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Smart grid is an integration between traditional electricity grid and communication systems and networks. Providing reliable services and functions is a critical challenge for the success and diffusion of smart grids that needs to be addressed. The purpose of this study is to determine the critical criteria that affect smart grid reliability from the perspective of users and investigate the role big data plays in smart grid reliability.

This study presents a model to investigate and identify criteria that influence smart grid reliability from the perspective of users. The model consists of 12 sub-criteria covering big data management, communication system and system characteristics aspects. Multi-criteria decision-making approach is applied to analyze data and prioritize the criteria using the fuzzy analytic hierarchy process based on the triangular fuzzy numbers. Data was collected from 16 experts in the fields of smart grid and Internet of things.

The results show that the “Big Data Management” criterion has a significant impact on smart grid reliability followed by the “System Characteristics” criterion. The “Data Analytics” and the “Data Visualization” were ranked as the most influential sub-criteria on smart grid reliability. Moreover, sensitivity analysis has been applied to investigate the stability and robustness of results. The findings of this paper provide useful implications for academicians, engineers, policymakers and many other smart grid stakeholders.

The users are not expected to actively participate in smart grid and its services without understanding their perceptions on smart grid reliability. Very few works have studied smart grid reliability from the perspective of users. This study attempts to fill this considerable gap in literature by proposing a fuzzy model to prioritize smart grid reliability criteria.

The purpose of this study is to explore the latest approaches in integrating artificial intelligence and analytics (AIA) in energy smart grid projects. Empirical results are synthesized to highlight their relevance from a technology and project management standpoint, identifying several lessons learned that can be used for planning highly integrated and automated smart grid projects.

A systematic literature review leads to selecting 108 research articles dealing with smart grids and AIA applications. Keywords are based on the following research questions: What is the growth trend in Smart Grid projects using intelligent systems and data analytics? What business value is offered when AI-based methods are applied? How do applications of intelligent systems combine with data analytics? What lessons can be learned for Smart Grid and AIA projects?

The 108 selected articles are classified according to the following four research issues in smart grids project management: AIA integrated applications; AI-focused technologies; analytics-focused technologies; architecture and design methods. A broad set of smart grid functionality is reviewed, seeking to find commonality among several applications, including as follows: dynamic energy management; automation of extract, transform and load for Supervisory Control And Data Acquisition (SCADA) systems data; multi-level representations of data; the relationship between the standard three-phase transforms and modern data analytics; real-time or short-time voltage stability assessment; smart city architecture; home energy management system; building energy consumption; automated fault and disturbance analysis; and power quality control.

Given the diversity of issues reviewed, a more capability-focused research agenda is needed to further synthesize empirical findings for AI-based smart grids. Research may converge toward more focus on business rules systems, that may best support smart grid design, proof development, governance and effectiveness. These AIA technologies must be further integrated with smart grid project management methodologies and enable a greater diversity of renewable and non-renewable production sources.

The purpose of this study is to establish a hierarchy of critical success factors to develop a framework for evaluating the performance of smart grids from a sustainability perspective.

The fuzzy analytical hierarchy process is used in this study to assess and determine the relative weight of economic, operational and environmental criteria. At the same time, the evidential reasoning algorithm is used to determine the belief degree of expert’s opinion, and the expected utility theory for the crisp value of success factors in performance estimation.

The finding reveals that success factors associated with the economic criteria receive significantly more attention from the expert group. Sensitivity analysis indicates the ranking of consumer satisfaction remains stable no matter how criteria weights are changed, which verifies the robustness and effectiveness of the proposed model and evaluation results.

The study presents a solid mathematical framework for collaborative system modeling and systematic analysis. Managers and stakeholders may use the proposed technique as a flexible tool to improve the energy system’s resiliency in a systematic way.

The need to address energy management as a significant innovation in the smart grid is emphasized to enable a more effective penetration of renewable energy to achieve energy savings and CO₂ emission reductions. The purpose of this study is to propose a holistic, flexible decision framework for energy management in a smart grid.

According to the situation actor process−learning action performance (SAP−LAP) model, the variables have been identified after a comprehensive analysis of the literature and consideration of the opinions of domain experts. However, the importance of each SAP−LAP variable is not the same in real practice. Hence, focus on these variables should be given based on their importance, and to measure this importance, an interpretive ranking process based ranking method is used in this study. This helps to allocate proportionate resource to each SAP−LAP variable to make a better decision for the energy management of the smart grid.

This study ranked five actors based on their priorities for energy management in a smart grid: top management, generator and retailor, consumers, government policy and regulation and technology vendors. Furthermore, actions are also prioritized with respect to performance.

The SAP−LAP model conveys information about the state of energy management in India to actors who may proceed or manage the flow of electricity. Additionally, this study aids in detecting vulnerabilities in the current energy generation, transmission and distribution technique. The synthesis of SAP results in LAP, which assists in recommending improvement actions learned from the current situation, actors and processes.

The SAP−LAP model is a revolutionary approach for examining the current state of energy management in a unified framework that can guide decision-making in conflicting situations, significantly the contradictory nature of India’s renewable energy and power sectors.

The chapter analyses the role of smart grid technology in the German energy transition. Information technologies promise to help integrate volatile renewable energies (wind and solar power) into the grid. Yet, the promise of intelligent infrastructures does not only extend to technological infrastructures, but also to market infrastructures. Smart grid technologies underpin and foster the design of a “smart” electricity market, where dispersed energy prosumers can adapt, in real time, to fluctuating price signals that register changes in electricity generation. This could neutralize fluctuations resulting from the increased share of renewables. To critically “think” the promise of smart infrastructure, it is not enough to just focus on digital devices. Rather, it becomes necessary to scrutinize economic assumptions about the “intelligence” of markets and the technopolitics of electricity market design. This chapter will first show the historical trajectory of the technopolitical promise of renewable energy as not only a more sustainable, but also a more democratic alternative to fossil and nuclear power, by looking at the affinities between market liberal and ecological critiques of centralized fossil and nuclear based energy systems. It will then elucidate the co-construction of smart grids and smart markets in the governmental plans for an “electricity market 2.0.” Finally, the chapter will show how smart grid and smart metering technology fosters new forms of economic agency like the domo oeconomicus. Such an economic formatting of smart grid technology, however, forecloses other ecologically prudent and politically progressive ways of constructing and engaging with intelligent infrastructures.

This paper aims to market analysis on the base many factors. Market analysis must be done correctly to increase the efficiency of smart grid technologies. On the other hand, it is not very possible for the company to make improvements for too many factors. The main reason for this is that businesses have constraints both financially and in terms of manpower. Therefore, a priority analysis is needed in which the most important factors affecting the effectiveness of the market analysis will be determined.

In this context, a new fuzzy decision-making model is generated. In this hybrid model, there are mainly two different parts. First, the indicators are weighted with quantum spherical fuzzy multi SWARA (M-SWARA) methodology. On the other side, smart grid technology investment projects are examined by quantum spherical fuzzy ELECTRE. Additionally, facial expressions of the experts are also considered in this process.

The main contribution of the study is that a new methodology with the name of M-SWARA is generated by making improvements to the classical SWARA. The findings indicate that data-driven decisions play the most critical role in the effectiveness of market environment analysis for smart technology investments. To achieve success in this process, large-scale data sets need to be collected and analyzed. In this context, if the technology is strong, this process can be sustained quickly and effectively.

It is also identified that personalized energy schedule with smart meters is the most essential smart grid technology investment alternative. Smart meters provide data on energy consumption in real time.

On its way to develop a smart grid in Indonesia, one key enabler in the early stage of implementation is advanced metering infrastructure (AMI). Thus, Perusahaan Listrik Negara (PLN), an electrical energy utility company owned by the government of the Republic of Indonesia as the only electricity utility company servicing customers from upstream to downstream in Indonesia, has started AMI program at some main cities. With AMI, real-time energy consumption profile, energy meter status and condition, and customer power quality can be acquired. Subsequently, these data collected by AMI can be used for further smart grid implementation by such IT systems and big data analysis. Instead of its function for smart grid backbone, AMI also significantly support smart energy on the city as a part of smart city initiatives. Nevertheless, its implementation requires more investment than the conventional metering system. This investment needs to be evaluated to define whether AMI is feasible and viable or not. This chapter is intended to observe the feasibility of AMI implementation in Indonesia using cost-benefit analysis (CBA). Two schemes were used as study objects, one scheme in which the communication infrastructure was managed by PLN itself, and the other one in which the communication infrastructure was managed by a third party. From the analysis, it appears that both schemes are proven to be feasible.

At present the energy generation and distribution landscape is changing rapidly. The energy grid is becoming increasingly smart, relying on an information network for the purposes of monitoring and optimization. However, because of the particularly stringent regulatory and technical constraints posed by smart grids, it is not possible to use ordinary communication protocols. The purpose of this paper is to revisit such constraints, reviewing the various options available today to realize smart‐metering networks.

After describing the regulatory, technological and stakeholders' constraints, the authors provide a taxonomy of network technologies, discussing their suitability and weaknesses in the context of smart‐metering systems. The authors also give a snapshot of the current standardization panorama, identifying key differences among various geographical regions.

It is found that the field of smart‐metering networks still consists of a fragmented set of standards and solutions, leaving open a number of issues relating to the design and deployment of suitable systems.

This paper addresses the need to better understand state‐of‐the‐art and open issues in the fast‐evolving area of smart energy grids, with particular attention to the challenges faced by communication engineers.

There are 29 million homes in the UK, accounting for 14% of the UK's energy consumption. This is given that UK has one of the highest water and energy demands in Europe which needs to be addressed according to the Committee on Climate Change (CCC). Smart homes technology holds a current perception that it is principally used by “tech-savvy” users with larger budgets. However, smart home technology can be used to control water, heat and energy in the entire house. This paper investigates how smart home technology could be effectively utilised to aid the UK government in meeting climate change targets and to mitigate the environmental impact of a home in use towards reducing carbon emissions.

Both primary and secondary data were sought to gain insight into the research problem. An epistemological approach to this research is to use interpretivism to analyse data gathered via a semi-structured survey. Two groups of participants were approached: (1) professionals who are deemed knowledgeable about smart home development and implementation and (2) users of smart home technology. A variety of open-ended questions were formulated, allowing participants to elaborate by exploring issues and providing detailed qualitative responses based on their experience in this area which were interpreted quantitatively for clearer analysis.

With fossil fuel reserves depleting, there is an urgency for renewable, low carbon energy sources to reduce the 5 tonnes annual carbon emissions from a UK household. This requires a multi-faceted and a multimethod approach, relying on the involvement of both the general public and the government in order to be effective. By advancing energy grids to make them more efficient and reliable, concomitant necessitates a drastic change in the way of life and philosophy of homeowners when contemplating a reduction of carbon emissions. If both parties are able to do so, the UK is more likely to reach its 2050 net-zero carbon goal. The presence of a smart meter within the household is equally pivotal. It has a positive effect of reducing the amount of carbon emissions and hence more need to be installed.

Further research is needed using a larger study sample to achieve more accurate and acceptable generalisations about any future course of action. Further investigation on the specifics of smart technology within the UK household is also needed to reduce the energy consumption in order to meet net-zero carbon 2050 targets due to failures of legislation.

For smart homes manufacturers and suppliers, more emphasis should be placed to enhance compatibility and interoperability of appliances and devices using different platform and creating more user's friendly manuals supported by step-by-step visual to support homeowners in the light of the wealth of knowledge base generated over the past few years. For homeowners, more emphasis should be placed on creating online knowledge management platform easily accessible which provide virtual support and technical advice to home owners to deal with any operational and technical issues or IT glitches. Developing technical design online platform for built environment professionals on incorporating smart sensors and environmentally beneficial technology during early design and construction stages towards achieving low to zero carbon homes.

This paper bridges a significant gap in the body of knowledge in term of its scope, theoretical validity and practical applicability, highlighting the impact of using smart home technology on the environment. It provides an insight into how the UK government could utilise smart home technology in order to reduce its carbon emission by identifying the potential link between using smart home technology and environmental sustainability in tackling and mitigating climate change. The findings can be applied to other building types and has the potential to employ aspects of smart home technology in order to manage energy and water usage including but not limited to healthcare, commercial and industrial buildings.

Battery integration with renewable energy and conventional power grid is common practice in smart grid systems and provides higher operational flexibility. Abundant issues and challenges to the Indian smart grid while integrating renewable energy and storage technology will give timely emphasis to grasp uninterrupted power supply in forthcoming trend. Hence, this paper aims to acknowledge different barriers of battery integration and evaluate them to develop approaches for restricting their influence.

A multi-model approach is used to illustrate how these challenges are interrelated by systematically handling expert views and helps to chronologically assemble various issues from the greatest severe to the slightest severe ones. Further, these barriers are grouped using the cross-impact matrix multiplication applied to the classification analysis (MICMAC) study grounded on their driving and dependence power. Also, hypothesis testing was done to validate the obtained model.

It provides a complete thoughtful on directional interrelationships between the barriers and delivers the best possible solution for the active operation of the smart grid and its performance.

There is a significant requirement for high-tech inventions outside the transmission grid to function for the integration of renewables and storage systems.

The model will support policymakers in building knowledgeable decisions while chronologically rejecting the challenges of battery integration in smart grid systems to improve power grid performance.

Based on author’s best knowledge, there is hardly any research that explicitly explains the framework for the barriers of battery integration in grid for developing countries like India. It is one of the first attempts to understand the fundamental barriers for battery integration. This study adds significantly to the literature on the energy sector by capturing the perspective of various stakeholders.