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The path congestion and communication risks of electric power communication network have emerged as the carried businesses are becoming more and more heavy. In this paper, a multi-objective optimization method for power communication network routing considering the importance of the carried businesses is proposed to reduce load imbalance and transmission risk. Firstly, information entropy is introduced as the objective of communication network load balancing optimization. And a risk assessment model for power communication network nodes and links is established. Then fuzzy membership functions are adopted to singularize the two objectives to jointly optimize path congestion and communication risks. The device nodes are dynamically divided according to the carried businesses to pursue the global optimization of the power communication network in which the Yen's algorithm is adopted. Finally, this paper uses the IEEE 30-bus communication network to carry out case simulations and analyzes the proposed method to verify the effectiveness and feasibility.

Demand side management is a useful and necessary tool in smart grid energy management system to reduce total power demand during peak demand periods and hence, enhancing grid sustainability and reducing overall cost. This paper discusses a new load shifting approach for demand side management in smart grid energy management. This approach optimizes the consumption curves of household, commercial and industrial consumers. The proposed algorithm in this approach minimizes the cost incurred by users while taking into account users' individual preferences for the loads by setting priorities and preferred time intervals for load scheduling.

With the fast growth of the global economy, energy supply and demand have a strong impact on social, economic, and environmental aspects. As a consequence, this has pushed the decision-makers to formulate objectives, guiding economic policies toward sustainable goals. The process is known as Sustainable Development Goals (SDGs) that have been proposed by the United Nations. This being said, the energy sector is a vital domain with a vast potential for improvments in terms of technologies and ligistalations. Solar energy is among the most efficient solutions proposed to reduce the economic and environmental footprints of energy. In this frame, the current paper aims to localize solar energy within SDGs and analyze the contribution of the solar energy towards the achievement of the SDGs. Moreover, the current work highlights the contributions of Mohammed bin Rashid Al Maktoum (MBR) Solar Park in the United Arab Emirates to achieving the SDGs. Indeed, the MBR Solar Park concept offers valuable insights of environmental impacts by deploying clean and affordable energy sources in place of conventional fossil fuel power plants that are still heavily used in the region. The MBR Solar Park operation has already mitigated 6.5 million tonnes of carbon dioxide equivalent and this number will likely rise when all phases are installed and operational. Moreover, it has been shown that MBR Solar Park achieve several SDGs such SDG 8: decent work and economic growth, SDG 9: industry, innovation and infrastructure, SDG 11: sustainable cities and communities, and SDG 15: life on land.

Cloud computing and sustainability have become part of a core strategy in organizations globally and locally, since their characteristics assist both businesses and individuals to become unique and exclusive in their work and study. Businesses and individuals should integrate sustainability in their strategy and to include cloud computing technology as a tool for sustainable work, especially in the Information Technology (IT) departments to cut costs and increase efficiencies and productivity. This paper examines European organizations' awareness of cloud computing and sustainability opportunities and risks, via an online survey targeting 56 Information Technology managers in Europe. A Cloud Computing Conceptual model was developed using structural equation modeling (SEM) to evaluate the survey results. The study results confirmed that cloud computing technology opportunities, including sustainability in the organization's strategy, will enhance their job performance and job satisfaction, use and awareness; however, security, privacy and risks are still a major concern.

Increasing the use of electric vehicles (EVs) is regarded as a step in the right direction to reduce air pollution and carbon emissions. However, a dramatic increase of EV and charging stations has raised voltage quality and harmonic distortion issues that affect the performance of integrated renewable power sources (wind and solar) and smart-grid electrical transmission networks. This paper models an integrated electric vehicle charging and battery storage system operating in the presence of unpredictable wind and solar power sources. The aim is to enable the design of an electrical control system that develops the correct duty cycle to stabilize and regulate the voltage at the dc/dc power conversion station. Simulations are performed to evaluate energy management by the proposed control system. The proposed system effectively manages the electric power on the grid by drawing power from the batteries at peak times and then charging them in off-peak times, reducing the load on the converter and enabling the reduction of charging time for electric vehicles. A constant voltage is achieved on the grid irrespective of fluctuations in renewable energy generation and in the load.

Closed-loop supply chain networks are gaining research popularity due to environmental, economic and social concerns. Such networks are primarily designed to overcome carbon footprints and to retrieve end of life products from customers. This study considers a multi echelon closed-loop supply chain in the presence of machine disruption. A multi-objective model is presented to optimize the total cost, the total time and emissions in a closed-loop supply chain network. The aim is to analyze the trade-off between the objectives of cost, time, and emissions and how these decisions are impacted by the selection of different available machines. A number of solution approaches are tested on a case study from the tire industry. The results suggest the improved performance of the hybrid heuristic and the importance of controlling disruption in a closed-loop supply chain network. Furthermore, there is a trade-off between the different objective functions which can help the decision maker to choose a particular solution according to the preference of an organization. Finally, conclusion and future research avenues are provided.

Abstract Mitigating the effects of environmental deterioration requires a focus on not just CO2 emissions from energy consumption, but also environmental pollution from industry sectors. To reach this goal, recent studies have extended ecological footprint (EF) analysis to identify the ecological drivers of various key industry sectors. The role of the phosphorus (P) industry on the EF within the environmental Kuznets curve (EKC) framework for China is the emphasis of this study. Autoregressive distributive lag (ARDL) as well as the impulse response function and robustness analysis were used to consider a time from 1985 to 2018. The study verifies the EKC hypothesis for China in both the long and the short run, and indispensable determinants are proposed to be included to assure the model’s fitness and robustness when conducting EF analysis of industry sectors. Energy consumption–based carbon emissions have been verified as the dominant contributor to EF, but P use and urbanization have a significant lagged positive influence on EF in the short run. P exports, in particular, have been highlighted as a critical driver of the EF of China’s P industry. The conducted frequency domain causality test reinforced the above findings and demonstrated bidirectional causality at different frequencies. This work suggests that formulating plausible P export policies to alleviate the conflict between the output of China’s P industry and the environmental sustainability of this industry are necessary. In this context, “multidisciplinary, multidimensional, and practical solutions” are most desirable for sustainable P management.

It is imperative to increase the connectable capacity (i.e., hosting capacity) of distributed generation in order to decarbonise electricity distribution networks. Hybrid generation that exploits complementarity in resource characteristics among different renewable types potentially provides value for minimising technical constraints and increasing the effective use of the network. Tidal, wave and wind energy are prominent offshore renewable energy sources. It is of importance to explore their potential complementarity for increasing network integration. In this work, the novel introduction of these distinct offshore renewable resources into hosting capacity evaluation enables the quantification of the benefits of various resource combinations. A scenario reduction technique is adapted to effectively consider variation of these renewables in an AC optimal power flow-based nonlinear optimisation model. Moreover, the beneficial impact of active network management (ANM) on enhancing the renewable complementarity is also investigated. The combination of complementary hybrid generation and ANM, specifically where the maxima of the generation profiles rarely co-occur with each other and with the demand minimum, is found to make the best use of the network components.

Although considered a current highlight, the concept of intelligent buildings (IB) has not been adopted as quickly and widely as expected. One of the reasons for this is the lack of information and knowledge support to all professionals involved at the design stage of a project. This paper provides a brief overview on the new advances of IB technologies and discusses ways of supplementing the decision making process by adopting two methods for economical and technical aspects of IB applications. It goes on to introduce an on-going research which aims to utilise knowledge based systems to provide comprehensive evaluations to alternatives and decision support to retrofit building projects, when they are being conceptualised.

Introduction Increases in recent times in electricity costs and in associated emissions of greenhouse gases are having an impact on societies to adopt business and lifestyle strategies based on sustainability practices. The emergence of the smart grid (Xinghuo et al., 2011) facilitates both suppliers and consumers of electricity in reducing carbon footprint and improving the reliability and efficiency of electricity generation, distribution and utilization. The smart grid unifies recent developments in the electrical power area with those in information and communication technologies (ICT) to bring to bear changes to business practices and life styles of consumers. The smart grid recognizes the distributed nature of electricity industry and the unifying power of the ICT. Traditional power grids consist of (i) large-scale electricity generators that are located within easy reach of energy resources, (ii) highvoltage transmission lines to bring bulk electricity to load centres that are close to loads, such as industries, cities, townships etc., and (iii) lower voltage distribution networks which in turn distribute electrical power to smaller consumers of electricity. Unlike such traditional power grids, smart grids have distributed energy generation that encompasses both centrally-located large-scale generators with ratings of 100's of megawatts (MWs) and many geographically distributed smaller generators of widely varying sizes from 10's of MWs that use fossil fuels and renewables to a few kilo watts (kW) that may be solar photo voltaic (PV) panels mounted on the roof of a small house. [FIGURE 1 OMITTED] Several geographically distributed power generators need to be integrated into the smart grid, recognizing the varying capacities, characteristics and technologies associated with generators (Figure 1). Electricity generated using renewable energy sources, such as photovoltaic (PV) solar panels and wind turbines, is variable depending upon the season, weather conditions and the period of any given day. This variability has a strong influence on the delivery of reliable power to consumers. Storage of electrical energy to dampen the effects of variability in the power from renewables is therefore an important aspect of the smart grid. Various types of energy storage: pumped hydro storage, batteries, fuel cells, flywheels etc. need to be integrated into a smart grid. Such distributed energy storages in the grid may serve different networks within the grid so that they continue to operate as self-powered islands during outages resulting from natural causes or system faults (Nourai & Keane, 2010). The electricity generated by solar PV panels and by some wind generators is in the form of direct current (DC). This DC power must be converted (or inverted) to make alternating current (AC) power to enable connection to an AC smart grid. Smart grids need smart inverters with controls to maximise renewable power utilization, and to supply power to either the local load and/or the grid (Xinghuo et al., 2011). The smart grid needs to integrate the action of generators, energy suppliers and customers. The smart grid must provide suitable multi-way communication of relevant information between various business actors associated with the grid. The smart grid includes even a small household as a business actor into its business model because a household contributes towards sustainable business outcomes. There are many research papers on smart grids with a focus on large power systems (Brown, 2008; Ipakchi & Albuyeh, 2009; and Farhangi, 2010) that emphasize the importance of pervasive control and monitoring requirements in a smart grid. They point out the convergence of ICT with power system engineering. There are also many publications (Guinard, 2011; Kamilaris, et al., 2011) that deal with energy management at household levels using the ICT strategy, such as Web of things. …