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The current and modern electrical distribution networks, named smart grids (SGs), use advanced technologies to accomplish all the technical and nontechnical challenges naturally demanded by energy applications. Energy metering collecting is one of these challenges ranging from the most basic (i.e., visual assessment) to the expensive advanced metering infrastructure (AMI) using intelligent meters networks. The AMIs’ data acquisition and system monitoring environment require enhancing some routine tasks. This paper aims to propose a methodology that uses a distributed and sustainable approach to manage wide-range metering networks, focused on using current public or private telecommunication infrastructure, optimizing the implementation and operation, increasing reliability and decreasing costs.

Inspired by blockchain technology, a collaborative metering system architecture is conceived, managing massive data sets collected from the grid. The use of cryptography handles data integrity and security issues.

A robust proof-of-concept simulation results are presented concerning the resilience and performance of the proposed distributed remote metering system.

The methodology proposed in this work is an innovative AMI solution related to SGs. Regardless of the implementation, operation and maintenance of AMIs, the proposed solution is unique, using legacy and new technologies together in a reliable way.

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.

Digitizing of the electrical power grid promotes the advantages of efficient energy management alongside the possibilities of major vulnerabilities. A typical inadequacy that needs critical attention to ensure the seamless operation of the smart grid system remains in the data transmission between consumer premises smart devices and the utility centres. Many researches aim at establishing security protocols to ensure secure and efficient energy management resulting in perfect demand–supply balance.

In this paper, the authentication of the smart meter data has been proposed with enhanced Rivest–Shamir–Adleman (RSA) key encryption using an efficient way of generating large prime numbers. The trapdoor one-way function applied in the RSA algorithm makes it almost impossible for the reverse engineering attempts of cracking the key pair.

The algorithm for generating prime numbers has been tested both with the convention method and with the enhanced method of including a low-level primality test with a first few hundred primes. The combination of low-level and high-level primality tests shows an improvement in execution time of the algorithm.

There is a considerable improvement in the time complexities when using the combination method. This efficient generation of prime numbers can be successfully applied to the smart meter systems, thereby increasing the strength and speed of the key encryption.

Distribution and retail supply of electricity is the most important cog in the power sector value chain. Despite several reforms, most of the Discoms are facing huge financial losses and resorting to a tariff hike which may not be a viable solution. The purpose of this paper is to analyze a case study of Tata Power Delhi Distribution Ltd (Tata Power-DDL) which inoculated itself against the financial ills, and demonstrates how a utility can nurture itself and manage the key stakeholder expectation with innovation, ethics, safety, transparency and agility being its cornerstone.

The study analyses the situation for Tata Power-DDL which needs to realign its strategy to meet emerging sustainability challenges. The case covers the aspect of strategic management, strategy formulation and change management system deployment using tools such as strength, weakness, opportunities, threat (SWOT), political economical social technological legal environment (PESTLE), critical success factor and key performance indicator cascade. It touches upon the emerging need for distribution utilities to look beyond economic signals and take social and environmental impacts into the strategy planning process.

It viewed the distribution business beyond its conventional responsibility of making power available to consumers and to provide quality service. A well thought out adaption and adoption of upgraded technology can be a game changer even for a market which is highly regulated and dominated by players in their respective defined territories.

Since the sector is regulated and each utility has a pre-defined set of area of operation with no competition within its licensed area, hence, there is a limited application of applied strategy tools such as SWOT and PESTLE.

Since the sector is regulated and each utility has a pre-defined set of area of operation with no competition within its licensed area, hence, there is a limited application of applied strategy tools such as SWOT and PESTLE.

India as a market is evolving in energy space and utilities are still struggling to have a fundamental structure to meet the agenda of “power to all.” The paper provides the valuable insights into the process of environmental scanning and formulation of organizational strategy to meet the needs of existing and future energy markets.

The purpose of this study is to examine cyber security risks in globalized supply chains (SCs). It has been seen to have a greater impact on the performance of SCs. The information and communication technology of a firm, which enhances the efficiency and effectiveness in the SC, could simultaneously be the cause of vulnerabilities and exposure to security threats. Researchers have primarily focussed on the cyber-physical system (CPS) vulnerabilities impacting SC. This paper tries to categorize the cyber security risks occurring because of the SCs operating in CPS.

Based on the flow of information along the upstream and downstream SC, this paper tries to identify cyber security risks in the global SCs. It has further tried to categorize these cyber security risks from a strategic point of view.

This paper tries to identify the various cyber security risk and cyber-attacks in globalized SC for improving the performance. The 16 cyber security risks have been categorized into three categories, namely, supply risk, operational risk and demand risk. The paper proposes a framework consisting of different cyber-attacks across the information that flows in global SCs along-with suitable mitigation strategies.

The paper presents the conceptual model of cyber security risks and cyber-attacks in globalized SCs based on literature review and industry experts. Further validation and scale development of these risks can be done through empirical study.

This paper provides significant managerial insights by developing a framework for understanding the cyber security risks in terms of the drivers of these risks and how to deal with them. From a managerial perspective, this framework can be used as a decision-making process while considering different cyber security risks across the stages of globalized SCs.

The major contribution of this study is the identification and categorization of cyber security risks across the global SCs in the digital age. Thus, this paper introduces a new phenomenon to the field of management that has the potential to investigate new areas of future research. Based on the categorization, the paper provides insights on how cyber security risks impact the continuity of SC operations.

This paper aims to propose a machine learning approach-based power theft detection using Garra Rufa Fish (GRF) optimization. Here, the analyzing of power theft is an important part to reduce the financial loss and protect the electricity from fraudulent users.

In this section, a new method is implemented to reduce the power theft in transmission lines and utility grids. The detection of power theft using smart meter with reliable manner can be achieved by the help of GRF algorithm.

The loss of power due to non-technical loss is small by using this proposed algorithm. It provides some benefits like increased predicting capacity, less complexity, high speed and high reliable output. The result is analyzed using MATLAB/Simulink platform. The result is compared with an existing method. According to the comparison result, the proposed method provides the good performance than existing method.

The proposed method gives good results of comparison than those of the other techniques and has an ability to overcome the associated problems.

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 paper is to describe challenges and lessons learned in the design and development of a comprehensive, flexible environmental management system (EMS) in a real university setting; also to inform development of similar systems elsewhere and provide a modular, extensible software architecture for such efforts.

A modular, flexible software architecture was designed as the cornerstone of a comprehensive, secure web‐based data collection and analysis framework. Environmental data such as utility usages, waste generation and transportation services were identified, collected, and entered into the evolving system. The system is easily extensible to new environmental data types, and supported manual and automated data entry, custom “at‐the‐source data entry” mechanisms, and flexible tools for visually analyzing environmental data captured.

Development of automated EMS systems for large institutions is significantly complicated by profound heterogeneity in campus infrastructure, management policies, and limited data accessibility; legacy data are often incomplete or inaccurate. Successful EMS initiatives must explicitly address these challenges through realistic project planning, choice of software technologies, design of system architecture, and administrative commitment. Detailed insights in each of the above areas are provided.

The authors provide clarifying discussion of sustainability plans versus monitoring systems, place popular technological gadgets such as live building energy monitors into perspective within this framework, and describe design and implementation of a comprehensive environmental monitoring framework. The modular concept for system architecture, design approach, and lessons learned can inform the development of similar comprehensive EMS development efforts.

This paper aims to disclose the role and features of various IT systems for environmental building performance (EBP) in facilities management.

The study focuses on IT systems used for facilities management in four organisations. The study is based on a maximum variance case study in which the selected organisations have different organisation type and portfolio size. Three organisations are from Denmark and one is from the UK.

Several IT systems can be used for managing EBP. EBP in IT systems is primarily reflected through energy management, with specific focus on monitoring and reporting electricity, heating and water consumption. Furthermore, greenhouse gas emissions related to energy consumption can be calculated in some IT systems, while other environmental categories like building materials and recycling potentials are not adequately supported by the systems covered in this study. Some IT systems offer additional features relating to EBP, such as waste management and space management, but the study shows that these features are not demanded at the current point.

The results can be used to support decision-making in organisations to improve EBP in facilities management by IT systems.

This study contributes with new knowledge on how IT systems are used in different organisations for managing EBP. The paper also shows how various IT systems can add value to real estate organisations and facilities management departments and support their business processes relating to EBP.