Smart Grid Deployment Research Articles

Threats and Challenges of Smart Grids Deployments - A Developing Nations’ Perspective

Considerable efforts in huge investments are being made to achieve a resilient Smart Grids (SGs) deployment for the improvement of power delivery scheme. Unsurprisingly, many developing nations are making slow progress to the achievement of this feat which is set to revolutionize the power industry own to several deployment and security issues. Studying these challenges from both technical and non-technical view, this paper presents a highlight and assessment of each of the identified challenges. These challenges are assessed by exposing the security and deployment related threats while suggesting ways of tackling these challenges with prominence to developing nations. Although, a brief highlight, this review will help key actors in the region to identify the related challenges and it’s a guide to sustainable deployments of SGs in the region

Blockchain-Based Anonymous Authentication With Key Management for Smart Grid Edge Computing Infrastructure

Achieving low latency and providing real-time services are two of several key challenges in conventional cloud-based smart grid systems, and hence, there has been an increasing trend of moving to edge computing. While there have been a number of cryptographic protocols designed to facilitate secure communications in smart grid systems, existing protocols generally do not support conditional anonymity and flexible key management. Thus, in this article, we introduce a blockchain-based mutual authentication and key agreement protocol for edge-computing-based smart grid systems. Specifically, leveraging blockchain, the protocol can support efficient conditional anonymity and key management, without the need for other complex cryptographic primitives. The security analysis shows that the protocol achieves reasonable security assurance, and the comparative summary for security and efficiency also suggests the potential of the proposed protocol in a smart grid deployment.

A Magnetic Core Permeance Model for Inductive Power Harvesting

A current transformer (CT) is a preferred device to harvest power in the high-voltage utility grid to power monitoring equipment. Widespread CT use is foreseen in future smart grid deployment. The most common CT use involves a laminated transformer iron split core installation around a high-voltage cable with a particular number of turns to power a load or burden. Less common is a gapless core installation to improve reliability and prevent CT degradation by avoiding gap corrosion. Even laminated high resistivity cores still suffer from eddy current loss. The goal is to design a core able to deliver the desired power at optimum number of turns, minimized dimensions, and minimal loss. This article focuses on the core permeance as a complex parameter, on core size, losses or efficiency, load impedance optimization, flux level, power factor performance, and the relationship between these parameters. A similar size split core shows reduced loss compared to a gapless core. Lossy cores can still operate relatively efficiently at low flux levels indicating that the load current should preferably approach the short circuit current. Notwithstanding nanocrystalline and ferrite material advantages, silicon-doped laminated iron remains the preferred choice for 50/60 Hz inductive power harvesting.

Recommendations and solutions to remove some barriers to the deployment of smart grid in Morocco

<p>In this paper, we identify the current state and prospects of smart grids in Morocco. We begin by describing the current state of the Moroccan network, then we study the obstacles to the development of smart grids in Morocco and internationally. We conclude with recommendations and solutions to remove some barriers to the deployment of intelligent electrical networks in Morocco.</p>

IoT-Based Implementation of Field Area Network Using Smart Grid Communication Infrastructure

A power grid is a network that carries electrical energy from power plants to customer premises. One existing power grid is going through a massive and revolutionary transformation process. It is envisioned to achieve the true meaning of technology as “technology for all.” Smart grid technology is an inventive and futuristic approach for improvement in existing power grids. Amalgamation of existing electrical infrastructure with information and communication network is an inevitable requirement of smart grid deployment and operation. The key characteristics of smart grid technology are full duplex communication, advanced metering infrastructure, integration of renewable and alternative energy resources, distribution automation and absolute monitoring, and control of the entire power grid. Smart grid communication infrastructure consists of heterogeneous and hierarchical communication networks. Various layers of smart grid deployment involve diverse sets of wired and wireless communication standards. Application of smart grids can be realized in the facets of energy utilization. Smart grid communication architecture can be used to explore intelligent agriculture applications for the proficient nurturing of various crops. The utilization, monitoring, and control of various renewable energy resources are the most prominent features of smart grid infrastructure for agriculture applications. This paper describes an implementation of an IoT-based wireless energy management system and the monitoring of weather parameters using a smart grid communication infrastructure. A graphical user interface and dedicated website was developed for real-time execution of the developed prototype. The prototype described in this paper covers a pervasive communication infrastructure for field area networks. The design was validated by testing the developed prototype. For practical implementation of the monitoring of the field area network, multiple sensors units were placed for data collection for better accuracy and the avoidance of estimation error. The developed design uses one sensor and tested it for IoT applications. The prototype was validated for local and wide area networks. Most of the present literature depicts a design of various systems using protocols such as IEEE 802.15.1 and IEEE 802.15.4, which either provide restricted access in terms of area or have lower data rates. The protocols used in developed system such as IEEE 802.11 and IEEE 802.3 provide ubiquitous coverage as well as high data rates. These are well-established and proven protocols for Internet applications and data communication but less explored for smart grid applications. The work depicted in this paper provides a solution for all three smart grid hierarchical networks such as home/field area networks, neighborhood area networks, and wide area networks using prototype development and testing. It lays a foundation for actual network design and implementation. The designed system can be extended for multiple sensor nodes for practical implementation in field area networks for better accuracy and in the case of node failure.

An Exploration of the Three-Layer Model Including Stakeholders, Markets and Technologies for Assessments of Residential Smart Grids

In this paper, a framework is presented for the evaluation of smart grid environment which is called the three-layer model. This three-layer model comprises three specific categories, or ‘layers’, namely, the stakeholder, market and technologies layers. Each layer is defined and explored herein, using an extensive literature study regarding their key elements, their descriptions and an overview of the findings from the literature. The assumption behind this study is that a solid understanding of each of the three layers and their interrelations will help in more effective assessment of residential smart grid pilots in order to better design products and services and deploy smart grid technologies in networks. Based on our review, we conclude that, in many studies, social factors associated with smart grid pilots, such as markets, social acceptance, and end-user and stakeholder demands, are most commonly defined as uncertainties and are therefore considered separately from the technical aspects of smart grids. As such, it is recommended that, in future assessments, the stakeholder and market layers should be combined with the technologies layer so as to enhance interaction between these three layers, and to be able to better evaluate residential smart energy systems in a multidisciplinary context.

Embedded Fuzzy Logic Controller and Wireless Communication for Home Energy Management Systems

Energy management systems in residential areas have attracted the attention of many researchers along the deployment of smart grids, smart cities, and smart homes. This paper presents the implementation of a Home Energy Management System (HEMS) based on the fuzzy logic controller. The objective of the proposed HEMS is to minimize electricity cost by managing the energy from the photovoltaic (PV) to supply home appliances in the grid-connected PV-battery system. A fuzzy logic controller is implemented on a low-cost embedded system to achieve the objective. The fuzzy logic controller is developed by the distributed approach where each home appliance has its own fuzzy logic controller. An automatic tuning of the fuzzy membership functions using the Genetic Algorithm is developed to improve performance. To exchange data between the controllers, wireless communication based on WiFi technology is adopted. The proposed configuration provides a simple effective technology that can be implemented in residential homes. The experimental results show that the proposed system achieves a fast processing time on a ten-second basis, which is fast enough for HEMS implementation. When tested under four different scenarios, the proposed fuzzy logic controller yields an average cost reduction of 10.933% compared to the system without a fuzzy logic controller. Furthermore, by tuning the fuzzy membership functions using the genetic algorithm, the average cost reduction increases to 12.493%.

An Incentive-Based Multistage Expansion Planning Model for Smart Distribution Systems

The deployment of smart grids has facilitated the integration of a variety of investor assets into power distribution systems, giving rise to the consequent necessity for positive and active interaction between those investors and local distribution companies (LDCs). This paper proposes a novel incentive-based distribution system expansion planning model that enables an LDC and distributed generation (DG) investors to work in a collaborative way for their mutual benefit. Using the proposed model, the LDC would establish a bus-wise incentive program based on long-term contracts, which would encourage DG investors to integrate their projects at specific system buses that would benefit both parties. The model guarantees that the LDC will incur minimum expansion and operation costs while concurrently ensuring the feasibility of DG investors' projects. To derive appropriate incentives for each project, the model enforces several economic metrics including internal rate of return, profit investment ratio, and discounted payback period. All investment plans committed to by the LDC and the DG investors for the full extent of the planning period are then coordinated accordingly. Several linearization approaches are applied to convert the proposed model into an MILP model. The intermittent nature of both system demand and wind- and PV-based DG output power is handled probabilistically, and a number of DG technologies are taken into account. Case study results have demonstrated the value of the proposed model.

Sources of risk and uncertainty in UK smart grid deployment: An expert stakeholder analysis

The shift to increasingly smarter grids will require preparation and planning on the part of a diverse selection of current and future stakeholders. There are substantive sources of uncertainty that will impact on the adoption of smarter grid solutions. Risks and uncertainties are placed in one of seven categories: markets, users, data and information, supply mix, policy, investment conditions, and networks. Each of these has the potential to add risk to the planning profiles of the stakeholders involved. Here, UK stakeholders drawn from industry, government, regulators, and academia are canvassed about potential sources of uncertainty within the UK’s electricity sector and the attendant risks that might be engendered by them.

Analysis of the World Experience of Smart Grid Deployment: Economic Effectiveness Issues

Despite the positive dynamics in the growth of RES-based power production in electric power systems of many countries, the further development of commercially mature technologies of wind and solar generation is often constrained by the existing grid infrastructure and conventional energy supply practices. The integration of large wind and solar power plants into a single power grid and the development of microgeneration require the widespread introduction of a new smart grid technology cluster (smart power grids), whose technical advantages over the conventional ones have been fairly well studied, while issues of their economic effectiveness remain open. Estimation and forecasting potential economic effects from the introduction of innovative technologies in the power sector during the stage preceding commercial development is a methodologically difficult task that requires the use of knowledge from different sciences. This paper contains the analysis of smart grid project implementation in Europe and the United States. Interval estimates are obtained for their basic economic parameters. It was revealed that the majority of smart grid implemented projects are not yet commercially effective, since their positive externalities are usually not recognized on the revenue side due to the lack of universal methods for public benefits monetization. The results of the research can be used in modernization and development planning for the existing grid infrastructure both at the federal level and at the level of certain regions and territories.

NB-PLC channel: Estimation of periodic impulsive noise parameters and mitigation techniques

Narrowband Power Line Communication (NB-PLC) plays a key role in the deployment of smart grid, since it is a widely spread technology for smart grid applications and systems, like the Advanced Metering Infrastructure (AMI) system. In this paper, we study the characteristics of the NB-PLC channel and noise. A method is proposed to estimate the occurrence and duration of the dominant category of noise, the periodic impulsive noise, which greatly degrades the signal quality. A technique is proposed to mitigate the noise effect, with the use of Luby Transform (LT) codes. The proposed scheme exploits the features of the dominant noise on the NB-PLC channel and mitigates its effect especially in highly noisy environments. An estimation algorithm of the burst time occurrence and its duration is introduced. The system can estimate these parameters with an accuracy in the range of 10−4 and it can work even without channel state information. The proposed scheme is compared to two popular NB-PLC technologies, namely the PRIME and G3-PLC, whereas the results show that it can be very effective under severe noise conditions.

Smart (Electricity) Grids for Smart Cities: Assessing Roles and Societal Impacts

Smart energy and electricity networks are a crucial component in building smart city architectures; their consistent and harmonized inclusion in the smart city design should be carefully considered through a detailed analysis of the impacts (environmental, energy, economic, societal) and the implementation of cost benefit analysis (CBA), not only in terms of managing the grid itself but also in a wider perspective that includes environmental, security, and social aspects. This paper first discusses the main impact that smart grid deployment has, in different respects, in smart cities and then presents a methodology for an extended CBA, able to go beyond the strictly financial aspects. It is based on previous developments at the European level. The methodology conceptually illustrated can naturally be extended to the assessment of proposals for the development of smart cities.

Performance Indicators of Electricity Generation at Country Level—The Case of Italy

Power Grids face significant variability in their operation, especially where there are high proportions of non-programmable renewable energy sources constituting the electricity mix. An accurate and up-to-date knowledge of operational data is essential to guaranteeing the optimal management of the network, and this aspect will be even more crucial for the full deployment of Smart Grids. This work presents a data analysis of the electricity production at the country level, by considering some performance indicators based on primary energy consumption, the share of renewable energy sources, and CO2 emissions. The results show a significant variability of the indicators, highlighting the need of an accurate knowledge of operational parameters as a support for future Smart Grid management algorithms based on multi-objective optimization of power generation. The renewable share of electricity production has a positive impact, both on the primary energy factor and on the CO2 emission factor. However, a strong increase of the renewable share requires that the supply/demand mismatching issues be dealt with through appropriate measures.

A Custom Approach for a Flexible, Real-Time and Reliable Software Defined Utility.

Information and communication technologies (ICTs) have enabled the evolution of traditional electric power distribution networks towards a new paradigm referred to as the smart grid. However, the different elements that compose the ICT plane of a smart grid are usually conceived as isolated systems that typically result in rigid hardware architectures, which are hard to interoperate, manage and adapt to new situations. In the recent years, software-defined systems that take advantage of software and high-speed data network infrastructures have emerged as a promising alternative to classic ad hoc approaches in terms of integration, automation, real-time reconfiguration and resource reusability. The purpose of this paper is to propose the usage of software-defined utilities (SDUs) to address the latent deployment and management limitations of smart grids. More specifically, the implementation of a smart grid’s data storage and management system prototype by means of SDUs is introduced, which exhibits the feasibility of this alternative approach. This system features a hybrid cloud architecture able to meet the data storage requirements of electric utilities and adapt itself to their ever-evolving needs. Conducted experimentations endorse the feasibility of this solution and encourage practitioners to point their efforts in this direction.

Prototyping a Web-of-Energy Architecture for Smart Integration of Sensor Networks in Smart Grids Domain.

Sensor networks and the Internet of Things have driven the evolution of traditional electric power distribution networks towards a new paradigm referred to as Smart Grid. However, the different elements that compose the Information and Communication Technologies (ICTs) layer of a Smart Grid are usually conceived as isolated systems that typically result in rigid hardware architectures which are hard to interoperate, manage, and to adapt to new situations. If the Smart Grid paradigm has to be presented as a solution to the demand for distributed and intelligent energy management system, it is necessary to deploy innovative IT infrastructures to support these smart functions. One of the main issues of Smart Grids is the heterogeneity of communication protocols used by the smart sensor devices that integrate them. The use of the concept of the Web of Things is proposed in this work to tackle this problem. More specifically, the implementation of a Smart Grid’s Web of Things, coined as the Web of Energy is introduced. The purpose of this paper is to propose the usage of Web of Energy by means of the Actor Model paradigm to address the latent deployment and management limitations of Smart Grids. Smart Grid designers can use the Actor Model as a design model for an infrastructure that supports the intelligent functions demanded and is capable of grouping and converting the heterogeneity of traditional infrastructures into the homogeneity feature of the Web of Things. Conducted experimentations endorse the feasibility of this solution and encourage practitioners to point their efforts in this direction.

A Cellular Approach to Net-Zero Energy Cities

Recent growth in the use of photovoltaic technology and a rapid reduction in its cost confirms the potential of solar power on a large scale. In this context, planning for the deployment of smart grids is among the most important challenges to support the increased penetration of solar energy in urban areas and to ensure the resilience of the electricity system. As part this effort, the present paper describes a cellular approach to a Net-Zero energy concept, based on the balance between the potential solar energy supply and the existing consumption patterns at the urban unit scale. To do that, the Geographical Urban Units Delimitation model (GUUD) has been developed and tested on a case study. By applying the GUUD model, which combines Geographic Information Systems (GIS), parametric modelling, and solar dynamic analysis, the whole area of the city was divided into urban cells, categorized as solar producers and energy consumers. The discussion around three theoretical scenarios permits us to explore how smart grids can be approached and promoted from an urban planning perspective. The paper provides insights into how urban planning can be a driver to optimize and manage energy balance across the city if the deployment of smart grids is correctly integrated in its operative process.

Explaining the role of incumbent utilities in sustainable energy transitions: A case study of the smart grid development in China

Smart grids (SGs) have been widely recognized as an enabling technology for delivering sustainable energy transitions. Such transitions have given rise to more complex government-utility-consumer relationships. However, these stakeholder relationships remain largely under-researched. This paper critically examines and explains the role of incumbent utilities in sustainable energy transitions, using SG developments in China as a case study. We have three major findings. First, China has developed an incumbent-led model for deploying SGs. Second, two incumbents, the major-state-owned grid companies, act as enablers of SG deployment. They are strategic first-movers and infrastructure builders of SGs. They have also developed five types of networks as they increasingly reach out to other state actors, businesses, and electricity consumers. Thirdly, these two grid companies also act as a fundamental block to structural changes in socio-technical regimes. Disincentives to these large existing grid companies coupled with excessive reliance on them to provide public goods have resulted in major weaknesses in China’s incumbent-led model. Our findings have clear policy implications. Innovation in regulating incumbents is needed in order to provide sufficient regulatory incentives for advancing SG developments in China.

Detection of non-technical losses in smart meter data based on load curve profiling and time series analysis

The advent and progressive deployment of the so-called Smart Grid has unleashed a profitable portfolio of new possibilities for an efficient management of the low-voltage distribution network supported by the introduction of information and communication technologies to exploit its digitalization. Among all such possibilities this work focuses on the detection of anomalous energy consumption traces: disregarding whether they are due to malfunctioning metering equipment or fraudulent purposes, strong efforts are invested by utilities to detect such outlying events and address them to optimize the power distribution and avoid significant income costs. In this context this manuscript introduce a novel algorithmic approach for the identification of consumption outliers in Smart Grids that relies on concepts from probabilistic data mining and time series analysis. A key ingredient of the proposed technique is its ability to accommodate time irregularities – shifts and warps – in the consumption habits of the user by concentrating on the shape of the consumption rather than on its temporal properties. Simulation results over real data from a Spanish utility are presented and discussed, from where it is concluded that the proposed approach excels at detecting different outlier cases emulated on the aforementioned consumption traces.

Integration of PV and EVs in unbalanced residential LV networks and implications for the smart grid and advanced metering infrastructure deployment

Voltage unbalance is a relevant problem that causes a less efficient operation of the system due to higher energy losses and lower hosting capacity. Unbalance has often been neglected by distribution system operators due to the lack of monitoring data in the low voltage (LV) grid. However, the massive deployment of smart metering in recent years in many countries provides very valuable information to detect unbalance. Moreover, in the current context of increasing presence of single-phase distributed energy resources connected to LV networks, such as electric vehicles (EVs) and photovoltaic (PV) generation, unbalance is bound to increase.This article investigates the technical impact of future integration of EV and PV in LV unbalanced networks. This paper has assessed the daily energy losses and voltage problems as load unbalance gradually increases, based on load flow analysis on an hourly basis, considering residential demand and homogeneously distributed EV and PV. The analysis has been carried out for several rural and semi-rural LV networks and various scenarios of demand level and penetration degree of EV and PV. The three-phase load flow analysis is computed using the forward-backward sweep algorithm.Furthermore, this work discusses the implications for the deployment of supervision and monitoring solutions based on advanced metering infrastructure (AMI). Their implementation should be prioritized in more loaded and longer networks where high integration of distributed energy resources is expected so that unbalance can be detected and corrective actions can be applied.

Assessment of an Adaptive Load Forecasting Methodology in a Smart Grid Demonstration Project

This paper presents the implementation of an adaptive load forecasting methodology in two different power networks from a smart grid demonstration project deployed in the region of Madrid, Spain. The paper contains an exhaustive comparative study of different short-term load forecast methodologies, addressing the methods and variables that are more relevant to be applied for the smart grid deployment. The evaluation followed in this paper suggests that the performance of the different methods depends on the conditions of the site in which the smart grid is implemented. It is shown that some non-linear methods, such as support vector machine with a radial basis function kernel and extremely randomized forest offer good performance using only 24 lagged load hourly values, which could be useful when the amount of data available is limited due to communication problems in the smart grid monitoring system. However, it has to be highlighted that, in general, the behavior of different short-term load forecast methodologies is not stable when they are applied to different power networks and that when there is a considerable variability throughout the whole testing period, some methods offer good performance in some situations, but they fail in others. In this paper, an adaptive load forecasting methodology is proposed to address this issue improving the forecasting performance through iterative optimization: in each specific situation, the best short-term load forecast methodology is chosen, resulting in minimum prediction errors.