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Deploying renewable energy to unit design energy-efficient technologies may fulfill the additional demand of various energy-intensive industries for their sustainability and resiliency. Multiple Stage Evaporator (MSE) is one of the most energy-intensive units used to extract the water content of the weak liquor in various industries, including the paper industry. This energy intensiveness may be reduced by integrating various Energy Reduction Schemes (ERSs). Hence, this work proposes a ERSs integrated MSE model to analyze its energy efficiency. These ERSs includes Thermo-Vapor Compressor, Steam-, Feed- Split, Feed Preheater, and Flash Tanks. Further, the performance of the proposed model is investigated under two important real-time plant complexities: Boiling Point Elevation and Fouling to achieve more realistic results. The performance analysis is initiated with the formulation of a nonlinear constrained optimization problem to increase the steam economy (SE). Also, the simulation is extended to validate at two different product concentrations (52% and 65%) by employing state-of-art optimization algorithms: CONOPT, and SCA in GAMS and MATLAB respectively. The simulated results shows an increment 1.64% and 1.37% of SE for both 52% and 65% concentration of weak liquor respectively in case of CONOPT than SCA. Also, the waste heat of the condensate, feed, and product may be further utilized for the heat recovery by incorporating the flash tanks which leads to a countable energy saving. Eventually, integrating the solar fields: PTC and LFR ensures a notable reduction in conventional heat utilization by 85.96% and 92.85%, respectively and hence, enhance the energy efficiency. • Expounded energy modeling of ERSs based MSE with BPE and Fouling. • Implementation of NLP and metaheuristic approaches for performance optimization. • Reutilization of waste heat to maximize the energy efficiency. • Integration of solar fields (PTC and LFR) to reduce conventional fuel utilization. • Prospecting the challenges and direction of energy management optimization. [ABSTRACT FROM AUTHOR]

Home energy consumption is increasing, and renewable energy sources are being deployed. The use of renewable energy sources as an alternative to fossil fuels and nuclear energy is a significant opportunity for reducing CO 2 emissions. However, carbon emissions from electricity generation are dependent on the type of renewable energy source and the quantity of the electricity that is produced. With the emergence of the smart grid, residents are able to reduce their electricity consumption by shedding the power usage in their homes. The objective of this study is to smooth power peak demand and diminish CO 2 emissions. This paper describes the power shedding benefits of reducing energy consumption and CO 2 emissions. This reduction of CO 2 emissions eliminates the need for auxiliary power plants in the grid in the case of peak demand points and the need to switch to renewable energy sources. In this study, we prove that emerging information and communication technology can reduce energy use and CO 2 emissions. Wireless communication architecture is introduced in this study to increase grid flexibility and rapidity in the data flow among all of the components in the proposed system. Our proposed system with local renewable generation can reduce CO 2 emissions nearly 72% of all CO 2 emissions when all appliances are supplied with the grid. With our load shedding algorithm, the CO 2 emissions decrease nearly 91%. The yearly estimation shows that our system can reduce 62% of CO 2 emissions and 37% of consumed power. In this paper, we introduce an efficient architecture of a smart home energy management system and propose a shedding algorithm for home energy usage. This system is based on wireless communication among home appliances, a home management and control system, a grid management and control system and domestic renewable energy sources. Our proposed system, which employs wireless communication, domestic renewable generation and a power shedding algorithm, can operate in conjunction with future smart grids by applying real-time data, such as peak demand points. Numerous real data sets permitted the development of some of the statistics in the system results. [ABSTRACT FROM AUTHOR]

Energy hubs as a multi-carrier energy system with various energy carriers and conversions have been integrated with smart grids to increase the efficiency, flexibility, and reliability of the network. Today, scheduling multi-energy hubs (MEH) is one of the challenging issues in smart grids. In this paper, the optimal schedule of interconnected MEHs based on the robust optimization in the presence of electric vehicles (EVs) is proposed. A robust optimization approach is considered to deal with uncertainties of electrical price, renewable energy resources (RESs) generations, and electrical loads. In this paper, MEHs network include commercial, industrial, and residential energy hubs. The energy consumption of MEHs consist of electrical, water, gas, and heat. RESs, demand response (DR) programs, heat and electrical energy storage devices are used to supply the energy demand. The aim of the proposed model is reducing the total cost of operation and carbon emission. The price-based demand response program is applied to shift the power consumption from on-peak to off-peak times in response to the price signal. Finally, the problem is solved for the three cases with CPLEX under YALMIP MATLAB. The results illustrate the effectiveness of the proposed model to achieve optimal scheduling of MEHs. The proposed problem is organized in three scenarios, among which the scenario I determines optimal scheduling of MEHs, using robust optimization method. The scenario II investigates the problem with deterministic model. The scenario III evaluates the problem applying robust optimization method without DR program and energy storage device consideration in autonomous EHs. The numerical results show that the total operation cost is increased 15.46% in scenario I compared with the scenario II due to applying the worst-case of uncertainties in robust optimization approach. • An optimal scheduling of Multi-Energy Hubs is proposed with energy costs and emission. • Electrical, heat, gas and water demands, RESs, storages, and EVs is considered with DR. • A robust optimization is used to cover uncertainties of price, generation of RESs and loads. • Three interconnected EHs as MEHs including commercial, industrial and residential sectors. • The proposed problem is optimized in three cases and the results are compared with each other. [ABSTRACT FROM AUTHOR]

The special volume on green and sustainable chemistry and engineering has fourteen papers that were considered relevant to the present day issues and discussion, such as adequate use of raw materials and efficient energy, besides considering renewable sources for materials and energy; and changing economical canons towards circular economy. Businesses, governments and Society are facing a number of challenges to tread the sustainability path and provide wellbeing for future generations. This special volume relevance provides discussions and contributions to foster that desirable future. Chemicals are ubiquitous in everyday activities. Their widespread presence provides benefits to societies’ wellbeing, but can have some deleterious effects. To counteract such effect, green engineering and sustainable assessment in industrial processes have been gathering momentum in the last thirty years. Green chemistry, green engineering, eco-efficiency, and sustainability are becoming a necessity for assessing and managing products and processes in the chemical industry. This special volume presents fourteen articles related to sustainable resource and energy use (five articles), circular economy (one article), cleaner production and sustainable process assessment (five article), and innovation in chemical products (three articles). Green and sustainable chemistry, as well as sustainable chemical engineering and renewable energy sources are required to foster and consolidate a transition towards more sustainable societies. This special volume present current trends in chemistry and chemical engineering, such as sustainable resource and energy use, circular economy, cleaner production and sustainable process assessment, and innovation in chemical products. This special volume provides insights in this direction and complementing other efforts towards such transition. [ABSTRACT FROM AUTHOR]

Educational sector is growing drastically as a result of upward trend of population. These schools require tremendous quantities of energy units to be generated and consumed. As a result, this will impact negatively on the environment by increasing the carbon emissions and depletion of non-renewable energy resources. Moreover, the harsh climate condition contributes substantially to increase the energy consumption in various weather zones in the world. Therefore, several energy efficiency plans have been developed to improve the energy performance of the schools facilities globally. Hence, this paper discusses the energy management program as a sustainable strategy that applicable on the schools. This program is designed for the schools to improve the energy efficiency, indoor environmental quality and adopting the best management practices during the operating stages. This research has developed a customized energy management program for one of the schools in UAE. It has concluded the findings by using computerized hourly thermal modeling. The energy model has evaluated the proposed energy conservation measures and the best practices that were generated by the energy management program steps. This case shows that the energy performance could be improved substantially by 35%. Thus, the energy use index of the audited school that adopted the energy management program has reduced from 438 kWh/m 2 /year to 285 kWh/m 2 /year. The proposed energy management program has been articulated in this study as a consecutive and linear progression. This methodology presents several steps to mitigate the carbon emission by addressing the sustainability dimensions; economic, environment and social aspects. This study discusses the steps and the work flow of developing the energy management program and the anticipated outcomes for the school's buildings. The program considers practical ECMs along with the students and teachers participation and interaction. Furthermore, it highlights the success criteria that assure the sustainability of the energy efficiency at the operating life cycle of school's facilities. [ABSTRACT FROM AUTHOR]

Given the self-declared energy and environmental protection objectives of many car manufacturers responsible companies must use energy-efficient production technologies. The running costs of production sites are a decisive factor in the overhead of automotive production. Therefore, it is important for many operators to reduce those costs in a sustainable way. For this purpose, they attempt to reduce both the energy consumption costs and CO 2 emissions of production systems. However, most components of the energy costs are determined during the very early phases of the product creation process. To achieve an estimation of the energy consumption in this early planning stage, a new suitable forecasting method is required. Therefore, this paper presents an approach for determining the prospective energy consumption by using Methods-Energy Measurement combined with defined energy reference cycles for manufacturing technologies. With this approach, key performance indicators are defined, and the production technologies are divided into basic energy consumers. The average energy values will be determined empirically by using the defined energy reference cycles. With these data, the energy demands for different scenarios are calculated. Thereby, it is possible to estimate the potential energy consumption of complex manufacturing cells. The designed method is validated within a case study of a modern automotive body shop. In summary, the approach contributes to identify and realize sustainable solutions in advance and thus increase the profitability of a factory. [ABSTRACT FROM AUTHOR]

Due to the widespread deployment of distributed energy resources, renewable energies and battery energy storage, the peer to peer (P2P) energy trading schematic has gained the staple attention for improving the energy efficiency and energy flexibility of power grids. This is while, smart demand response programming (DRP) is considered as the bridge between these two indicators of smart grid. Moreover, the subtle point of proliferating P2P schematics is the regulation towards the maximization of social welfare leading to economic profitability of customers and owner's of microgrid and, eventually, reduction of pollutant emission of fossil fuels. Also, uncertainty, aroused by electrical consumption and renewable energy resources, is the core of every considerations, which has to be dealt with intelligent algorithms for strengthening the stability of transactions. On the other hand, compatibility with upper grid's regulations, i.e. power loss and voltage deviation, along with determining fair price of energy trading are the subjects of P2P-based tactics. Therefore, this paper proposes a P2P-based transactive energy sharing architecture, as two stage mixed integer non-linear programming, using smart DRP integrated with machine learning approach, i.e. radial basis neural network. Firstly, the uncertainty of electrical demand and renewable energies are relaxed through short term forecasting. Doing so, the day-ahead transactions of peers are obtained based on their energy management objective, targeting the energy reliability of customers, which energy not supplied criterion has to be equal to zero. Then, participation of customers in DRP, cost of customers, revenue of microgrid's owner and transactions of real time programming are optimally acquired based on Pareto front technique. Also, the simulations are conducted on IEEE 85 bus test system to realize the considerations. The results convey that the profitability of customers and owners is tied with the implementation of smart DRP and accurate forecasting of uncertain variables. In addition, the maximum improvements towards maximizing the revenue of owners and minimizing the cost of customers take place at hours which the electrical consumption is shifted from peaks to off-peaks and mid-peaks, certifying the performance of proposed methodology. [ABSTRACT FROM AUTHOR]

The increasing global consumption of energy and its negative impacts on the environment has been an issue discussed both by academics and practitioners, including in the health sector. Hospitals are major consumers of energy, which leads to increased operating costs, decreased competitiveness, and negative environmental impacts. Energy management in hospitals must be understood as a way to contribute to environmental sustainability and as a way to improve competitiveness. Therefore, the objective of this paper is to propose guidelines for efficient and sustainable energy management in hospitals, developed based on the literature review, the challenges faced and the good practices of sustainable energy management in the hospitals studied, the cross analysis of the case studies, and the authors' expertise. As a result, the eight proposed guidelines are related to culture change, energy consumption management, energy management standard, purchase of renewable energy, green technologies, sustainable hospital buildings, social responsibility programs focused on energy use, and sustainable energy public policies. These guidelines contribute in an applied/managerial way to help managers of public and private hospitals overcome the challenges of energy management and contribute to UN's SDG7 due to its potential to improve energy efficiency and environmental performance, therefore, being a movement towards clean energy. This study also theoretically/scientifically contributes to the academic debate since the empirical findings found in the hospitals studied and the proposition of guidelines deepen and expand the key elements identified in the literature on efficient energy management in hospitals, providing the basis for developing new research on the subject. Energy management in hospitals is discussed from the perspective of sustainability. Challenges need to be overcome for sustainability benefits to be achieved. This work can assist public and private hospitals in developing sustainability. Guidelines for sustainable energy management in hospitals are proposed. [ABSTRACT FROM AUTHOR]

Generation of electricity comes with the emission of toxic gases into the atmosphere by the fossil fueled generators. Along with the promotion in the utilization of renewable energy sources (RES), it is also the duty of the power engineers to arrive at a compromised solution such that less emission of toxic gases occurs with economic generation of electricity. This paper proposes a balanced trade-off method for solving environment constrained economic dispatch (ECED) problems. A novel comparative analysis is performed among proposed ECED method with existing price-penalty-factor (PPF) and fractional programming (FP) methods for solving combined economic emission dispatch (CEED) problems on a 3-unit dynamic test system to sort out the method, which yields a better trade off solution between generation cost and pollutants emitted. An algorithm, following the hunting strategy of wolves, is improvised by incorporating strategies from population-based sine-cosine algorithm along with position updating methods of crows to form a robust hybrid algorithm, which was used as the optimization tool for the study. Involvement of RES diminished the generation cost to 5.5% for both economic dispatch and PPF based CEED, and 6.5% decrease in emission of pollutants was observed due to the same. The generation cost and amount of emitted pollutants, evaluated using proposed ECED approach, were much closer to the economic dispatch and emission dispatch values respectively compared to PPF based and FP based CEED solution. Furthermore, statistical analysis endorses the superiority of the proposed hybrid optimizer over other algorithms presented in the state-of-art literature. • Three different types of CEED methods are studied. • Subject test system is a 3-units RES integrated microgrid system. • Comparative analysis among the generation costs and pollutants emitted is performed. • A novel HMGWO algorithm was proposed as the optimization tool for the study. [ABSTRACT FROM AUTHOR]

Over the last few decades, the use of renewable and clean energy sources has been the core of attention of the researchers. Besides, utilization of the energy hubs as a great innovation for future multi-carrier energy systems is well perceived for integrating intermittent sources of energy into the energy systems, which is surged and bolded in recent years. In this regard, this paper proposes an effective distributed energy management framework for modeling and optimal operation management of clean smart islands based on primal-dual method of multipliers. The primal-dual method of multipliers approach has shown superior performance compared to the alternating method of multipliers for distributed optimization. In this study, two different agents including a smart energy hub and a microgrid comprises of renewable and clean energy sources are considered in the smart island. These two distinct energy systems are assumed to be equipped with communication apparatuses and are intended to negotiate over the energy they need in a proper and completely distributed manner. Results show the effectiveness, accuracy and applicability of the approach for energy communication. • Providing a novel management scheme to properly supply the proposed system. • Incorporating a smart island, a smart microgrid and a SEH in remote areas. • Proposing a fully distributed energy management scheme based PDMM approach. • Investigating the distributed framework which covers demands in a smart island. [ABSTRACT FROM AUTHOR]