Grid Implementation Research Articles

Strategic deployment of energy storage systems in the Indian power grid

PurposeThe transition from centralized thermal power plants to distributed renewable energy sources complicates the balance between power supply and load demand in electrical networks. Energy storage systems (ESS) offer a viable solution to this challenge. This research aims to analyze the factors influencing the implementation of ESS in the Indian smart grid.Design/methodology/approach To analyze the factors affecting ESS deployment in the grid, the SAP-LAP framework (situation-actor-process and learning-action-performance) integrated with e-IRP (efficient-interpretive ranking process) was used. The variables of SAP-LAP elements were selected from expert opinion and a literature review. Here, e-IRP was utilized to prioritize elements of SAP-LAP (actors in terms of processes and actions in terms of performance).Findings This analysis prioritized five stakeholders in the Indian power industry for energy storage implementation: government agencies/policymakers, ESS technology developers/manufacturers, private players, research and development/academic institutions, and contractors. Furthermore, the study prioritized the necessary actions that these stakeholders must take.Research limitations/implications The study’s findings help identify actors and manage different actions in implementing grid energy storage integration. Ranking these variables would help develop a strategic roadmap for ESS deployment and decisions about adopting new concepts.Originality/value It is one of the first attempts to analyze factors influencing ESS implementation in the power grid. Here, qualitative and quantitative methodologies are used to identify and prioritize various aspects of ESS implementation. As a result, the stakeholder can grasp the concept much more quickly.

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.

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.

Comparison of optimized effective potential with inverse Kohn-Sham method for Hartree-Fock exchange energy.

The inverse Kohn-Sham (inv-KS) density-functional theory for the electron density of the Hartree-Fock (HF) wave function was revisited within the context of the optimized effective potential (HF-OEP). First, we clarify the relationship between the inv-KS and the HF-OEP within the framework of the potential-functional theory. The similarities and the differences of the approaches are then discussed on the basis of their methodological details, which motivates comparisons of the wave function provided by each method. Next, the real-space grid implementations of the inv-KS and the HF-OEP are addressed for the comparisons. The total HF energies EHF[{φiinv-KS}] for the wave functions φiinv-KS on the effective potentials optimized by the inv-KS are computed for a set of small molecules. It is found that the mean absolute deviation (MAD) of EHF[{φiinv-KS}] from the HF energy is clearly smaller than the MAD of EHF[{φiOEP}], demonstrating that the inv-KS is advantageous in constructing the detailed structure of the exchange potential υx as compared with the HF-OEP. The inv-KS method is also applied to an ortho-benzyne radical known as a strongly correlated polyatomic molecule. It is revealed that the spin populations on the atomic sites computed by the UHF calculation can be faithfully reproduced by the wave functions on the inv-KS potential.

Assessing the performance of three experimental methods to investigate air path inside wall assemblies

Air leakages in buildings’ envelopes can lead to an over-consumption of energy and to additional issues such as moisture damage and poor indoor environment. The leakage air flow rate is usually assessed at the building scale using a pressurization test and leakage locations are commonly detected by infrared thermography or smoke. However, little is known about the air paths within wall assemblies, despite the need for detailed experimental data to validate numerical models for the coupled heat, moisture and pollutants transfers. One of the reasons is the difficulty to find adapted and robust experimental methods.In this paper, three experimental laboratory approaches are tested on simple light-wall assembly configurations: the implementation of three-dimensional grids of thermocouples and relative humidity sensors within the wall, and the use of a micro-particle tracer. The results are compared with each other as well as with numerical simulations.It was found that thermocouple grid has limited intrusiveness, good accuracy and response time but results are subject to flow fluctuations. Moreover, heat capacity and conductive transfer within materials complicate the correlation between heat and air transfers. Humidity sensors grid avoids the latter issue but is intrusive, overestimating air dispersion. The micro-particle tracer has the advantage of being non-intrusive and less impacted by flow fluctuations but its ability to track the air flow is strongly linked with the insulation filtration properties and the flow velocity. Overall this method seems to provide the best results but it is also the most complex and time-consuming one.

Implementation of Anti-Abrasion Grid in Sumsel-5 580 t/h CFB Boiler (Reliability and Performance Evaluation)

CFB Boiler operated with turbulence model and fast fluidization. This model regime gives CFB boiler great heat distribution and increase boiler efficiency. Disadvantage of regime is due boiler furnace feed with coal, sand and limestone as bed material. Bed material with the high velocity and turbulence regime can be harmful for water and steam tube inside of furnace. Operational challenges such as abrasion and abrasion of boiler components will significantly affect their efficiency and increase possible force shutdown because of boiler tube leakage. This research investigated the implementation of anti-abrasion grids perpendicular to water wall tubes of Sumsel-5 CFB Boiler, installed horizontally and vertically to mitigate abrasion and enhance overall performance. The result showed that anti-abrasion grid installation could increase the lifespan of the CFB boiler, reduce the abrasion rate by more than 50%, and lead to enhanced boiler performance by 0,4%. Anti-abrasion grid installation could also reduce the maintenance cost due to water wall tube repair.

Impact of scatter radiation on spectral quantification performance of first- and second-generation dual-layer spectral computed tomography.

To assess the impact of scatter radiation on quantitative performance of first and second-generation dual-layer spectral computed tomography (DLCT) systems. A phantom with two iodine inserts (1 and 2mg/mL) configured to intentionally introduce high scattering conditions was scanned with a first- and second-generation DLCT. Collimation widths (maximum of 4cm for first generation and 8cm for second generation) and radiation dose levels were varied. To evaluate the performance of both systems, the mean CT numbers of virtual monoenergetic images (MonoEs) at different energies were calculated and compared to expected values. MonoEs at 50 versus 150keV were plotted to assess material characterization of both DLCTs. Additionally, iodine concentrations were determined, plotted, and compared against expected values. For each experimental scenario, absolute errors were reported. An experimental setup, including a phantom design, was successfully implemented to simulate high scatter radiation imaging conditions. Both CT scanners illustrated high spectral accuracy for small collimation widths (1 and 2cm). With increased collimation (4cm), the second-generation DLCT outperformed the earlier DLCT system. Further, the spectral performance of the second-generation DLCT at an 8cm collimation width was comparable to a 4cm collimation on the first-generation DLCT. A comparison of the absolute errors between both systems at lower energy MonoEs illustrates that, for the same acquisition parameters, the second-generation DLCT generated results with decreased errors. Similarly, the maximum error in iodine quantification was less with second-generation DLCT (0.45 and 0.33mg/mL for the first and second-generation DLCT, respectively). The implementation of a two-dimensional anti-scatter grid in the second-generation DLCT improves the spectral quantification performance. In the clinical routine, this improvement may enable additional clinical benefits, for example, in lung imaging.

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.

MODERNIZAÇÃO DA DISTRIBUIÇÃO DE ENERGIA NO AMAZONAS: A REVOLUÇÃO DAS SMART GRIDS

The Smart Grids network has introduced a proven power system based on a modernized power supply system with the introduction of advanced data information and communication technologies. Therefore, the general objective of the research is to highlight the benefits of modernizing the energy measurement process in Amazonas through the implementation of the smart grids device. Data production occurred through documentary and bibliographical research, thus the study was classified as qualitative, in addition, it was necessary to carry out documentary research carried out in the public information database of the National Electric Energy Agency (Aneel) and the Brazilian Association of Electricity Distributors (ABRADEE). It is concluded that the SG system are highly integrated intended to provide reliable and quality energy in an economical and sustainable way, include better quality of energy transmission/distribution from power generation to end users, with energy flow and optimized efficiency. In addition to modern automation, it offers two-way communications, advanced monitoring and control to optimize power quality issues.

Electrochemical Synthesis of Hollow Nanoparticles via Anodic Transformation of Metastable Core-Shell Precursors.

Recent advances in electrosynthesis of nanomaterials expanded structural and compositional variations accessible by the electrochemical method; however, reliably synthesizable morphological variety fall shy of that available by conventional solvothermal synthesis. In this communication, electrochemical preparation of surfactant-free hollow nanoparticles is demonstrated. By anodic conversion of core-shell precursors with metastable cores, hollowed nickel nanoparticles with uniform dimensions were synthesized and characterized. Implementation of TEM grids as the working electrodes, identical location tracking of the morphological evolution of single particles to anodic stimulus has been demonstrated. The synthesized nanoparticles were employed as catalysts for the alkaline hydrogen evolution reaction and exhibited catalytic rates that compare favorably to the Pt/C benchmark. This marks the first pure electrochemical synthesis of hollow nanoparticles and shall contribute to the structural diversification of electrosynthesized nanomaterials.

Current and future development of thermal grids in Switzerland: an organizational perspective

IntroductionThermal grids are key to decarbonizing heating and cooling. However, their development is a complex socio-technical process. This study aims to (1) understand the thermal grid ecosystem’s development under changing political, economic and cultural frame conditions, (2) elicit actors’ perception of options for future development, and (3) identify concrete problem situations for the future development of thermal grids and describe how to address them.MethodsWe draw on 18 semi-structured interviews with decision-makers in utilities, municipal administrations, planning and engineering companies and intermediary organizations.ResultsWith increased strategic importance of thermal grids, the ecosystem has been in a phase of rapid growth and professionalization in the last 10–15 years. This is reflected in a rapid increase in the number of grids, but also in capability and capacity building and greater quality standards. This transformation has been supported by a resource pool (e.g., knowledge base, capacities and capabilities, networks or decision-support tools), built partly through the value network’s activities and partly through purposeful orchestration by associations, authorities, utilities and other actors. While policy developments, energy price fluctuations and changes in customer perceptions spurred demand, thermal grid development is limited by supply-side constraints, especially a skill shortage. Four interrelated problem situations were identified: (1) Municipalities lack the resources to manage the implementation of their energy strategies. (2) The modernization of thermal grids and integration of low-carbon heat sources entails high transaction costs. (3) The implementation of thermal grids is subject to delays and quality risks, with consequences for the timely achievement of decarbonization goals. (4) Customers face uncertainty on available options, as well as on the systemic impacts of their decisions.DiscussionBased on current practices, suggestions by the interviewees, as well as a comparison with the international literature, we identify four development areas to address these problem situations: (1) Empower and support municipalities. (2) Manage the scarcity of qualified workforce. (3) Leverage digital technology for the planning, realization and operation of thermal grids. (4) Pilot technological and organizational innovations together. This complements the set of previously suggested measures to support the development of thermal grids, which focused strongly on technical and regulatory aspects.

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

Statistical pathways to low-carbon cities: Analyzing renewable integration, energy-efficient design, and job creation

To address the existing gap in understanding the intricate dynamics of resource management in Cloud Fog Computing (CFC)-driven Smart Grids (SG), this study introduces an innovative adaptive framework integrating Genetic Optimization Algorithm (GOA) and Cuckoo Search Optimization Algorithm (CSOA), aiming to optimize response times and enhance overall efficiency. In the domain of contemporary energy grids, the implementation of intelligent grids (IG) has ushered in a new era of dependable, streamlined, eco-friendly, and economically viable electric services. These grids constitute a fundamental facet of present-day energy resources. Moreover, the advent of cloud and mist computing (CMC) provides on-demand access to computational resources. Overcoming associated challenges, CMC not only delivers advantages like cost-effectiveness, energy conservation, scalability, flexibility, and adaptability but also presents an innovative model for resource management in IG. This study introduces a CMC-driven strategy for managing resources in IG by digitally replicating key grid components. The proposed framework aims to furnish diverse computational services for resource management within IG through a hierarchical arrangement of CMCs. Additionally, this investigation scrutinizes and simulates two optimization approaches: the cuckoo search and grasshopper optimization algorithms. These algorithms operate on an adaptive machine learning mechanism designed to balance the load, and the study meticulously compares their efficacy. These algorithms operate on an adaptive machine learning mechanism designed to balance the load, and the study meticulously compares their efficacy in the context of Renewable Integration, Energy-Efficient Design, and Job Creation.

Algorithm 1040: The Sparse Grids Matlab Kit - a Matlab implementation of sparse grids for high-dimensional function approximation and uncertainty quantification

The Sparse Grids Matlab Kit provides a Matlab implementation of sparse grids, and can be used for approximating high-dimensional functions and, in particular, for surrogate-model-based uncertainty quantification. It is lightweight, high-level and easy to use, good for quick prototyping and teaching; however, it is equipped with some features that allow its use also in realistic applications. The goal of this paper is to provide an overview of the data structure and of the mathematical aspects forming the basis of the software, as well as comparing the current release of our package to similar available software.

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.

Design and implementation of grid tied high step-up DC-DC converter with switched capacitor

In this paper, the design and implementation of a three-phase grid-connected inverter coupled with a high step-up DC-DC converter with a switched capacitor is demonstrated. In this converter two capacitors are utilized with a coupled inductor. The charging of capacitors takes place parallel and discharging in series during switch off and switch on time respectively. The energization of the coupled inductor provides the high voltage gain. The passive clamp circuit is used to recycle the leakage energy of the inductor circuit. Therefore, the switch stress is reduced. This high gain converter is given DC input of 40 V and a high voltage 538 V obtained is supplied to the grid connected inverter which uses sinusoidal pulse width modulation (SPWM), to obtain 3phase line-neutral voltage of 415 V from inverter for grid synchronization. A high voltage gain of 13 and efficiency of 96% is obtained for different load and voltage variation. The modeling and the simulation are done using physical security information management (PSIM) software and all the results are presented in this paper.

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.

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.