Smart Grid Implementation Research Articles

The One-Node Approach to Implement Smart Grid Functions for Residential Loads

The One-Node Approach to Implement Smart Grid Functions for Residential Loads

ANÁLISE SOBRE A INDÚSTRIA 4.0 NA DISTRIBUIÇÃO DE ENERGIA E O FUTURO DAS REDES INTELIGENTES

The technological evolution brought about by Industry 4.0 has significantly impacted several sectors, including the energy sector. The introduction of smart grids into the energy distribution system offers solutions to increase efficiency, integrate renewable sources, and reduce losses. These networks use technologies such as automation, big data, and the Internet of Things to modernize the way energy is managed and distributed. The overall objective of this research was to analyze the impact of Industry 4.0 on energy distribution, focusing on the implementation of smart grids in Brazil. To achieve this objective, the methodology adopted was a literature review with a qualitative approach, using articles published between 2020 and 2024, obtained from databases such as Lilacs, Periódicos Capes, and Scielo. The research addressed the benefits and challenges of modernizing the Brazilian electricity system, with an emphasis on the integration of renewable sources, such as solar and wind, and on combating non-technical losses. The results indicate that smart grids contribute to greater efficiency in the energy distribution system, enabling real-time management, in addition to promoting better security against failures and cyber threats. Another relevant point identified was the importance of training professionals capable of implementing these new technologies. The research concludes that the adoption of Industry 4.0 in the energy sector is a necessary step towards the sustainability and modernization of the electrical system in Brazil.

Implementation of ANFIS-based UPQC for Power Quality and Thermal Management Enhancement in the Distribution System

Conventional distribution systems generally operate with voltage and current waveforms being sinusoidal, though they slightly deviate from the ideal sinusoidal waveform, which is measured as distortion. The increase in power demand has led to the local generation and storage of power (Micro Grid systems). For its adoption, we need to implement smart grid architecture. Power electronics is a technologically sound way to limit different kinds of power quality (PQ) disturbances. It can also be used to control power flow, boost energy transmission capacity, enhance dynamic behavior and voltage stability, and ensure better power quality at distribution within established bounds. Unified Power Quality Conditioners (UPQC), one of the well-known Flexible AC Transmission System (FACTS) devices, are typically used to address problems in distribution systems such as voltage surges, flickers, neutral current reduction, and PQ. Additionally, thermal management is crucial for maintaining system stability and preventing overheating. While dealing with sensitive loads, a UPQC injects harmonics into the system, which can compromise system stability. This article describes an artificial neural network with harmonics elimination techniques for a modified UPQC connected with a Smart Grid. The performance of the proposed system is evaluated using MATLAB/Simulink software.

Secure smart grid implementation with automatic data integrity attack location prediction and exalted energy theft detection

Smart grid systems use digital communication technology to efficiently monitor and manage electricity distribution. However, there is a need for improve the robustness of smart grid systems. Hence a novel “Secure Smart Grid Implementation with Automatic Data Integrity Attack Location Prediction and Exalted Energy Theft Detection” has been proposed. Current detection methods are not good at identifying data integrity attacks. So a novel Automatic Deterministic Attack Location Prediction Model detects data integrity attacks using a Stacked Watermarking BiGRU-based Deep Deterministic Q network, extracting system matrix and state time series variation. Moreover, Energy theft detection algorithms, which are intended to detect dishonest clients, provide erroneous findings because of linear interpolation processes and randomised near misses, which ignore important data points. Thus a novel Exalted Energy Theft Detector with Secure Encoding is introduced where Amortized Multicode GAN method secures smart grids by detecting energy theft and preventing firmware code modifications, utilising fractional multi-level quantum encoding to identify injection locations. As a result, the proposed model has an accuracy of 97.1%, recall of 96.25%, error rate is 1.36%, F1-score is 96.20%, sensitivity is 96.10%, specificity is 96.10%, MAPE is 0.48%, MSE is 0.0001 and RMSE is 0.017.

Challenges and Opportunities in Implementing Smart Grid Technologies in Kurdistan: A Comprehensive Review

Challenges and Opportunities in Implementing Smart Grid Technologies in Kurdistan: A Comprehensive Review

Enhancing Distribution Grid Efficiency and Congestion Management through Optimal Battery Storage and Power Flow Modeling

The significant growth in demand for electricity has led to increasing congestion on distribution networks. The challenge is twofold: it is needed to expand and modernize our grid to meet this increased demand but also to implement smart grid technologies to improve the efficiency and reliability of electricity distribution. In order to mitigate these congestions, novel approaches by using flexibility sources such as battery energy storage can be used. This involves the use of battery storage systems to absorb excess energy at times of low demand and release it at peak times, effectively balancing the load and reducing the stress on the grid. In this paper, two optimal power flow formulations are discussed: the branch flow model (non-convex) and the relaxed bus injection model (convex). These formulations determine the optimal operation of the flexibility sources, i.e., battery energy storage, with the objective of minimizing power losses while avoiding congestions. Furthermore, a comparison of the performance of these two formulations is performed, analyzing the objective function results and the flexibility operation. For this purpose, a real Spanish distribution network with its corresponding load data for seven days has been used.

Home-personas meet energy narratives of demand response: Uncovering mismatches between Swedish stakeholder expectations and everyday life

Smart grids are proposed to enable the integration of renewables and facilitate the energy transition. Households have been pointed out as a significant resource for demand response, that is to adapt their electricity consumption based on the status in the grid. This article analyses narrative mismatches in the context of smart grid implementation in Sweden. We compare policy narratives on the role of homes in the future energy system with home personas, emerging from interviews with households. The policy narratives envision households to become either actively engaged in time-shifting motivated by information and incentives, or bypassed through automation. The home personas, although seemingly similar, show great diversity, being well informed about their electricity use, concerned regarding the safety of technology, preferring to manage flexibility themselves, and reluctant to give up control. Several dissonances are identified between narratives and the home personas regarding smart meter communication, energy awareness, trust, agency, and control, that need further attention for demand response to be realised. The analysis illustrates how policy visions of the home in the future grid would encounter severe challenges in living up to values and characteristics of real households. Policy thus needs to acknowledge households as a diverse group to ensure a sustainable and democratic energy transition. We encourage the use of home personas to substantiate this diversity.

Optimizing smart grid performance: A stochastic approach to renewable energy integration

Smart grids offer numerous possibilities for developing and executing sustainable and efficient electricity supply chains that exhibit increased resilience to disturbances. The exploration of the Electric Supply Chain Network (ESCND) design problem using smart grids has been limited. This article aims to tackle this challenge through the application of a robust multi-objective optimization approach, encompassing three economic goals (maximizing profit), environmental goals (minimizing greenhouse gas emissions), and resilience goals (maximizing network resilience). Additionally, the optimization process takes into account the dual objectives of maximizing efficiency and minimizing energy loss by incorporating relevant cost considerations. The proposed methodology incorporates distinctive features of smart grids, such as demandside management programs, microgrid structures, bidirectional distribution lines, and consumer–supplier nodes. It addresses various interconnected decisions, including location placement, capacity expansion, load allocation, and pricing. To solve the formulated model, a potent combination of multi-objective optimization methods based on cutting-plane algorithms and AUGMECON2 is introduced. Subsequently, the proposed model and solution approach are applied to a practical case study, and the obtained results are comprehensively examined. The findings suggest that, despite potential contradictions between economic and environmental objectives, the implementation of smart grids can concurrently improve environmental performance and network flexibility.

Smart grid deployment: from a bibliometric analysis to a survey

Smart grids are one of the last decades' innovations in electrical energy. They bring relevant advantages compared to the traditional grid and significant interest from the research community. Assessing the field's evolution is essential to propose guidelines for facing new and future smart grid challenges. In addition, knowing the main technologies involved in the deployment of smart grids (SGs) is important to highlight possible shortcomings that can be mitigated by developing new tools. This paper contributes to the research trends mentioned above by focusing on two objectives. First, a bibliometric analysis is presented to give an overview of the current research level about smart grid deployment. Second, a survey of the main technological approaches used for smart grid implementation and their contributions are highlighted. To that effect, we searched the Web of Science (WoS), and the Scopus databases. We obtained 5,663 documents from WoS and 7,215 from Scopus on smart grid implementation or deployment. With the extraction limitation in the Scopus database, 5,872 of the 7,215 documents were extracted using a multi-step process. These two datasets have been analyzed using a bibliometric tool called bibliometrix. The main outputs are presented with some recommendations for future research.

Development and Implementation of an ESP32 IOT-Based Smart Grid for Enhanced Energy Efficiency and Management

Development and Implementation of an ESP32 IOT-Based Smart Grid for Enhanced Energy Efficiency and Management

Implementing Smart Grid Technology in Developing Countries: Challenges, Opportunities, and Pathways to Sustainable Energy Solutions

The integration of smart grid technology is becoming crucial for developing countries to address the increasing energy demands and to transition towards sustainable and reliable electricity systems. This paper discusses the significant challenges these nations face, such as outdated infrastructure, high transmission and distribution losses, and limited access to electricity. With electricity consumption projected to grow by over 50% by 2030 in emerging markets and developing economies, smart grids offer benefits including enhanced reliability, reduced losses, and better integration of renewable energy sources. However, high upfront costs, lack of skilled personnel, inadequate regulatory frameworks, and resistance to change pose substantial barriers. This study explores the potential of smart grids to transform energy systems, presenting case studies of successful implementations and highlighting strategies for overcoming barriers. Emphasis is placed on innovative financing models, capacity building, technology leveraging, and stakeholder engagement as pathways to sustainable smart grid deployment.

Detection and confirmation of electricity thefts in Advanced Metering Infrastructure by Long Short-Term Memory and fuzzy inference system models

The successful implementation of Smart Grids heavily relies on energy efficiency, particularly through the Advanced Metering Infrastructure (AMI) and Smart Electricity Meters (SEM). However, cyber-attacks pose a threat to SEM, with electricity theft being a primary motivation. Despite the valuable data provided by SEM for analytical purposes, existing methods to identify theft involve cumbersome and costly on-site inspections. This research proposes an electricity theft detection model using the Long Short-Term Memory (LSTM) network. The model employs a collective anomaly approach, defining prediction errors through a threshold and forecast horizon. Suspicious consumption profiles are analysed, and a fuzzy inference system (FIS) implemented in MATLAB 2021b is used to model security risks based on these profiles. The study utilizes energy consumption data from four diverse consumer profiles (consumers 1, 2, 3, and 4) to develop consumer-specific LSTM models for detection and an FIS model for confirmation. Tampered consumer data is identified and confirmed based on selected AMI parameters. While all consumers exhibit suspicious profiles at times, only consumers 2 and 3 are confirmed as engaging in electricity theft. This research provides a robust approach to detecting and verifying fraudulent consumption profiles within the context of AMI, offering a more reliable dimension to theft detection and confirmation.

Assessing the performance of hydro-solar hybrid (HSH) grid integration: A case study of Bui Generating Station, Ghana

Renewable energy sources (RES) are rapidly expanding as a result of energy security and environmental concerns. Despite their numerous benefits, they pose significant challenges to power grid operation. Ghana is dedicated to reaching a 10 % renewable energy mix target by 2030 to promote low-emission development. Ghana has the first hybrid power plant made up of 400MW hydropower plant and 50 MW solar PV plant supplying power to the national grid. The study designs a hydro-solar hybrid system configuration for Ghana's Bui generation unit, using data from the 50 MW ground-mounted solar PV and 133.33 MW hydropower units to assess the performance and challenges of the hydro-solar hybrid system at the Bui Generating Station. Methodology involves modeling and simulation in the DIgSILENT power factory software environment. Utilizing quasi-dynamic simulations, the study investigates variations in active power generation, voltage fluctuations, grid losses, and reactive power generation. Results highlight technical challenges such as voltage fluctuations and power loss, and propose mitigation measures. Comparisons between simulated and field data reveal discrepancies attributed to factors such as temperature effects, dust accumulation, and conductor resistance. Mitigation strategies are proposed, including energy storage expansion, smart grid implementation, advanced control techniques, FACTS device deployment and grid monitoring improvements. Despite limitations in data availability and simulation accuracy, the study underscores the system's reliability and provides insights for enhancing renewable energy integration in the region. Generally, the study contributes to advancing renewable energy integration efforts, with implications for sustainable development and climate action in Ghana and West Africa at large.

Smart AC-DC Coupled Hybrid Railway Microgrids Integrated with Renewable Energy Sources: Current and Next Generation Architectures

In recent years, there has been increasing interest in integrating the smart grid concept into railway networks, which has been driven by the need to enhance energy efficiency and reduce air pollution in such energy-intensive systems. Consequently, experts have actively sought innovative solutions with which to tackle these challenges. One promising strategy involves integrating renewable energy sources (RESs), energy storage systems (ESSs), and electric vehicle charging stations (EVCSs) into current electric railway systems (ERSs). This study begins by examining the concept of implementing smart grids in railway systems through bibliometric analysis. It then delves into the realization of a hybrid railway microgrid (H-RMG) designed to enhance power flow capacities, improve energy efficiency, and address power quality issues in traditional AC railway networks. This paper introduces various future AC–DC-coupled hybrid railway microgrid (ADH-RMG) architectures centered around a shared DC bus acting as a DC hub for upgrading conventional AC railway systems utilizing interfacing static converters. Through an exploration of different possible ADH-RMG configurations, this research aims to offer valuable insights and a roadmap for the modernization and reconstruction of existing railway networks using smart grid technologies. The integration of RESs and EV charging infrastructures within the ADH-RMG concept presents a promising pathway toward establishing more sustainable and environmentally friendly railway systems.

EFTA: An Efficient and Fault-Tolerant Data Aggregation Scheme without TTP in Smart Grid

Abstract With the rapid construction and implementation of smart grid, lots of studies have been conducted to explore how to ensure the security of information privacy. At present, most privacy-preserving data aggregation schemes in smart grid achieve privacy data protection through homomorphically encrypted data aggregation. However, these data aggregation schemes tend to rely on a trusted third party (TTP), and fail to efficiently handle the case of a meter failure. Besides, they are less flexible for overall user management, and resistance to collusion attacks needs to be improved. In this paper, we propose an efficient and robust privacy-preserving data aggregation scheme without TTP, called EFTA. Overall, the scheme eliminates the reliance on a TTP, combines with Shamir threshold secret sharing scheme to increase overall fault tolerance, supports flexible and dynamic user management, and effectively defends against entity initiated collusion attacks. According to security and performance analysis results, the scheme proposed in this paper meets the multiple security requirements of smart grid, and is more efficient in terms of overall overhead compared to the existing privacy-preserving data aggregation schemes.

Paper Certificate SMART GRID framework for Pakistan” Perception to practicality

As moving further into the digital age of the 21st century, Pakistan. and rest of the world is becoming increasingly dependent upon electric power. Despite the colossal potential of its energy resources, still Pakistan remains energy deficient. As a consequence, the crucial energy supplies today are not adequate to meet even the present demand. Similarly Line losses are a major issue in Pakistan. We are losing 35 to 40 billion per annum due to inefficiency in power distribution [4], While continuing blackouts or load shedding as it is commonly known, has always been a staple of daily life in Pakistan (figure 1). the dilemma has turned out to be acute since the preceding couple of months. The only way to tackle such colossal plight collectively is to implement smart grid infrastructure into our system. Also integrated use of smart grid would enhance the cooperation between the different sectors of the energy mix to provide an optimal solution in the electrical energy scenario of Pakistan. Smart grid is nothing but a concept/idea needed to run our present day Electrical power system in a more effective, more systematic and less error prone way. To achieve this way of wisdom, we must keep the end or the output required in our mind. Accommodating the present infrastructure with newer and more reliable modern day technologies are also a target of the Smart grid planning. Similarly Clean, green energy structure is an inherent requirement of smart grid development [6].It would provide a long term economic and social benefit to the existing structure of the society.

Review of methods for modeling and control of cyber-physical systems in multi-energy microgrids

The article analyzes the development of methods for modeling and control of multi-energy microgrids through cyber-physical systems. We used the methods of literature review and meta-analysis based on publications from international databases Scopus and Web of Science, Russian database eLibrary, digital platform IEEEXplore et al. According to the analysis, Smart Grid implementation drives the development of cyber-physical systems. As summarized in this study, control interfaces, data transmission channels, and remote debugging ports are vulnerable parts of IoT devices that can possibly be attacked by intruders. A review of the recent publications in this field finds multi-agent technologies to be an effective approach not only for the operational control of multi-energy microgrid modes, but also for the construction of its reliable information network at the level of medium and low voltage systems. In the field of distributed energy systems, literature review of information technology indicates that the more capabilities are added to receive and process various kinds of information (transaction data, mode parameters, status of controllers, etc.) from external sources, the more vulnerable a multi-energy microgrid is to any cyber threats. Modern mathematical methods such as artificial intelligence, dynamic optimization, and multi-agent approaches should be used to effectively solve the problem of load distribution between different energy sources with cost minimization.

Power flow analysis in a distributed network for a smart grid system

<span>This article presents the implementation of a hybrid renewable energy-based smart grid in a distributed system. Photovoltaic (PV) and wind generation are variable and time-dependent, yet they are very efficient and correlated, making them perfect for a two-source hybrid system. To maximize the generated power, using the maximum power point tracker (MPPT) technique, the incremental conductance (IC) algorithm is employed. The proportional integral (PI)-based MPPT controller is chosen to improve the efficiency of conventional MPPT controllers. A battery system is implemented as an energy management system (EMS) to aid in transferring or managing the high load throughout peak and off-peak hours. The proposed system uses an optimization technique called genetic algorithm (GA) to control the inverter voltage. The GA-tuned PI controller performs efficiently and has less harmonic distortion than the traditional sinusoidal pulse width modulation (SPWM) control method. The designed system uses real-time measurable parameters as inputs and is simulated in Matlabtool. The system generates 42 kW of solar power and 250 kW of wind power; the total harmonic distortion (THD) value is 5% less than the SPWM technique. For future work, flexible alternating current transmission system (FACTS) devices can improve the power quality and lower the oscillations.</span>

Fuzzy cognitive map-based modelling for smart grid implementation in India

Fuzzy cognitive map-based modelling for smart grid implementation in India

ОПТИМИЗАЦИЯ УМНЫХ СЕТЕЙ (SMART GRIDS) С ИНТЕГРАЦИЕЙ ВОЗОБНОВЛЯЕМЫХ ИСТОЧНИКОВ ЭНЕРГИИ

The article considers the issues of smart grid optimization with renewable energy sources (RES) integration. Particular attention is paid to solving problems associated with the instability of RES generation and the need to ensure the reliability of the power system. Various approaches to demand management, the use of energy storage systems and distributed energy resources are analyzed. The challenges of cybersecurity and grid sustainability in the context of RES integration are considered. The article also provides case studies and simulation results demonstrating the effectiveness of the proposed solutions. The economic and environmental aspects of smart grid implementation are assessed.