Global Trends in the Political Economy of Smart Grids

2017 ◽  
Author(s):  
Cherrelle Eid ◽  
Rudi Hakvoort ◽  
Martin de Jong
Keyword(s):  
Smart Grid ◽  
Smart Grids ◽  
The United States ◽  
Industry Structure ◽  
Electricity Sector ◽  
Distributed Energy ◽  
Global Trends ◽  
Political Economic ◽  
Regulatory Models ◽  
Global Transition

The global transition towards sustainable, secure, and affordable electricity supply is driving changes in the consumption, production, and transportation of electricity. This chapter provides an overview of three main causes of political–economic tensions with smart grids in the United States, Europe, and China, namely industry structure, regulatory models, and the impact of energy policy. In all cases, the developments are motivated by the possible improvements in reliability and affordability yielded by smart grids, while sustainability of the electricity sector is not a central motivation. A holistic smart grid vision would open up possibilities for better integration of distributed energy resources. The authors recommend that smart grid investments should remain outside of the regulatory framework for utilities and distribution service operators in order to allow for such developments.

scholarly journals Regulation of advocacy profession: global trends

2021 ◽  
Vol 39 (69) ◽  
pp. 689-706
Author(s):  
Tetiana Vilchyk ◽  
Alla Sokolova ◽  
Tetiana Demchyna
Keyword(s):  
Self Regulation ◽  
Legal Profession ◽  
The United States ◽  
Legal Regulation ◽  
International Standards ◽  
Global Trends ◽  
Scientific Methods ◽  
General Scientific ◽  
Different Sources ◽  
Regulatory Models

The objective of the article is to analyze the regulation of the legal profession and its global trends. There are many different types of regulators globally, and many different sources and methods of regulation. There is no simple approach to setting goals for regulating the legal profession in different legal systems. Although self-regulation of the legal profession is considered the basis for adhering to the standard of its independence, at the same time, academics recognize the existence of the theory of the management of the legal profession. To study these problems, the authors conducted a comparative study of the regulatory models of the legal profession in the world in terms of compliance with international standards of legal independence in different legal jurisdictions and made some suggestions to improve the legal regulation of the legal profession in Ukraine. Empirical sources for scientific research were international documents, court decisions, national legislation of Great Britain, Canada, the United States, Ireland, Scotland, Australia and others, and the work of scientists. The article uses general scientific methods - dialectic, analysis, synthesis, analogy, etc., and special methods, particularly legal, historical, and formal comparative law.

scholarly journals A Comparative Analysis of Enhanced Machine Learning Algorithms for Smart Grid Stability Prediction

2021 ◽  
Author(s):  
ANKIT GHOSH ◽  
ALOK KOLE
Keyword(s):  
Machine Learning ◽  
Comparative Analysis ◽  
Smart Grid ◽  
Smart Grids ◽  
Machine Learning Algorithms ◽  
Electricity Sector ◽  
Stochastic Gradient Descent ◽  
Energy Output ◽  
Gradient Boosting ◽  
Support Vector

<p>Smart grid is an essential concept in the transformation of the electricity sector into an intelligent digitalized energy network that can deliver optimal energy from the source to the consumers. Smart grids being self-sufficient systems are constructed through the integration of information, telecommunication, and advanced power technologies with the existing electricity systems. Artificial Intelligence (AI) is an important technology driver in smart grids. The application of AI techniques in smart grid is becoming more apparent because the traditional modelling optimization and control techniques have their own limitations. Machine Learning (ML) being a sub-set of AI enables intelligent decision-making and response to sudden changes in the customer energy demands, unexpected disruption of power supply, sudden variations in renewable energy output or any other catastrophic events in a smart grid. This paper presents the comparison among some of the state-of-the-art ML algorithms for predicting smart grid stability. The dataset that has been selected contains results from simulations of smart grid stability. Enhanced ML algorithms such as Support Vector Machine (SVM), Logistic Regression, K-Nearest Neighbour (KNN), Naïve Bayes (NB), Decision Tree (DT), Random Forest (RF), Stochastic Gradient Descent (SGD) classifier, XGBoost and Gradient Boosting classifiers have been implemented to forecast smart grid stability. A comparative analysis among the different ML models has been performed based on the following evaluation metrics such as accuracy, precision, recall, F1-score, AUC-ROC, and AUC-PR curves. The test results that have been obtained have been quite promising with the XGBoost classifier outperforming all the other models with an accuracy of 97.5%, recall of 98.4%, precision of 97.6%, F1-score of 97.9%, AUC-ROC of 99.8% and AUC-PR of 99.9%. </p>

scholarly journals Smart grids investigation and analysis in terms of cost benefits

2018 ◽  
Vol 7 (2.21) ◽  
pp. 185
Author(s):  
B Rubini ◽  
N Shanmugasundaram ◽  
S Pradeepkumar
Keyword(s):  
Smart Grid ◽  
Smart Grids ◽  
Distribution Networks ◽  
Distribution Automation ◽  
Power Networks ◽  
Distributed Energy ◽  
Smart Power ◽  
Advanced Technologies ◽  
Advanced Metering ◽  
Grid Operation

Currently, different advanced technologies are implemented in power networks, with aim to improve power quality and reliability of grid operation. Naturally, Distribution Automation and Management Systems (DAMS), Smart power equipment, Advanced Metering Structure, Distributed Energy Resources and/or systems Demand Response are implemented in electricity distribution networks. Smart Grid Solutions coordinate different advanced technologies in an efficient energy management system. Outline Smart Grid Solutions, with investments of estimation, possible benefits and operation costs, is presented in this article, with estimation of cost-effectiveness in a lifetime of particular systems. 

scholarly journals Internet of Things Technologies for Smart Grid

2022 ◽  
pp. 805-832
Author(s):  
Imed Saad Ben Dhaou ◽  
Aron Kondoro ◽  
Syed Rameez Ullah Kakakhel ◽  
Tomi Westerlund ◽  
Hannu Tenhunen
Keyword(s):  
Internet Of Things ◽  
Smart Grid ◽  
Smart Grids ◽  
Reference Model ◽  
Energy Resources ◽  
Distributed Energy Resources ◽  
Reference Architecture ◽  
Distributed Energy ◽  
Research Gaps ◽  
Utility Company

Smart grid is a new revolution in the energy sector in which the aging utility grid will be replaced with a grid that supports two-way communication between customers and the utility company. There are two popular smart-grid reference architectures. NIST (National Institute for Standards and Technology) has drafted a reference architecture in which seven domains and actors have been identified. The second reference architecture is elaborated by ETSI (European Telecommunications Standards Institute), which is an extension of the NIST model where a new domain named distributed energy resources has been added. This chapter aims at identifying the use of IoT and IoT-enabled technologies in the design of a secure smart grid using the ETSI reference model. Based on the discussion and analysis in the chapter, the authors offer two collaborative and development frameworks. One framework draws parallels' between IoT and smart grids and the second one between smart grids and edge computing. These frameworks can be used to broaden collaboration between the stakeholders and identify research gaps.

scholarly journals A Comparative Analysis of Enhanced Machine Learning Algorithms for Smart Grid Stability Prediction

2021 ◽  
Author(s):  
ANKIT GHOSH ◽  
ALOK KOLE
Keyword(s):  
Machine Learning ◽  
Comparative Analysis ◽  
Smart Grid ◽  
Smart Grids ◽  
Machine Learning Algorithms ◽  
Electricity Sector ◽  
Stochastic Gradient Descent ◽  
Energy Output ◽  
Gradient Boosting ◽  
Support Vector

<p>Smart grid is an essential concept in the transformation of the electricity sector into an intelligent digitalized energy network that can deliver optimal energy from the source to the consumers. Smart grids being self-sufficient systems are constructed through the integration of information, telecommunication, and advanced power technologies with the existing electricity systems. Artificial Intelligence (AI) is an important technology driver in smart grids. The application of AI techniques in smart grid is becoming more apparent because the traditional modelling optimization and control techniques have their own limitations. Machine Learning (ML) being a sub-set of AI enables intelligent decision-making and response to sudden changes in the customer energy demands, unexpected disruption of power supply, sudden variations in renewable energy output or any other catastrophic events in a smart grid. This paper presents the comparison among some of the state-of-the-art ML algorithms for predicting smart grid stability. The dataset that has been selected contains results from simulations of smart grid stability. Enhanced ML algorithms such as Support Vector Machine (SVM), Logistic Regression, K-Nearest Neighbour (KNN), Naïve Bayes (NB), Decision Tree (DT), Random Forest (RF), Stochastic Gradient Descent (SGD) classifier, XGBoost and Gradient Boosting classifiers have been implemented to forecast smart grid stability. A comparative analysis among the different ML models has been performed based on the following evaluation metrics such as accuracy, precision, recall, F1-score, AUC-ROC, and AUC-PR curves. The test results that have been obtained have been quite promising with the XGBoost classifier outperforming all the other models with an accuracy of 97.5%, recall of 98.4%, precision of 97.6%, F1-score of 97.9%, AUC-ROC of 99.8% and AUC-PR of 99.9%. </p>

Smart Grid Efficiency: a Chinese Approach

2019 ◽  
pp. 24-31
Author(s):  
Ihor A. Vakulenko
Keyword(s):  
Smart Grid ◽  
Smart Grids ◽  
Energy System ◽  
The United States ◽  
Indicator System ◽  
People’S Republic Of China ◽  
Time Interval ◽  
The European Union ◽  
People's Republic Of China ◽  
Republic Of China

The paper considers the issues of evaluating the efficiency of smart grid projects, which is important for evaluating the performance of implemented projects and identifying the most promising projects among those proposed for implementation. The objective of the work is to identify and analyze the approaches to the assessment of smart grids used in the People's Republic of China (PRC). For this purpose, has been allocated two typical approaches that have proliferated and are widely used in China. Moreover, one of them (Grid development assessment index system) is universal: it is used to evaluate both existing and potential projects - the other (Smart grid pilot project evaluation indicator system) is used solely to evaluate pilot projects (smart grid projects that may be implemented). The urgency of the work is justified by the need to identify the best world practices for evaluating Smart Grid projects in view of the prospects for the development of smart grids in Ukraine, and therefore the need to select the most effective projects and identify the most promising areas of energy sector development. Building smart grids is a prerequisite for integrating the Ukrainian energy system with the European Union's energy system. The geographical choice of the People's Republic of China for research purposes is explained by the country's significant progress in building a smart grid over a limited time interval. The beginning of active activity in this area in the PRC dates back to the period when the countries of the European Union and the United States of America implemented the basic reforms necessary for the implementation of complex infrastructure projects in the field of smart energy networks. Key words: energy, innovation, Smart Grid, evaluation techniques.

scholarly journals State-of-the-Art Artificial Intelligence Techniques for Distributed Smart Grids: A Review

Electronics ◽  
2020 ◽  
Vol 9 (6) ◽  
pp. 1030 ◽  
Author(s):  
Syed Saqib Ali ◽  
Bong Jun Choi
Keyword(s):  
Artificial Intelligence ◽  
Smart Grid ◽  
Power System ◽  
Energy Management ◽  
Smart Grids ◽  
State Of The Art ◽  
Energy Resources ◽  
Distributed Energy ◽  
Artificial Intelligence Techniques ◽  
Home Energy Management

The power system worldwide is going through a revolutionary transformation due to the integration with various distributed components, including advanced metering infrastructure, communication infrastructure, distributed energy resources, and electric vehicles, to improve the reliability, energy efficiency, management, and security of the future power system. These components are becoming more tightly integrated with IoT. They are expected to generate a vast amount of data to support various applications in the smart grid, such as distributed energy management, generation forecasting, grid health monitoring, fault detection, home energy management, etc. With these new components and information, artificial intelligence techniques can be applied to automate and further improve the performance of the smart grid. In this paper, we provide a comprehensive review of the state-of-the-art artificial intelligence techniques to support various applications in a distributed smart grid. In particular, we discuss how artificial techniques are applied to support the integration of renewable energy resources, the integration of energy storage systems, demand response, management of the grid and home energy, and security. As the smart grid involves various actors, such as energy produces, markets, and consumers, we also discuss how artificial intelligence and market liberalization can potentially help to increase the overall social welfare of the grid. Finally, we provide further research challenges for large-scale integration and orchestration of automated distributed devices to realize a truly smart grid.

scholarly journals Open Information Architecture for Seamless Integration of Renewable Energy Sources

Electronics ◽  
2021 ◽  
Vol 10 (4) ◽  
pp. 496
Author(s):  
Armin Veichtlbauer ◽  
Oliver Langthaler ◽  
Filip Pröstl Andrén ◽  
Christian Kasberger ◽  
Thomas I. Strasser
Keyword(s):  
Smart Grid ◽  
Information Exchange ◽  
Smart Grids ◽  
Information Technologies ◽  
Renewable Energy Sources ◽  
Energy Resource ◽  
Distributed Energy ◽  
Open Communication ◽  
Seamless Integration ◽  
Automation Systems

Electric power systems are currently confronted with a fundamental paradigm change related to its planning and operation, mainly caused by the massive integration of renewables. To allow higher penetration of them within existing grid infrastructures, the “smart grid” makes more efficient use of existing resources by integrating appropriate information technologies. Utilising the benefits of such smart grids, it is necessary to develop new automation architectures and control strategies, as well as corresponding information and communication solutions. This makes it possible to effectively use and manage a large amount of dispersed generators and to utilise their “smart” capabilities. The scalability and openness of automation systems currently used by energy utilities have to be improved significantly for handling a high amount of distributed generators. This will be needed to meet the challenges of missing common and open interfaces, as well as the large number of different protocols. In the work at hand, these shortcomings have been tackled by a conceptual solution for open and interoperable information exchange and engineering of automation applications. The approach is characterised by remote controllable services, a generic communication concept, and a formal application modelling method for distributed energy resource components. Additionally, the specification of an access management scheme for distributed energy resources, taking into account different user roles in the smart grid, allowed for a fine-grained distinction of access rights for use cases and actors. As a concrete result of this work, a generic and open communication underlay for smart grid components was developed, providing a flexible and adaptable infrastructure and supporting future smart grid requirements and roll-out. A proof-of-concept validation of the remote controllable service concept based on this infrastructure has been conducted in appropriate laboratory environments to confirm the main benefits of this approach.

scholarly journals Internet of Things Technologies for Smart Grid

2020 ◽  
pp. 256-284
Author(s):  
Imed Saad Ben Dhaou ◽  
Aron Kondoro ◽  
Syed Rameez Ullah Kakakhel ◽  
Tomi Westerlund ◽  
Hannu Tenhunen
Keyword(s):  
Internet Of Things ◽  
Smart Grid ◽  
Smart Grids ◽  
Reference Model ◽  
Energy Resources ◽  
Distributed Energy Resources ◽  
Reference Architecture ◽  
Distributed Energy ◽  
Research Gaps ◽  
Utility Company

Smart grid is a new revolution in the energy sector in which the aging utility grid will be replaced with a grid that supports two-way communication between customers and the utility company. There are two popular smart-grid reference architectures. NIST (National Institute for Standards and Technology) has drafted a reference architecture in which seven domains and actors have been identified. The second reference architecture is elaborated by ETSI (European Telecommunications Standards Institute), which is an extension of the NIST model where a new domain named distributed energy resources has been added. This chapter aims at identifying the use of IoT and IoT-enabled technologies in the design of a secure smart grid using the ETSI reference model. Based on the discussion and analysis in the chapter, the authors offer two collaborative and development frameworks. One framework draws parallels' between IoT and smart grids and the second one between smart grids and edge computing. These frameworks can be used to broaden collaboration between the stakeholders and identify research gaps.

scholarly journals FLEXGRID – A novel smart grid architecture that facilitates high-RES penetration through innovative flexibility markets towards efficient stakeholder interaction

2021 ◽  
Vol 1 ◽  
pp. 128
Author(s):  
Nikolaos Efthymiopoulos ◽  
Prodromos Makris ◽  
Georgios Tsaousoglou ◽  
Konstantinos Steriotis ◽  
Dimitrios J. Vergados ◽  
...  
Keyword(s):  
Smart Grid ◽  
Distribution System ◽  
Smart Grids ◽  
Large Scale ◽  
Renewable Energy Sources ◽  
Market Liquidity ◽  
Level Energy ◽  
Intelligent Network ◽  
Distributed Energy ◽  
Electricity System

The FLEXGRID project develops a digital platform designed to offer Digital Energy Services (DESs) that facilitate energy sector stakeholders (i.e. Distribution System Operators - DSOs, Transmission System Operators - TSOs, market operators, Renewable Energy Sources - RES producers, retailers, flexibility aggregators) towards: i) automating and optimizing the planning and operation/management of their systems/assets, and ii) interacting in a dynamic and efficient way with their environment (electricity system) and the rest of the stakeholders. In this way, FLEXGRID envisages secure, sustainable, competitive, and affordable smart grids. A key objective is the incentivization of large-scale bottom-up investments in Distributed Energy Resources (DERs) through innovative smart grid management. Towards this goal, FLEXGRID develops innovative data models and energy market architectures (with high liquidity and efficiency) that effectively manage smart grids through an advanced TSO-DSO interaction as well as interactions between Transmission Network and Distribution Network level energy markets. Consequently, and through intelligence that exploits the innovation of the proposed market architecture, FLEXGRID develops investment tools able to examine in depth the emerging energy ecosystem and allow in this way: i) the financial sustainability of DER investors, and ii) the market liquidity/efficiency through advanced exploitation of DERs and intelligent network upgrades.

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