinct players: EDC, microgrids, aggregators, customers. The interactions between these four actors are modelled within a tri‐level game framework, where the EDC and aggregators act as leaders, and the micro‐grids and customers are followers. This multi‐level and multi‐player game structure allows for a more realistic representation of the complexities involved in DSM programs within the energy market. To demonstrate the effectiveness of the proposed model, a real case study is utilized, showing that the new model better resembles real‐life market conditions. The results illustrate how the tri‐level energy market model can significantly reduce demand fluctuations during peak hours, leading to improved efficiency and effectiveness within DSM programs.

Cost-Benefit Analysis Tool for Deploying Solar Irrigation Pumps: The Case for Rajasthan

This technical note discusses a cost benefit analysis tool to assess the economic viability of Solar Irrigation Pumps by calculating the monetary benefits to stakeholders such as distribution companies, the Rajasthan state government, and farmers by creating an additional income source. Feasible costs and assistance from DISCOMs and the state government will embolden more farmers to opt for solar irrigation pumps. Additionally, this technical note also highlights the reduced carbon footprint resulting from the avoided power procurement costs by DISCOMs.

A Systematic Review on the Application of Power Eelectronics in Renewable Energy Systems using SWOT Analysis

Background: The frequency of energy crises due to shortage of fuel or rise in fuel prices has increased in the past decade. This may be due to increasing energy demand, the financially crippled state of the distribution companies, high prices of fuel, shortage of fuel, tension between the countries, etc. Apart from this, climate change, global warming, and rising environmental concerns have necessitated the need to search for more sustainable alternative sources of electricity. It has created a lot of interest in Renewable Energy Sources (RES), which includes solar, wind and hydropower. Even governments all around the world are introducing policies to support the adoption of RES for the generation of electricity and have set the target to achieve the Net-Zero emission level by decarbonizing the power sector. Methods: This paper provides an overview of all the prominent renewable energy technologies, namely solar power plants, wind energy plants, biomass and hydropower, using a systematic review procedure. In addition to this, the importance of Power Electronic Technologies (PET) in the integration of RES in today’s power system has also been presented. Further, a SWOT analysis framework has also been utilized to evaluate the strengths, weaknesses, opportunities and threats associated with the application of PET in renewable energy systems. Result: The results from the analysis showcases that the implement of PET offers significant strength for the implementation of RES in the power system by providing increased system efficiency, and improved power quality. However, the technologies also face some of the weakness of limited scalability, regulatory concerns, high initial cost etc. Further, the different opportunities for a widespread adoption of PET have been discussed in this paper. Finally, all the threats concerning the implementation of the PET in the RES in the modern power system have also been highlighted. Conclusion: The purpose of this research work is to classify recent research techniques on renewable energy sources that were published between the years of 2010 to 2022 through a systematic and statistical review framework to showcase the need for power electronic technologies for the implementation of RES.

Design and Development of a Web-Based Medicine Inventory Information System

The establishment of this company took place in 2011, and it currently has a workforce of 63 individuals. The company distributes goods exclusively to authorized agencies or pharmacies rather than the general public. Only entities with a valid business license can purchase drugs from this company. It should be noted that this company does not produce drugs but rather acquires them from suppliers for resale. There are still challenges in gathering reports on the inflow and outflow of medicine stock data during inventorying. These reports are still reliant on ledger records. Consequently, warehouse staff require considerable time to document reports regarding the arrival and departure of items. This study aims to examine and create a web-based system for managing drug inventory, which is essential for enterprises. Developing this system entails utilizing the Prototyping methodology as a system development approach and the Unified Modeling Language (UML) as a modeling instrument. The activities implemented in this system encompass the management of goods data, incoming goods transactions, outgoing goods transactions, inventory management, goods stock reports, outgoing goods reports, incoming goods reports, and user administration. Based on this study, a web application was developed to address the drug supply system issues at Pharmaceutical Distribution Companies In Bandung.

Data-Driven Short-Term Load Forecasting for Multiple Locations: An Integrated Approach

Short-term load forecasting (STLF) plays a crucial role in the planning, management, and stability of a country’s power system operation. In this study, we have developed a novel approach that can simultaneously predict the load demand of different regions in Bangladesh. When making predictions for loads from multiple locations simultaneously, the overall accuracy of the forecast can be improved by incorporating features from the various areas while reducing the complexity of using multiple models. Accurate and timely load predictions for specific regions with distinct demographics and economic characteristics can assist transmission and distribution companies in properly allocating their resources. Bangladesh, being a relatively small country, is divided into nine distinct power zones for electricity transmission across the nation. In this study, we have proposed a hybrid model, combining the Convolutional Neural Network (CNN) and Gated Recurrent Unit (GRU), designed to forecast load demand seven days ahead for each of the nine power zones simultaneously. For our study, nine years of data from a historical electricity demand dataset (from January 2014 to April 2023) are collected from the Power Grid Company of Bangladesh (PGCB) website. Considering the nonstationary characteristics of the dataset, the Interquartile Range (IQR) method and load averaging are employed to deal effectively with the outliers. Then, for more granularity, this data set has been augmented with interpolation at every 1 h interval. The proposed CNN-GRU model, trained on this augmented and refined dataset, is evaluated against established algorithms in the literature, including Long Short-Term Memory Networks (LSTM), GRU, CNN-LSTM, CNN-GRU, and Transformer-based algorithms. Compared to other approaches, the proposed technique demonstrated superior forecasting accuracy in terms of mean absolute performance error (MAPE) and root mean squared error (RMSE). The dataset and the source code are openly accessible to motivate further research.

Nontechnical Loss Detection for Metered Customers in Alexandria Electricity Distribution Company Using Support Vector Machine

Non-technical losses (NTL) during transmission and distribution (T&D) of electrical energy is a major problem faced by utility companies which is very difficult to fight and detect. For that, more of power utilities spend thousands dollar for research centres to find efficient methods for detecting and controlling abnormalities. Electricity theft and billing irregularities forms the main portion of NTL. With the introduction of smart meter, the frequency of reporting energy consumption data to the utility company has been increased. Incoming and outgoing energy could be monitored and analyzed. Electricity theft is a complex problem with many parameters to be evaluated before implementing any measures to detect and control that. These parameters include some issues like social, economic, regional, managerial, infrastructural, and corruption. In recent years, several data mining and research studies on fraud detection and prediction techniques have been carried out in the electricity distribution sector. Support vector machine (SVM) technique has dominated the research for classifying data and detecting fraudulent electricity customers. SVM technique has good ability in data mining and data classification. The paper objective is to analyze the metered energy consumption data recorded and predict the pattern or the form of daily user’s energy consumption, then using SVM to classify the data whether normal or theft. The suggested technique is then tested using real data from Alexandria Electricity Distribution Company (AEDC). The proposed technique was able to distinguish between healthy and theft cases.

Evolutionary Approach for DISCO Profit Maximization by Optimal Planning of Distributed Generators and Energy Storage Systems in Active Distribution Networks

Distribution companies (DISCOs) aim to maximize their annual profits by performing the optimal planning of distributed generators (DGs) or energy storage systems (ESSs) in the deregulated electricity markets. Some previous studies have focused on the simultaneous planning of DGs and ESSs for DISCO profit maximization but have rarely considered the reactive powers of DGs and ESSs. In addition, the optimization methods used for solving this problem are either traditional or outdated, which may not yield superior results. To address these issues, this paper simultaneously performs the optimal planning of DGs and ESSs in distribution networks for DISCO profit maximization. The utilized model not only takes into account the revenues of trading active and reactive powers but also addresses the active and reactive powers of DGs and ESSs. To solve the optimization problem, a new hybrid evolutionary algorithm (EA) called the oppositional social engineering differential evolution with Lévy flights (OSEDE/LFs) is proposed. The OSEDE/LFs is applied to optimize the planning model using the 30-Bus and IEEE 69-Bus networks as test systems. The results of the two case studies are compared with several other EAs. The results confirm the significance of the planning model in achieving higher profits and demonstrate the effectiveness of the proposed approach when compared with other EAs.

Profitability Analysis Using the Du Pont System Method In the Fast-Moving Consumer Goods (FMCG) Distribution Subsector of a Go-Public Company for The Period 2017-2021

The aim of this study is to analyze the profitability level of Fast-Moving Consumer Goods companies in the Retail and Distributor of Medicines (D111), Rental and Distributor of Food (D112), and Processed Food Distributors (D222) subsectors listed on the Indonesian Stock Exchange in the period 2017-2021 based on Du Pont system analysis. The Du Pont system is an analysis method used to show the interaction between Net Profit Margin (NPM), Total Asset Turnover (TATO), Return on Asset (ROA) and Equity Multiplier in determining the value of Return on Equity (ROE). This type of research is descriptive quantitative using the Du-Pont analysis method. The method used in this study is judgement sampling. Types of data and data sources use secondary data derived from financial statements published by companies that are samples of research and data from the Stock Exchange of Indonesia. Analysis shows that PT. Tigaraksa Satria Tbk has the highest profitability as a Fast-Moving Consumer Goods subsector distribution company. The company's ROE from 2017 to 2020 is higher than the industry average, by 2019 has increased and decreased by 2021. PT. Wicaksana Overseas International Tbk became a Fast-Moving Consumer Goods subsector distribution company with the lowest profitability performance of the five samples, based on analysis carried out by the company's ROE from 2017 to 2020 experienced a decline below the industry average and by 2021 a decrease slightly above the industrial average.

Virtual Prosumers’ P2P Transaction Based Distribution Network Expansion Planning

The deployment of prosumers with distributed energy resources (DERs) has facilitated the prosumer-centric transactive market, giving rise to the consequent necessity for the coordination between prosumers and the distribution networks. This paper proposes an incentive-based expansion planning method considering virtual peer-to-peer (P2P) transaction among prosumers, which is characterized as a tri-level planning-operation-transaction framework. Each prosumer optimizes its internal response of DERs and external P2P transaction jointly, formulating virtual P2P transaction. Under such a paradigm, the distribution company (DISCO) identifies the optimal expansion planning in the network assets, while the independent distribution system operator (IDSO) is responsible for the optimal operation of the expanded distribution networks. To derive appropriate incentives for each prosumer, the DISCO and IDSO allocate long-term investment network charges and short-term operation network charges on prosumers, along with the designed financial transmission rights coupling multiple time scales. Through such incentives, self-profit driven virtual transactions can relieve operation problems and postpone expansion planning, acting as a short-term alternative. Moreover, a risk-based approach is proposed for prosumer to flexibly change strategy according to different risk preference. Finally, results from the case study demonstrate the superiority and effectiveness of the proposed method in the collaborative application of virtual transaction in the expansion planning.

Improving the reliability of power distribution substations equipment for life extension by considering Condition Based Maintenance

Maintenance of aged power equipment is a proven technique for establishing systems reliability and longevity. It is extensively relevant when combined with Condition Based Maintenance (CBM) approaches for predicting power system infrastructure life, especially with imminent obsolescence. The research focuses on distribution companies with mixed aged power infrastructure, which continuously degradate. A significant setback in older systems is the scarcity of replacement parts leading to unplanned investment in substantial infrastructure due to unexpected failed components that are no longer in production. To guarantee excellent infrastructure health in older equipment, utility companies should consider applying Condition Based Maintenance (CBM) using Artificial Neural Network (ANN) to stabilize older equipment and restore malfunctioning assets. Studies have shown that the life span of older equipment can be extended when adequate maintenance strategies are put in place through the prediction of possible failures using equipment inspections and risk matrix. CBM's strategy improved the Key Performance Indicator (KPIs) System Average Interruption Duration Index (SAIDI) has improved by lowering the average monthly customers power interruptions by 19,15 % lesser time spent without electricity. The System Average Interruption Frequency Index (SAIFI) was improved by lowering the average monthly power interruptions frequency by 20,63% lesser outage frequency. The Distribution Supply Loss Index (DSLI) was improved by dropping the average monthly power losses by 7,5% power losses saved. The Customers Average Interruption Duration Index (CAIDI) was improved by lowering the average customer interruption by 36.1% improvement from the average period before the CBM optimization. The Average System Availability Index (ASAI) was improved by shortening the average annual interruption durations by 1,36%. The ASUI was improved by increasing the average duration of electrical power availability by 1.28%. The optimization of CBM was measured over 24 moths period.

Optimization of position and rating of shunt and series connected FACTS devices for transmission congestion management in deregulated power networks

<abstract><p>Transmission congestions are caused by electricity trading between generators and distribution companies in a deregulated environment. Power system operation and security in liberalized scenarios are maintained by removing branch overloads. A flexible alternating current transmission system (FACTS) controller is installed in a suitable location to redistribute the power flow among the transmission lines so that the power flows are brought within the capacity of the lines. In this work, series-connected thyristor-controlled switched compensators (TCSCs) and shunt-connected Volt-Ampere reactive (VAR) static compensators (SVCs) are installed in appropriate locations to alter the power flow patterns and to remove overloads. It is proposed to reduce the overload of transmission lines by locating series and shunt connected FACTS devices at proper locations. The size and location of TCSC and SVC devices greatly affect their ability to meet a congestion management goal. An optimization process optimizes the location and size of these devices to maximize the congestion mitigation benefits of the TCSC and SVC controllers. In this work, the whale optimization algorithm (WOA) is used to optimize the value of the objective function by appropriately choosing the location and size of the FACTS controllers. This algorithm has a few parameters that are tuned to give the best overall results. A WOA-based method is proposed to optimize the size and location of the FACTS devices and is implemented on the IEEE-30 bus test case. The results were compared and found to be improved with those of other algorithms such as the particle swarm optimization algorithm (PSO) and the firefly algorithm (FFA).</p></abstract>

Evaluation of Harmonic Currents and Network Impedance using Norton Model in an Unidentified Network Configuration

This paper presents a study that focuses on the evaluation of the analysis of harmonic currents emitted by loads and the harmonic impedance of a real electrical network using the Norton model. The primary advantage of employing this model lies in its ability to address scenarios where the complete network configuration, particularly from the distribution side, is not known. By calculating currents and voltages at the supply-side for two different operating conditions, the harmonic current content and the network impedance can be evaluated. To induce variations in operating conditions, a switching shunt capacitor is utilized. The results show that the fifth and the seventh harmonics clearly appear with values of 189.382 A and 135.073 A, respectively, while the other harmonics have values close to zero. The harmonic impedance also shows the presence of the fifth and the seventh harmonics with values of 1865.681 Ω and 4289.3 Ω, respectively. The main contribution of this paper focuses on converting the real electrical network into numerical data that can be accepted by the software. The components of the network model have to be carefully selected to understand the harmonic analysis and to success the simulation, which is conducted using the EMTP-ATPDraw program. The results of this investigation can be used as a database for electrical transmission and distribution companies in case of making any changes in the network, such as installation of new loads or cables, or in case of making measurements.

The Direction of the City Gas as Clean Energy in Indonesia with the Work Force as the Moderator

The distribution of city gas to consumers as clean energy has expanded. Despite its expansion, the trend can run into a drop in consumer demand. This can be the case if factors that control its growth are improperly managed. Hence, regulating the variables are of critical relevance. The data movement from year to year continues to show an expanding tendency with reference to the Indonesian city gas industry. This study can further improve knowledge of Indonesia's city gas distribution industry and to paint a clearer picture of a number of latent variables that need to be taken into account in order to distribute natural gas to Indonesian cities as efficiently as possible. The Structured Equation Technique (SEM)was the methodology employed in this investigation. In a more detailed explanation, the association between indicators and latent variables is examined using path analysis, which is derived from multivariate regression, in order to assess the validity of the multiple regression model. In keeping with the research methodology, data from indicators of city gas distribution companies during the period 2010-2020 were grouped and sorted by the Indonesian Central Statistics Agency. These indicators included income, the number of employees paid, the volume of city gas distributed, and operational costs. The purpose of this research is to produce information that can be used by the government and other stakeholders to accelerate the development of Indonesia's gas distribution business. This study's novelty or worth lies in its ability to shed light on the influence of latent variables that hold the status as moderating variables. Study limitations: Because non-disclosure primary data are not readily available and secondary data are scarce, it is assumed that the information from the Indonesian Central Statistics Agency is reliable and can be used to describe the explanatory variables of the city gas distribution industry in Indonesia.

Comparative Analysis of DG Units with Shunt Capacitive Banks on the Improvement of Voltage Profiles in Distribution Networks.

Electrical distribution systems’ reliability is a critical parameter for electrical networks and their end-users. Among the different parameters associated with these systems’ reliability, voltage profile is most commonly affected in the electrical network due to different internal and external parameters such as lines and feeders’ impedance, system overloads, and increments on end-users. A poor voltage profile can have adverse impacts on the end user, such as long-term harm to their electric and electronic devices. For both consumers and companies that provide electricity, a low voltage profile thus leads to a loss of power. The Distributed Generation (DG) system is a viable option to improve voltage profiles while conserving the environment by unlocking the usage of any renewable energies following recent technological advancements and environmental concerns. This article proposes an alternative method to enhance voltage profiles in a distribution network (Abuja Electricity Distribution Company, AEDC) by comparing the most effective approach for power losses and voltage profile compensation through DGs and capacitor banks. Detailed simulations are conducted to explain and validate the results with the optimum system voltage improvement and loss reduction. This work has found that the voltage profiles are more enhanced with DG units compared to capacitor banks. The power losses were reduced from the initial value of 1196.4 kW to 762.4 kW with a saved energy of 36.3% with DG-unit as compared to FC with a power loss reduction of 1005.2 kW (energy saved of 16.0%).