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An unreliable supply of grid electricity has a strong negative impact on industrial and commercial profitability as well as on household activities and government services that rely on electricity supply. This unreliable grid electricity could be a result of technical and security factors affecting the grid network. Therefore, this study aims to investigate the effects of technical and security factors on the transmission and distribution of grid electricity in Uganda.

This study used the ordinary least squares (OLS) and autoregressive distributed lag (ARDL) models to examine the effects of technical and security factors on grid electricity reliability in Uganda. The study draws upon secondary time series monthly data sourced from the Uganda Electricity Transmission Company Limited (UETCL) government utility, which transmits electricity to both distributors and grid users. Additionally, data from Umeme Limited, the largest power distribution utility in Uganda, were incorporated into the analysis.

The findings revealed that technical faults, failed grid equipment, system overload and theft and vandalism affected grid electricity reliability in the transmission and distribution subsystems of the Ugandan power grid network. The effect was computed both in terms of frequency and duration of power outages. For instance, the number of power outages was 116 and 2,307 for transmission and distribution subsystems, respectively. In terms of duration, the power outages reported on average were 1,248 h and 5,826 h, respectively, for transmission and distribution subsystems.

This paper investigates the effects of technical and security factors on the transmission and distribution grid electricity reliability, specifically focusing on frequency and duration of power outages, in the Ugandan context. It combines both OLS and ARDL models for analysis and adopts the systems reliability theory in the area of grid electricity reliability research.

Nowadays, the increase in the capacity of batteries has laid the foundations for a broader diffusion of electric mobility. However, electric mobility is causing a growing electricity demand as well as the need to increase the diffusion of suitable charging stations. Within these last challenges, drawing on the recent literature, this chapter provides a critical and wide-ranging review of papers dealing with the formulation of the problem of the localisation of electric vehicle (EV) charging points. This problem is approached considering the electric charging infrastructure technologies, localisation criteria and related methodologies. This review shows how the ‘electric mobility revolution’ applies the technological innovations provided by the energy supply systems, and the location of these systems within the urban contexts. Since the technological innovations have different options, achieving an international standard of charging systems is still far away. Moreover, as there are several criteria, parameters and methodologies, and some analytical approaches for the localisation of electric vehicle charging points, the formulation of the ‘localisation’ problem should require the application of multi-criteria analysis to be addressed. Finally, the results show that there is no consensus on technologies, criteria, and methodologies to be adopted. Therefore, this wide-ranging analysis of the literature would be useful to support possible benchmarking and systematisation accordingly.

This paper deals with analyzing the relationships between the domains of the Sustainable Development Goals (SDGs) and the Missions envisaged by the National Recovery and Resilience Plan (NRRP). Specifically, the authors refer to Mission 2 (Green revolution and ecological transition) and to the statistical indicators related to the M2C1 component (Circular economy and sustainable agriculture).

The numerous data available were analyzed at a regional level using multivariate statistical methodologies (Totally Fuzzy and Relative method) capable of summarizing the various information to evaluate the current situation relating to the “circular economy and sustainable agriculture” component. The presence of multiple updated data allows for the development of a holistic approach to the evaluation of the local government policies in place and to be able to monitor the progress of the subsequent intervention policies of the Italian government.

No Findings.

NRRP represents an opportunity for development for the area, providing for reforms and substantial investments for the promotion of circular economy solutions, the improvement of the capacity for efficient and sustainable waste management, the strengthening of the infrastructures for treatment of waste and separate collection, the reduction of the North/South gap.

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.

This research studies the impact of introducing distributed generators (DGs) into a distribution network. The aim of this paper is to optimally site DGs based on economic, environmental and reliability indices are presented.

The considered network was modelled by using the network’s line parameters and capacity of the load bus with the help of Power System Analysis Toolbox. The location of the DG is based on voltage stability index and power loss reduction index. The DG energy sources considered are the diesel generator, solar photo-voltaic (PV) and wind generator, and the objectives were to minimize cumulative cost while maximizing reliability of the network. The Advanced Interactive Multidimensional Modelling System was used for the mathematical modelling.

The obtained results in the cases of introducing renewable energy into a network improves network performance. The benefits of renewable energy on the distribution network measured in terms of electricity production cost, gas emission cost, fuel cost and value of energy not supplied were positive. The research also showed that the total benefit of renewable energy reduces as the price of the renewable generators increases.

This paper introduces a new approach to determining the optimal location of DG for reducing line losses and improved voltage profile. A new cost modelling function based on external grid power transfer cost, technical losses and cost because of the various energies source is also introduced.

The purpose of this paper is to understand the issues related to the deployment of renewable electricity technologies (RETs) in remote indigenous communities by examining the views of key informants in a remote northern Ontario community through the lens of a wicked problem approach, with the goal to identify policy direction and strategies for the further development of renewable electricity projects.

The paper uses semi-structured interviews with community key informants, informed discussions with community members and energy conference participants and literature reviews of academic, policy and utility documents as complementary data sources for triangulation of results.

According to informants, the complexity surrounding the deployment of RETs in remote Canadian indigenous communities is the result of different stakeholder perspectives on the issues that RETs are expected to address. Furthermore, institutional complexity of the electricity generation system and uncertainty over both the choice of off-grid renewable technology and the future of electricity generation systems structure and governance add to this complexity.

Given the governments’ legal obligation to consult with indigenous people for projects within their territories, community perspectives provide insights for policy design to support both the deployment of RETs and address indigenous communities sustainability goals.

This paper offers views and opinions of community members from an off-grid Canadian indigenous community. Community members describe how they envision their electricity systems and the desired contribution of community owned renewable electricity generation to increase local control and economic development.

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 study aims to focus on the nexus between off-grid systems and impacts on islands and remote villages in Ghana by investigating the sources and cost of energy, willingness to pay for electricity and impacts of off-grid energy on the local economy, education, health, social activities, the environment and migration.

Data were obtained from 110 households; heterogeneous impact analysis of off-grid technologies, average treatment effect by inverse probability weights (IPW) and inverse probability weighted regression adjustment (IPWRA) models were used to analyse the data.

The sources of energy are gas, kerosene, wood fuel and dry-cell battery. All households in communities with neither electricity nor off-grid system were willing to pay for electricity. Households without off-grid systems (US$8.1) were willing to pay higher amounts per month for electricity. The off-grid technologies improve the local economy, social activities, security, the environment, education and health as well as reduce out-migration.

Most of the literature on mini-grid/off-grid systems have been from the engineering and the technical perspective, with a few on the socioeconomic impacts of the systems and consumer engagements. Besides, methods including descriptive statistics, energy technology sustainability framework and qualitative analysis were used in these studies. Nevertheless, the authors used a more rigorous method of the doubly robust inverse probability weighted regression adjustment model and a heterogeneous method to model the impact analysis of off-grid systems.

Due to technological improvement and development of the vehicle-to-home (V2H) concept, electric vehicle (EV) can be considered as an active component of net-zero energy buildings (NZEBs). However, to achieve more dependable results, proper energy analysis is needed to take into consideration the stochastic behavior of renewable energy, energy consumption in the building and vehicle use pattern. This study aims to stochastically model a building integrating photovoltaic panels as a microgeneration technology and EVs to meet NZEB requirements.

First, a multiobjective nondominated sorting genetic algorithm (NSGA-II) was developed to optimize the building energy performance considering panels installed on the façade. Next, a dynamic solution is implemented in MATLAB to stochastically model electricity generation using solar panels as well as building and EV energy consumption. Besides, the Monte Carlo simulation method is used for quantifying the uncertainty of NZEB performance. To investigate the impact of weather on both energy consumption and generation, the model is tested in five different climatic zones in Iran.

The results show that the stochastic simulation provides building designers with a variety of convenient options to select the best design based on level of confidence and desired budget. Furthermore, economic evaluation signifies that investing in all studied cities is profitable.

Considering the uncertainty in building energy demand and PV power generation as well as EV mobility and the charging–discharging power profile for evaluating building energy performance is the main contribution of this study.