To limit the global temperature change to no more than 2 °C by reducing global emissions, the European Union (EU) set up a goal of a 20% improvement on energy efficiency, a 20% cut of greenhouse gas emissions, and a 20% share of energy from renewable sources by 2020 (10% share of renewable energy (RE), specifically in the transport sector). By 2030, the goal is a 27% improvement in energy efficiency, a 40% cut of greenhouse gas emissions, and a 27% share of RE. However, the integration of RE in energy system faces multiple challenges. The geographical distribution of energy supply changes significantly the availability of the primary energy source (wind, solar, water) and is the determining factor, rather than where the consumers are. This leads to an increasing demand to match supply and demand for power. Especially intermittent RE like wind and solar power face the issue of energy production unrelated to demand (issue of excess energy production beyond demand and/or grid capacity) an... [more]

In this study, we used the thermoeconomic theory to evaluate the impact of residue cost formation on the cost of electricity generated from natural gas burned in a gas turbine that applied sequential combustion; we also analyzed the impact of the combustion process on the additional fuel consumption to compensate for a malfunction component. We used the Alstom GT24 gas turbine, which applied sequential combustion and generated 235 MW of power. Thermoeconomic analysis indicated that the exergy cost of power generation was 626.33 MW (30.42% corresponded to irreversibility costs, and 29.22% and 2.84% corresponded to the formation costs of physical and chemical residues, respectively). The exergoeconomic production cost of gas turbine was 10,098.71 USD/h, 34.76% from external resources and 65.24% from capital and operating costs. Thermoeconomic diagnosis revealed that a compressor deterioration (of 1-% drop in the isentropic efficiency) resulted in an additional fuel consumption of 4.05 MW... [more]

This paper made an attempt to put forward the comparative performance analysis of different energy storage devices (ESDs), such as redox flow batteries (RFBs), superconducting magnetic energy storage (SMES) device and ultra-capacitors (UCs), in the combined frequency and voltage stabilization of a multi-area interconnected power system (MAIPS). The investigative power system model comprises two areas, and each area consists of the power-generating sources of thermal, hydro and gas units. The intelligent control mechanism of fuzzy PID was used as a secondary controller optimized with a hybridized approach of the artificial electric field algorithm (HAEFA) subjected to the minimization of integral time absolute error (ITAE) objective function. However, the superiority of fuzzy PID in dampening the deviations of combined load frequency control (LFC) and automatic voltage regulator (AVR) responses was revealed upon comparison with conventional PI and PID. Further, the LFC-AVR combined anal... [more]

The greatest challenge in accelerating the realisation of a sustainable and competitive bioeconomy is to demonstrate that enshrining sustainability principles at the very heart of a production line can generate value and improve its overall system. Strategies for reducing emissions, pollutants, indirect land use change or soil depreciation are all perceived as costs or necessary inconveniences to comply with stringent, climate change-focused policy frameworks. System dynamics modelling and competitive priorities are tools that can accurately and intelligently expand on the cross-value chain approach, which integrates both technical and environmental performances, to address the issue of harmonising sustainability and technical operations as one overall dimension of performance. A stock-and-flow model is developed to map a full biofuel value chain and quantitatively and coherently integrate factors of emissions, carbon, land, production, and technology. As such, environmental and operat... [more]

Wind turbines have a wide range of applications as the main equipment for wind-power generation because of the rapid development of technology. It is very important to select a reasonable maintenance strategy to reduce the operation and maintenance costs of wind turbines. Traditional maintenance does not consider the environmental benefits. Thus, for the maintenance problems of wind turbines, an opportunistic maintenance strategy that considers structural correlations, random correlations, and carbon emissions is proposed. First, a Weibull distribution is used to describe the deterioration trend of wind turbine subsystems. The failure rates and reliability of wind turbines are described by the random correlations among all subsystems. Meanwhile, two improvement factors are introduced into the failure rate and carbon emission model to describe imperfect maintenance, including the working-age fallback factor and the failure rate increasing factor. Then, the total expected maintenance cos... [more]

Estimation of core temperature is one of the crucial functionalities of the lithium-ion Battery Management System (BMS) towards providing effective thermal management, fault detection and operational safety. It is impractical to measure the core temperature of each cell using physical sensors, while at the same time implementing a complex core temperature estimation strategy in onboard low-cost BMS is also challenging due to high computational cost and the cost of implementation. Typically, a temperature estimation scheme consists of a heat generation model and a heat transfer model. Several researchers have already proposed ranges of thermal models with different levels of accuracy and complexity. Broadly, there are first-order and second-order heat resistor−capacitor-based thermal models of lithium-ion batteries (LIBs) for core and surface temperature estimation. This paper deals with a detailed comparative study between these two models using extensive laboratory test data and simul... [more]

Vehicle exhaust emissions have seriously affected air quality and human health, and understanding the emission characteristics of vehicle pollutants can promote emission reductions. In this study, a chassis dynamometer was used to study the emission characteristics of the pollutants of two gasoline vehicles (Euro 5 and Euro 6) when using six kinds of fuels. The results show that the two tested vehicles had different engine performance under the same test conditions, which led to a significant difference in their emission characteristics. The fuel consumption and pollutant emission factors of the WLTC cycle were higher than those of the NEDC. The research octane number (RON) and ethanol content of fuels have significant effects on pollutant emissions. For the Euro 5 vehicle, CO and particle number (PN) emissions decreased under the WLTC cycle, and NOx emissions decreased with increasing RONs. For the Euro 6 vehicle, CO and NOx emissions decreased and PN emissions increased with increasi... [more]

This research examines the relationship between renewable energy consumption and electricity prices in six South American countries (Argentina, Bolivia, Colombia, Chile, Ecuador and Peru). The methodology used is a panel econometric model with annual data for the period 1990−2015. The results show that the consumption of renewable energies influences the price of electricity paid by households, although its influence is very moderate. On the other hand, it was observed that the consumption of renewable energies has no relationship with the energy prices of the industrial sector and the commercial and services sector. In the countries analyzed, an increase in GDP causes an increase in the price of energy in the industrial sector. With more CO2 emissions and a rise in the international price of oil, the annual average price of the industrial sector decreases.

Considering that more than half of the world’s population today lives in cities and consumes about 80% of the world’s energy and that there is a problem with drinking water supply, this paper presents a way to solve the problem of the sustainability of cities by enabling their complete independence from external sources of energy and drinking water. The proposed solution entails the use of Seawater Steam Engine (SSE) technology to supply cities with electricity, thermal energy and drinking water. The system would involve the seasonal storage of electricity and thermal energy, supported by geothermal heat pumps. The strategy of the distribution network would be based on the original concept of the “loop”. In cities that do not have enough space, SSE collectors would be placed above the lower parts of the city like “canopies”. The city of Zagreb (Croatia) was selected as a case study due to its size, climate and vulnerability to natural disasters. The results show that Zagreb could becom... [more]

This special issue was designed to draw attention to photovoltaic technology, which harnesses sunlight—the most promising renewable energy source—for our sustainable future [...]

Voltage regulation in distribution networks encounters a challenge of handling uncertainties caused by the high penetration of photovoltaics (PV). This research proposes an active exploration (AE) method based on reinforcement learning (RL) to respond to the uncertainties by regulating the voltage of a distribution network with battery energy storage systems (BESS). The proposed method integrates engineering knowledge to accelerate the training process of RL. The engineering knowledge is the chance-constrained optimization. We formulate the problem in a chance-constrained optimization with a linear load flow approximation. The optimization results are used to guide the action selection of the exploration for improving training efficiency and reducing the conserveness characteristic. The comparison of methods focuses on how BESSs are used, training efficiency, and robustness under varying uncertainties and BESS sizes. We implement the proposed algorithm, a chance-constrained optimizatio... [more]

DC-DC boost converters are necessary to extract power from solar panels. The output voltage from these panels is far lower than the utility voltage levels. One of the main functions of the boost converter is to provide a considerable step-up gain to interface the panel to the utility lines. There are several techniques used to boost the low panel voltage. Some of the issues faced by these topologies are a high duty ratio operation, complex design with multiple active switches and discontinuous input current that affects the power drawn from the panel. This paper presents a boost converter topology that combines the advantages of an interleaved structure, a voltage lift capacitor and a passive voltage multiplier network. A mathematical analysis of the proposed converter during its various modes of operation is presented. A 100 W prototype of the proposed converter is designed and tested. The prototype is controlled by a PIC16F18455 microcontroller. The converter is capable of achieving... [more]

The paper presents a mathematical model of a molten carbonate fuel cell with a catalyst in the anode channel. The modeled system is fueled by methane. The system includes a model of the steam reforming process occurring in the anode channel of the MCFC fuel cell and the model of the cell itself. A reduced order model was used to describe the operation of the molten carbonate fuel cell, whereas a kinetic model describes the methane steam reforming. The calculations of the reforming were done in Aspen HYSYS software. Four values of the steam-to-carbon ratio (2.0, 2.5, 3.0, and 3.5) were used to analyze the performance of the reforming process. In the first phase, the reaction kinetics model was based on data from the literature.

As an emerging unconventional energy resource, shale gas has great resource potential and developmental prospects. The effective evaluation of geological sweet spots (GSS), engineering sweet spots (ESS) and comprehensive sweet spots (CSS) is one of the main factors for a high-yield scale and economic production of shale gas. Sweet spot evaluation involves a comprehensive analysis based on multiple parameters. Conventional evaluation methods consider relatively simple or single factors. Although the main influencing factors are understood, the influence of different factors is as of yet unknown, and a comprehensive consideration may strongly affect the evaluation results. In this paper, the fuzzy mathematics method is introduced for shale gas sweet spot evaluation. With the help of fuzzy mathematics tools, such as membership function, the objective of comprehensive sweet spots evaluation based on multiple parameters is realized. Additionally, the reliability of the evaluation of sweet s... [more]

Hybrid and electric vehicle batteries deteriorate from use due to irreversible internal chemical and mechanical changes, resulting in decreased capacity and efficiency of the energy storage system. This article investigates the modeling and control of a lithium-ion battery and ultracapacitor hybrid energy storage system for an electric vehicle for improved battery lifespan and energy consumption. By developing a control-oriented aging model for the energy storage components and integrating the aging models into an energy management system, the trade-off between battery degradation and energy consumption can be minimized. This article produces an optimal aging-aware energy management strategy that controls both battery and ultracapacitor aging and compares these results to strategies that control only battery aging, strategies that control battery aging factors but not aging itself, and non-optimal benchmark strategies. A case study on an electric bus with variously-sized hybrid energy... [more]

The research reported in this paper involves the development and refinement of methods applicable to the measurement and analysis of infrasound signals generated by the operation of wind turbines. In particular, the presentation focuses on the use of a new system that is applied for simultaneous recording of acoustic signals in the low-frequency range emitted by wind farms in three independent and identical measurement setups. A comparative analysis of the proposed new system was made with the Brüel & Kjaer measurement, a commonly used methodology, which meets the requirements of the IEC 61400-11 standard. The paper focuses on the results of frequency and time-frequency analysis of infrasound signals recorded throughout the operation of a wind turbine with a rated capacity of 2 MW. The use of a correlated system with three simultaneous measurement systems can be a new and alternative measurement method that will eliminate the drawbacks of previous approaches.

Clearly and accurately communicating the economic, environmental, and social benefits of solar PV prosumerism poses significant challenges. Previous research shows that government policies and public engagement campaigns can positively impact solar prosumerism; however, little is known about the quality and accuracy of information exchanged between rooftop solar installers and potential prosumers. This study addresses part of this gap with a mixed methods approach. First, a multimodal discourse analysis of installation proposals from seven home solar installers in Madrid shows accurate and reasonable financial benefits alongside incongruent social and environmental benefits. Second, the calculated efficiency of the seven proposed solar installations is compared with the efficiency of four different PVSC solar arrays using actual load and generation profiles. The results show that (i) the high variability of actual household demand on the minute-by- minute level significantly decreases... [more]

With every passing second, we witness the effect of the global environmental impact of fossil fuels and carbon emissions, to which nations across the globe respond by coming up with ambitious goals to become carbon-free and energy-efficient. At the same time, electric vehicles (EVs) are developed as a possible solution to reach this ambitious goal of making a cleaner environment and facilitating smarter transportation modes. This excellent idea of shifting towards an entirely EV-based mobility industry and economy results in a range of issues that need to be addressed. The issues range from ramping up the electricity generation for the projected increase in consumption to developing an infrastructure that is large enough to support the higher demand for electricity that arises due to the market penetration of EVs. Vehicle to grid (V2G) is a concept that is largely in a testing phase in the current scenario. However, it appears to offer a solution to the issues created by a mobility sec... [more]

Flexibility is crucial to enable the penetration of high shares of renewables in the power system while ensuring the security and affordability of the electricity dispatch. In this regard, heat−electricity sector coupling technologies are considered a promising solution for the integration of flexible devices such as thermal storage units and heat pumps. The deployment of these devices would also enable the decarbonization of the heating sector, responsible for around half of the energy consumption in the EU, of which 75% is currently supplied by fossil fuels. This paper investigates in which measure the diffusion of district heating (DH) coupled with thermal energy storage (TES) units can contribute to the overall system flexibility and to the provision of operating reserves for energy systems with high renewable penetration. The deployment of two different DH supply technologies, namely combined heat and power units (CHP) and large-scale heat pumps (P2HT), is modeled and compared in... [more]

Faults and unintended conditions in grid-connected photovoltaic systems often cause a change of the residual current. This article describes a novel machine learning based approach to detecting anomalies in the residual current of a photovoltaic system. It can be used to detect faults or critical states at an early stage and extends conventional threshold-based detection methods. For this study, a power-hardware-in-the-loop approach was carried out, in which typical faults have been injected under ideal and realistic operating conditions. The investigation shows that faults in a photovoltaic converter system cause a unique behaviour of the residual current and fault patterns can be detected and identified by using pattern recognition and variational autoencoder machine learning algorithms. In this context, it was found that the residual current is not only affected by malfunctions of the system, but also by volatile external influences. One of the main challenges here is to separate th... [more]

Energy consumption in buildings is expected to increase by 40% over the next 20 years. Electricity remains the largest source of energy used by buildings, and the demand for it is growing. Building energy improvement strategies is needed to mitigate the impact of growing energy demand. Introducing a smart energy management system in buildings is an ambitious yet increasingly achievable goal that is gaining momentum across geographic regions and corporate markets in the world due to its potential in saving energy costs consumed by the buildings. This paper presents a Smart Building Energy Management system (SBEMS), which is connected to a bidirectional power network. The smart building has both thermal and electrical power loops. Renewable energy from wind and photo-voltaic, battery storage system, auxiliary boiler, a fuel cell-based combined heat and power system, heat sharing from neighboring buildings, and heat storage tank are among the main components of the smart building. A const... [more]

The frequency of power systems is very sensitive to load variations. Additionally, with the increased penetration of renewable energy sources in electrical grids, stabilizing the system frequency becomes more challenging. Therefore, Load Frequency Control (LFC) is used to keep the frequency within its acceptable limits. In this paper, an adaptive controller is proposed to enhance the system performance under load variations. Moreover, the proposed controller overcomes the disturbances resulting from the natural operation of the renewable energy sources such as Wave Energy Conversion System (WECS) and Photovoltaic (PV) system. The superiority of the proposed controller compared to the classical LFC schemes is that it has auto tuned parameters. The validation of the proposed controller is carried out through four case studies. The first case study is dedicated to a two-area LFC system under load variations. The WECS is considered as a disturbance for the second case study. Moreover, to d... [more]

Monitoring the variation of the loading blades is fundamental due to its importance in the behavior of the wind turbine system. Blade performance can be affected by different loads that alter energy conversion efficiency and cause potential safety hazards. An example of this is icing on the blades. Therefore, the main objective of this work is to propose a proportional digital controller capable of detecting load variations in wind turbine blades together with a fault detection method. An experimental platform is then built to experimentally validate the main contribution of the article. This platform employs an automotive throttle device as a blade system emulator of a wind turbine pitch system. In addition, a statistical fault detection algorithm is established based on the point change methodology. Experimental data support our approach.

Advanced control system design for large wind turbines is becoming increasingly complex, and high-level optimization techniques are receiving particular attention as an instrument to fulfil this significant degree of design requirements. Multiobjective optimal (MOO) control, in particular, is today a popular methodology for achieving a control system that conciliates multiple design objectives that may typically be incompatible. Multiobjective optimization was a matter of theoretical study for a long time, particularly in the areas of game theory and operations research. Nevertheless, the discipline experienced remarkable progress and multiple advances over the last two decades. Thus, many high-complexity optimization algorithms are currently accessible to address current control problems in systems engineering. On the other hand, utilizing such methods is not straightforward and requires a long period of trying and searching for, among other aspects, start parameters, adequate objecti... [more]

Storing CO2 in geological formations is an important component of reducing greenhouse gases emissions. The Carbon Capture and Storage (CCS) industry is now in its establishing phase, and if successful, massive storage volumes would be needed. It will hence be important to utilize each storage site to its maximum, without challenging the formation integrity. For different reasons, supply of CO2 to the injection sites may be periodical or unstable, often considered as a risk element reducing the overall efficiency and economics of CCS projects. In this paper we present outcomes of investigations focusing on a variety of positive aspects of periodic CO2 injection, including pressure management and storage capacity, also highlighting reservoir monitoring opportunities. A feasibility study of periodic injection into an infinite saline aquifer using a mechanistic reservoir model has indicated significant improvement in storage capacity compared to continuous injection. The reservoir pressure... [more]