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In recent years, the severe environmental degradation and high levels of fossil fuel consumption linked to conventional ship energy systems have drawn attention to the advancement of alternative ship energy systems. Consequently, ship energy systems based on the use of an electrical microgrid are coming to the fore as an increasingly popular alternative solution. However, managing the energy flows within a shipboard microgrid can be highly challenging due to the multiple energy sources (including renewable energy sources) and types of loads involved. Additionally, the integration of an energy storage system has been identified as an effective solution for improving the reliability of shipboard power systems, pointing out the important role of energy storage systems in maritime microgrids and their potential to enhance the energy management process. As such, effective energy management strategies are necessary to optimize performance and ensure that the vessel's energy demands are met while minimizing fuel consumption and reducing cost and environmental impacts. This paper presents a comprehensive review of such strategies and methods recently presented in the literature associated with energy management in shipboard microgrids integrating energy storage systems and examine the different techniques that can be utilized to achieve optimal system performance. Moreover, the paper also sheds light on the future challenges and perspectives imposed by the modern shipboard microgrids operation on the energy/power management of these systems. The aim of this paper is to provide a helpful guideline for researchers and engineers conducting research in the field of electrically powered ships. [Display omitted] • A comprehensive review of EMS for electrical and hybrid ship is presented. • A comprehensive review of ESS which can be used in such ships is presented. • Technologies of ESS and their suitability to ships are discussed and commented. • Future challenges and perspectives imposed by modern SMG operation are presented. [ABSTRACT FROM AUTHOR]

Existing pieces of literature on previous studies advocate the research focus by various researchers to reach the benchmark of energy efficiency of Wastewater Treatment Plants (WWTPs). The driving factors to improve the energy efficiency and mitigate the energy self-sufficiency of WWTP have been identified as the increase in population growth, rising energy costs, and tightening effluent discharge requirements. WWTP economy is directly related to energy consumption and thus affects smart grid economy. There has been limited research on energy self-sufficiency and optimizing the energy demand and cost of WWTP, where the significant contributing factors are in development an optimal pumping system and advanced motor technologies. Moreover, high quality WWTP's effluent depends on the concentration level of biochemical oxygen demand (BOD) and total kjedhal nitrogen (TKN). Even so, WWTPs are always subject to evident nonlinearities and uncertainties, making it difficult to define proper optimization objectives. Besides, controllers and control systems have a strong influence on the performance of the plants. Therefore, existing research gaps to achieve optimal efficiency with minimized energy consumption and costs are the design of the WWTP plant, pumping system, motors, selection of suitable controllers and control systems, and their parameter optimizations to get the optimal output from the plant, switching techniques, challenges and uncertainties associated with plant are highlighted in this paper. Thus, as a novel contribution to the literature, this study aims to review and analyze the history, current issues, and future directions of WWTP control technologies in the context of sustainable development. The rigorous study by the authors in this paper will definitely lead the academic researchers and industry partners toward the development of optimal WWTP technologies with improved efficiency and minimized energy consumption and costs. • Effective control techniques and monitoring of the wastewater treatment plant. • Optimal energy-efficient WWTPs with renewable sources and the utility grid. • Uncertainties of WWTP can be considered for improved operation. • Effective policies should be imposed by combining academics and industry. • Reduced energy consumption and cost can be achieved. [ABSTRACT FROM AUTHOR]

Due to increasing amounts of energy being supplied by intermittent renewable energy sources, future energy systems need to be able to react flexibly to sudden changes. To address this challenge, a large body of research is devoted to improving the utilization of energy flexibility of various types of energy resources on the supply and demand side. This is commonly done by applying mathematical models. The objective of this paper is to review such models and identify common modeling approaches used to quantify and optimize the use of flexible energy resources. The literature review is conducted systematically, encompassing 215 publications that feature 694 models of different energy resources. The main distinction of this work, in comparison to other reviews on the topic of energy flexibility lies in its focus on the mathematical formulation of models of energy resources and the quantification of the models' level of detail. The aim is to identify common modeling approaches and the corresponding research problems they address. The review shows that the majority of research efforts are directed towards the management and optimization of distributed energy resources. The most commonly employed modeling approach involves abstract black-box models with limited levels of detail. Linear programming and meta-heuristics are frequently used to optimize energy flexibility. A critical reflection of the current common practice is conducted and recommendations for future research are formulated. [Display omitted] • Literature review of 215 reports presenting model approaches for energy flexibility. • Categories of research problems identified and deduction of two main research focuses. • Presenting models of common energy resources classified into different model types. • Mostly low level of detail seen in modeling energy flexibility. • Optimization models are used to represent and quantify flexibility. [ABSTRACT FROM AUTHOR]

Improving the efficiency and reducing the pollutants are the critical concerns for any design of power generation plants. Identifying the characteristics of the Combined Cycle Gas Turbine (CCGT) system and locating the optimum operation conditions via simulation models are irreplaceable route due to the huge system and the impossibility of experimental investigations. To that end, this paper presents modelling analysis with the aim of enhancing the performance and optimization conditions seeking of the (CCGT) power plant with various configurations. The developed simulation models are integrated to encapsulate thermal analysis according to thermodynamics principles, optimization techniques, error analysis, and performance metrics assessment of the various CCGT system configurations using the MATLAB 10A software. A statistical tool, ANOVA, is utilized to assess the results and to develop correlations between the power outputs and performance metrics of the CCGT plants. The new correlations which are developed within the frame of this work are of acceptable accuracy for all the considered range of the simulation data. The coefficient of determination ( R 2 ) is calculated as 0.985 which is considered satisfactory as well. The validity of the correlations is investigated against actual performance and operation data extracted from an actual power generation plant, the MARAFIQ CCGT plant in KSA. Consequently, an error analysis which is carried out considering the actual operation and performance records of MARAFIQ CCGT plant as a benchmark proved the validity of the model. An error of about 0.8104% is found. The operation parameters and performance metrics of the CCGT plant are ultimately assessed against variations of selected parameters via the developed model. Adaptive Neuro-Fuzzy System (ANFIS) is used as an optimization technique. The highest attained power output and thermal efficiency were 1540 MW and 61%, respectively. Turbine inlet temperature is found to be the key parameter for the optimum performance (power and thermal efficiency). The models developed in this work are a powerful tool for analyzing and optimising CCGT which take the place of very expensive and strenuous experimental works. [ABSTRACT FROM AUTHOR]

The growing interest in fully decarbonizing worldwide energy systems requires abandoning traditional generation expansion planning in favour of other flexibility-enabling energy system planning tools allowing the integration of energy storage and sector coupling. Therefore, this paper proposes a mixed-integer linear programming formulation focused on enabling flexibility provision on integrated energy systems targeting independent sizing of power and energy capacities for simultaneous generation and storage expansion planning. The optimization problem minimizes investment, maintenance, operation and emissions costs over a 20 year horizon with hourly resolution. In this context, islands represent suitable study cases for the energy transition due to their exceptional renewable availability, and fast-paced development; despite being regions with extreme external dependence and isolation. In particular, the island of Santiago, Cape Verde is selected as study case given its existing targets regarding reaching 50 and 100% renewable shares in 2030 and 2040, its data availability, and the extreme seasonal variation in wind and solar resources. Four scenarios are considered. The first and second dismiss flexibility: business as usual (BAU), and another one aligned with the government goals (Green). Then, the other two exploit it: one equivalent to Green, FlexG, and a last one finding the Optimal. In addition, three energy demand growth levels are considered in order to reduce uncertainty, corresponding to 1, 3 and 5%. Last, a sensitivity analysis with three additional scenarios is performed to provide a thorough view of Cape Verde's energy future. The results highlight the importance of flexibility exploitation which provides up to 85% savings and allows to decarbonize other sectors via electrification. • Solar and hydro pumped storage drive the transition. • Wind power's role increases in hydrogen intensive and surface constraint scenarios. • Integrating flexibility into generation expansion planning halves power needs. • The current paradigm is the most expensive option, doubling emissions in 20 years. • The Optimal configuration achieves 96% renewable penetration. [Display omitted] [ABSTRACT FROM AUTHOR]

Since solar energy is intermittent, finding the best solutions for solar operated devices is a challenge. Multiple techniques exist to reach the best solutions for optimal solar operated devices. A thorough review of solar energy systems' optimization methods and tools is presented in this work. The intelligent optimization techniques for solar energy systems are discussed, including their functions, constraints, contributions, mathematical models, and analysis methods. Optimization studies using new and traditional generation techniques are analyzed, and a few optimization methods, including combined hybrid algorithms, are presented. New generation artificial intelligence algorithms have been most widely used during the last decade, needing less computational time. They have good convergence and better accuracy than traditional optimization methods. They can scan local and global optima and do robust calculations. Solar system optimization has demonstrated remarkable benefits in size, load demand, and electricity output. The improvements reduce operating expenditures, power losses, and peak output integration and controllability. With a 50% rise in power prices, the optimal number of solar collectors rises by approximately 25%. However, with adjustment as per optimization techniques, the solar absorption cooling system's maximum thermal efficiency can be increased up to 75%. The present study recommends using two or more algorithms to overcome the curbs of a single algorithm. The main aim of the optimization strategies, according to this assessment, is to reduce capital expenditures, operation and maintenance expenses, and emissions while improving system reliability. The paper also briefly describes several solar energy optimization challenges and issues. Lastly, some practical future approaches for establishing a reliable and efficient solar power system are proposed for developing the complex renewable energy-based hybrid system. • A thorough review of solar energy systems' generic optimization objectives. • Background and importance of solar energy and its various applications are reviewed. • Intelligent optimization approaches for solar energy systems, including their functions, constraints, and contributions. • Optimization methods, including combined hybrid algorithms, are presented. • Practical future approaches for developing a reliable and efficient solar power system are proposed. [ABSTRACT FROM AUTHOR]

Abstract: A hybrid power system is an emerging power generation technique which involves a combination of different energy systems, mostly renewables for optimal output configuration. In modern pursuit for renewable energy (RE) development, optimum conditions for the production and utilization of energy system are considered to be an indispensable feature for economic load dispatch. This is a rationalizing fact taking into consideration the rising price of energy for socio-economic development. Therefore, this paper reviews primary issues regarding the drivers and specific benefits of hybrid renewable energy systems (HRES). Moreover, this paper presents discussions on the various renewable energy sources which can be explored for HRES implementation. Finally, the framework unfolds a vivid review on factors to be considered for designing and implementation of HRES in general including simulation and optimization software packages for making such analyses. [Copyright &y& Elsevier]

Abstract: This paper presents a review of the current state of the art solutions to the problem of wind farm optimal design. The aim of this work is to present the problem by identifying the most relevant issues involved in the design of a wind farm, as well as to discuss the optimization techniques and wind farm models used in the published literature. An appropriate wind turbine layout is vital in order to obtain adequate performance in relation to the exploitation and operation of the plant during its lifespan. There are several factors that influence wind farm design, chief among them are the calculation of the overall energy yield by the wind farm and the initial investment. The energy produced depends on the local wind conditions and the interference caused by wind turbines nearby. The investment is mainly related to wind turbine acquisition, civil works and electrical infrastructure. However, these are not the only items that influence the design of a wind farm since economic indicators, environmental issues, local regulations, or the presence of wind farms should also be taken into account when deciding the design of the wind farm. Even in the case of the most simplified objective function (maximizing the annual energy produced) the optimization problem cannot be solved by classical optimization techniques. To cope with this problem, most authors have used meta-heuristics techniques which have proved to be efficient when searching for the optimal solution to this problem. The purpose of this paper is to review previous work by offering a clear outline of the latest advances, as well as to highlight the main aspects which need to be taken into account when tackling the wind farm design problem. In addition, in a conclusion of the review, future needs have been identified. [Copyright &y& Elsevier]

Abstract: A Compressed Air Energy Storage System is a means of storing energy which can then be used when the demand for energy increases. In this system, air is compressed in a cavern when power prices are low, and this air is used to run a natural gas-fired turbine to generate power when prices go up, with the aim of profiting from the price difference. This type of system can independently compress air, generate electricity, or do both. However, the prices of electricity and natural gas fluctuate, which directly impacts the amount of revenue that can be made, and this requires the calculating of estimates to optimize operation strategies and maximize profit. For these reasons, this is a crucial energy storage technology that requires economic analyses to justify investment decisions in power markets. In this paper, a mixed integer programming method is developed to schedule the operation of the system for forward market prices that are estimated using a markov-based probabilistic model. Then an algorithm that includes two separate modules in a simulation is employed to optimize the annual operation of the system. The paper presents a case study for Turkey as well as economic analyses based on probabilistic forward prices and the profits obtained from the optimization module. [Copyright &y& Elsevier]

The most important aspect of sustainability in manufacturing is the preservation of energy and natural resources. For modern production, optimized processes that minimize negative impacts on the environment are becoming increasingly important. This can be achieved by increasing energy efficiency through low, clean, and renewable energy consumption. There are many ways to produce less pollution, emissions, and waste in machining: by using more environmentally friendly cooling methods; by applying methods that reduce or eliminate the need for utilization of cooling lubrication; improving the energy efficiency of machining operations; determining the optimal cutting conditions that save resources by increasing machining productivity or reducing the metal removal rate (MRR); minimizing power consumption; and reducing carbon dioxide emissions. This article gives an idea of modern manufacturing with a focus on analyzing the current state of machining operations in terms of saving production resources and ensuring more environmentally friendly production using greener cooling methods of machining such as Dry, Conventional cooling systems, Minimum quantity of lubricant (MQL), Minimum quantity of cooling lubrication (MQCL), Nanofluids, Biodegradable Vegetable Oils, Cryogenic Lubrication, and High-Pressure Cooling (HPC). Finally, the important modern trends of providing resource-saving and environmentally efficient technologies in modern sustainable manufacturing are discussed in this paper. • Present review article deals with the sustainability and resource saving aspects during machining operations. • Different cooling conditions were presented. • Waste minimizing, recycling, pollution etc. were discussed during machining oeprations. [ABSTRACT FROM AUTHOR]

The finiteness of fossil fuels implies that future electric power systems may predominantly source energy from fuel-free renewable resources like wind and solar. Evidently, these power systems without fuel will be environmentally benign, sustainable, and subject to milder failure scenarios. Many of these advantages were projected decades ago with the definition of the soft energy path , which describes a future where all energy is provided by numerous small, simple, and diverse renewable sources. Here we provide a thorough investigation of power systems without any fuel-based generation from technical and economic standpoints. The paper is organized by timescale and covers issues like the irrelevance of unit commitment in networks without large, fuel-based generators, the dubiousness of nodal pricing without fuel costs, and the need for new system-level models and control methods for semiconductor-based energy-conversion interfaces. [ABSTRACT FROM AUTHOR]

In this paper MARKAL integrated energy system model is applied to explore the impacts and opportunities for low emissions energy system development in Macedonia, identifying CO 2 emission reduction policies and the cost of taking action. Two scenarios with different reduction target have been examined: higher ambition scenario where emissions are restricted to 10% above 1990 levels in 2021 and 2.5% in 2030, and moderate ambition scenario where emissions are restricted to 25% above 1990 levels in 2021 and 15% in 2030. In order to provide insights into the optimal timing of emission reductions, both of these cases have also been run under cumulative constraints, that is, rather than having the specified annual targets, there is a carbon “budget” set for 2015–2030 (44 Mt and 26 Mt for higher and moderate ambition cases, respectively), reflecting the same ambition as the above cases but providing flexibility to reduce emissions in the most cost-optimal way. The results show that most of the CO 2 reductions are in the power generation sector, which is not surprising as this tends to be the most carbon intensive sector. The higher ambition case is considerably more expensive than the reference case, with costs 1.9% higher, while the increase under the moderate ambition case is 1%. Under a cumulative constraint, the additional costs are reduced to 1.5% and 0.6% respectively, highlighting the importance of the timing of action. [ABSTRACT FROM AUTHOR]

Conventional electrical grid is transforming into smart grid—an evolutionary solution to satisfy rapidly emerging and vibrantly changing requirements of utilities and customers by intelligently leveraging telemetry concepts of instrumentation and control engineering in form of communication technology network infrastructure. The paper presents analogy of ‘smart grid’ to ‘industrial process’ and ‘communication technology infrastructure’ to ‘instrumentation telemetry’. Automated Metering Infrastructure (AMI), monitoring and automation of substations, power network monitoring, Home Automation Network (HAN), Demand Response (DR) and integration of solar PV—have been identified as ‘Critical Applications’ and Reliability, Scalability, Interoperability, Congestion, Energy Efficiency, Latency and Security – have been identified as ‘Critical Parameters’. Review of recent works has been presented for each segment. [ABSTRACT FROM AUTHOR]

Abstract: The issues of global warming and depletion of fossil fuels have paved opportunities to electric vehicle (EV). Moreover, the rapid development of power electronics technologies has even realized high energy-efficient vehicles. EV could be the alternative to decrease the global green house gases emission as the energy consumption in the world transportation is high. However, EV faces huge challenges in battery cost since one-third of the EV cost lies on battery. This paper reviews state-of-the-art of the energy sources, storage devices, power converters, low-level control energy management strategies and high supervisor control algorithms used in EV. The comparison on advantages and disadvantages of vehicle technology is highlighted. In addition, the standards and patterns of drive cycles for EV are also outlined. The advancement of power electronics and power processors has enabled sophisticated controls (low-level and high supervisory algorithms) to be implemented in EV to achieve optimum performance as well as the realization of fast-charging stations. The rapid growth of EV has led to the integration of alternative resources to the utility grid and hence smart grid control plays an important role in managing the demand. The awareness of environmental issue and fuel crisis has brought up the sales of EV worldwide. [Copyright &y& Elsevier]

Abstract: Nowadays, as set by the EU 20-20-20 targets, the reduction of primary energy use and greenhouse gas emissions in the energy sector can be attained by increasing the use of renewable sources and improving energy efficiency. Many national and international research programs are aiming at developing innovative technologies and new energy management strategies in order to reach the targets set out in the 20-20-20 directive. In this context, a primary role is played by the Distributed Generation (DG), which refers to the electrical and thermal generation located near to the place of use, exploiting available renewable sources. One of the best way to exploit the emerging potential of DG is to take a system approach which views generation and associated loads as a whole concept called “microgrid.” The sources can operate in parallel to the grid or can operate in island, providing utility power station services. Utilization of waste heat from the sources will increase total efficiency, making the polygeneration microgrid more financially attractive and “smart” from the energy consumption standpoint. The “smartness” is also in the management system, where control strategies aiming at the optimization of technical, economical and environmental issues are typically implemented. This paper deals with smart microgrids, addressing basically the following topics: (1) to review methods, models, tools, technologies and research challenges in the specific field; (2) to present the University of Genoa Smart Polygeneration Microgrid (SPM), built with the financial contribution of the Italian Ministry of Education, University and Research at the decentralized Savona Campus facilities. The SPM produces energy at low emissions for the University and operates as a test-bed facility for research, testing and development of smart grid components. [Copyright &y& Elsevier]

Abstract: With the 2009/28/EC Directive, the European Union has to guarantee three objectives by 2020: 20% reduction in greenhouse gases emissions, 20% share of renewable energy and 20% improvement of energy efficiency. New technologies and policies applied to power systems can positively influence the overall energy efficiency. The dimensions and complexity of the power system discourage the use of exact optimization techniques and heuristic methods are an effective option to find a rapid, robust and good solution. This paper presents a review of articles with applications of heuristic methods to the transmission and distribution system with the aim of improving energy efficiency. [Copyright &y& Elsevier]