The dark fermentation of lignocellulose hydrolysates is a promising process for the production of hydrogen from renewable sources. Nevertheless, hydrogen yields are often lower than those obtained from other carbohydrate sources due to the presence of microbial growth inhibitors in lignocellulose hydrolysates. In this study, a microbial consortium for the production of hydrogen by dark fermentation has been obtained from a wild methanogenic sludge by means of thermal treatments. The consortium has been initially acclimated to a glucose-based medium and then used as inoculum for the fermentation of Arundo donax hydrolysates. Hydrogen yields obtained from fermentation of A. donax hydrolysates were lower than those obtained from glucose fermentation using the same inoculum (0.30 ± 0.05 versus 1.11 ± 0.06 mol of H2 per mol of glucose equivalents). The hydrogen-producing bacteria belonged mainly to the Enterobacteriaceae family in cultures growing on glucose and to Clostridium in those grow... [more]

Bottom-up energy system models have been used extensively to analyse future energy scenarios, addressing a wide variety of policy questions. This paper focuses on energy efficiency, a key energy, climate, and economic policy area where several examples of energy system model applications can be found in the literature. This paper analyses how different studies implement energy efficiency scenarios in energy system models and explains how the approach taken can affect the results significantly, potentially affecting policy decisions. This analysis contributes to understanding how this type of modelling framework considers energy efficiency policy issues and the extent of insight provided, or not, on different dimensions. With the aim of identifying ‘best practice’ in using energy system models to inform effective analysis of energy efficiency policy, the UK TIMES energy system model is used to implement five different energy efficiency scenarios for residential heating following differe... [more]

Dual fuel combustion leverages a high-reactivity fuel (HRF) to ignite a premixed low reactivity fuel (LRF)−air mixture to achieve high efficiencies and low engine-out emissions. The difference in the relative amounts of these fuels and in-cylinder fuel reactivity stratification profoundly impacts dual fuel combustion. The effect of increasing LRF energy substitution on dual fuel combustion at various fixed HRF (diesel) quantities was experimentally studied for two different LRFs (natural gas and propane) on a heavy-duty single cylinder engine at a constant intake pressure of 1.5 bar and injection pressure of 500 bar. Further, this effect was studied for three different HRF start of injection (SOI) timings of 310 CAD (50° BTDC), 330 CAD (30° BTDC), and 350 CAD (10° BTDC). For 310 CAD SOI, increasing the LRF substitution at a fixed HRF resulted in higher loads, peak cylinder pressures, and peak apparent heat release rates (AHRR). The onset of low temperature heat release (LTHR) was advan... [more]

The article aims to systematize the state of knowledge of and research on the inclusion of ESG (Environmental, Social, and Governance) risk in companies’ business models, with a special stress on energy sector companies. Many publications address incorporating ESG, but only some deal with it from the perspective of business models. This paper fills that gap. The methods of incorporating ESG risk into a sustainable business model, identified on the basis of the literature review, were verified based on the examples of three companies from the energy industry. A two-stage review of publications from the WoS and Scopus databases was carried out, considering a more comprehensive (sustainability) and a narrower (ESG risk) range of keywords, and the period from 2000 to 2022. The result showed that SMEs and large enterprises consider ESG risk in their risk management systems (ERMs), while small enterprises and start-ups do not. In Europe, Asia, and Australia, it is common to include ESG risk... [more]

Dealing with multi-objective problems has several interesting benefits, one of which is that it supplies the decision-maker with complete information regarding the Pareto front, as well as a clear overview of the various trade-offs that are involved in the problem. The selection of such a representative set is, in and of itself, a multi-objective problem that must take into consideration the number of choices to show the uniformity of the representation and/or the coverage of the representation in order to ensure the quality of the solution. In this study, day-ahead scheduling has been transformed into a multi-objective optimization problem due to the inclusion of objectives, such as the operating cost of multi-energy multi-microgrids (MMGs) and the profit of the Distribution Company (DISCO). The purpose of the proposed system is to determine the best day-ahead operation of a combined heat and power (CHP) unit, gas boiler, energy storage, and demand response program, as well as the tra... [more]

To solve the problem of evenly mixing flocculant and sewage, a new type of two-chamber mechanical pipe mixer was numerically calculated and its working principle was studied by means of the internal flow field. The single factor numerical simulation and analysis of some of the structural parameters in the mixer were carried out to determine the influence of different parameters on the results. Latin hypercube sampling was used to design 100 sets of test tables for the four variables of the branch pipe diameter, sewage flow rate, the installation height of the impeller, and the angle of the deflector. The results were optimized using the SVR-DE algorithm. After optimization, the variation coefficient of export flocculant mixing uniformity was 16.02%, which was increased by 74.94% compared with the initial 63.921%. The power consumption of the impeller was reduced by 8.30%. The concentration curves of the flocculant at different positions of the outlet tube could quickly converge to the... [more]

Electricity load prediction is an essential tool for power system planning, operation and management. The critical information it provides can be used by energy providers to maximise power system operation efficiency and minimise system operation costs. Long Short-Term Memory (LSTM) and Support Vector Machine (SVM) are two suitable methods that have been successfully used for analysing time series problems. In this paper, the two algorithms are explored further for load prediction; two load prediction algorithms are developed and verified by using the half-hourly load data from the University of Warwick campus energy centre with four different prediction time horizons. The novelty lies in comparing and analysing the prediction accuracy of two intelligent algorithms with multiple time scales and in exploring better scenarios for their prediction applications. High-resolution load forecasting over a long range of time is also conducted in this paper. The MAPE values for the LSTM are 2.50... [more]

At present, a worldwide paradigm shift has become apparent, with more and more consumers consuming the energy generated by renewable energy sources (RES) systems, such as wind or photovoltaic (PV) energy, sometimes benefiting from appropriate incentives by individual governments. Consequently, it is necessary to carry out technical−economic assessments to understand the evolution of the viability of RES investments. Within the framework of an intelligent network control environment, the smart grid (SG) concept is associated with this model, and is an important tool in the management of energy distribution networks. This article aims to make a further contribution to this issue by analyzing the economic feasibility of investing in residential consumers, considering different RES configurations. Scenarios covered in this study include: “inject all on the low voltage network/consume all on the low voltage network”, self-consumption, net-metering, and storage systems. The economic study re... [more]

China and Russia have different interests in the Arctic but are forced to look for possible ways of cooperation in energy projects in the current external conditions. This changes the priorities of both countries and, accordingly, transforms the risks. Objectives of the research: to build an algorithm for identifying anthropogenic environmental risks in the context of two major players economic activities in the Arctic region: the Russian Federation and China. In the paper, we formulated an algorithm of environmental risk identification. We identified environmental hazards from the main parameter—the type of economic activity for the extraction of energy resources, premises, and factors for the occurrence of environmental hazards and compiled criteria for risk selection. Methods used: complex analysis (mixed method research): empirical and comparative methods, methods of expert assessments, the method of inductive statistics (inferential statistics) to compare the perception of risk at... [more]

Pig farming in mechanically ventilated barns requires much electricity for ventilation or exhaust air purification. Furthermore, thermal energy is needed to fulfill the animals’ temperature requirements, especially in piglet rearing. Electrical and thermal energy input leads to CO2 emissions and operating costs. Up to 90% of heat losses are due to the exhausted air. Heat exchangers can recover thermal energy from the warm exhaust air and transfer it to the cold fresh air. This study aimed to investigate energy consumption, efficiency, CO2 emissions, and energy costs when using heat exchangers in a German piglet rearing barn under practical conditions in combination with exhaust air purification. The following parameters were obtained for a two-year period: air temperatures, air flow rates, and electricity and liquefied natural gas consumption; the latter were used to calculate CO2 emissions and energy costs. In total, 576,042 kWhel,th and 616,893 kWhel,th (years 1 and 2) of energy were... [more]

In electrical power engineering, elements such as reliability analysis, modeling, and optimization for complex systems are of the utmost importance. Although there exist myriad studies regarding reliability optimization with conventional methods, researchers are still seeking to find more efficient and accurate methods to address the issue of the redundancy allocation problem. To that effect, an ideal power energy management approach is put forward for the operation of a hybrid microgrid system with different kinds of productions. In the present study, we suggest three algorithms in order to optimize the series-parallel power energy system: the Firefly (FA), Bat (BA), and Interior Search (ISA) algorithms. Moreover, the reliability estimate of the system is solved with the Ushakov algorithm (UMGF). The components may completely fail, which decreases their performance rate. Furthermore, the optimization results are achieved using objective functions that include the total cost of the sys... [more]

The hydrothermal behavior in a helical double-tube heat exchanger is numerically estimated. A new type of swirl generator with two sections, including; outer curved blades and a semi-conical section with two holes in the inner section, is employed. Two geometrical factors, containing the length (L1) and the position of the swirl generator (S), are used for investigation. The calculations were performed by a commercial FVM code, ANSYS FLUENT 18.2. The numerical outcomes show that a shorter length of the swirl generator leads to a better hydrothermal behavior. Accordingly, the model with L1 = 100 mm at m˙ = 0.008 kg/s achieves the maximum thermal performance by about 17.65, 53.85, and 100% enhancement compared to the models L1 = 200, 300 mm, and without swirl generator. Among the different studied positions of the swirl generator, the maximum heat transfer coefficient and average Nusselt number in entire mass flow rates belong to the case with position S = 0.3π mm. Moreover, the thermal... [more]

As a result of growing interest in the thermal treatment of sewage sludge with methods such as combustion, gasification or pyrolysis, and also in processes that aim to recover precious components such as phosphorus from this waste, a growing demand has been observed for Computational Fluid Dynamics (CFD) models that provide solutions rapidly and accurately for efficient application in research and development. This study was carried out to develop a computationally inexpensive modelling approach for the combustion of pulverized sewage sludge in entrained flow furnaces. Sewage sludge is a very volatile-rich fuel. Therefore, the Steady Diffusion Flamelet model (SFM), in combination with a validated skeletal reaction mechanism, was applied to consider the pulverized firing of sewage sludge. It was possible to represent the complex composition of volatiles emitted from the sludge particles by releasing surrogate fuels. In addition, the influence of limestone additive (calcination reaction)... [more]

The increasing demand for flexibility in hydropower systems requires pumped storage power plants to change operating modes and compensate reactive power more frequently. In this work, we demonstrate the potential of applying reinforcement learning (RL) to control the blow-out process of a hydraulic machine during pump start-up and when operating in synchronous condenser mode. Even though RL is a promising method that is currently getting much attention, safety concerns are stalling research on RL for the control of energy systems. Therefore, we present a concept that enables process control with RL through the use of a digital twin platform. This enables the safe and effective transfer of the algorithm’s learning strategy from a virtual test environment to the physical asset. The successful implementation of RL in a test environment is presented and an outlook on future research on the transfer to a model test rig is given.

The extent of fracture development is associated with the degree of enrichment of a natural gas reservoir and its productivity. Based on numerical simulation results of the paleotectonic stress field, a set of evaluation methods for determining the degree of development of reservoir tectonic fractures were established using rock rupture criteria. Taking the fourth member of the Leikoupo Formation in the Pengzhou area of western Sichuan as an example, a finite element (FE) method was employed to simulate the paleo-tectonic stress field during the period of fracture development, and the degree of tectonic fracture development was further evaluated using the above methods. The results indicated that effective fractures were created in the Himalayan period. In this time, mainly NE−NEE and nearly E−W strike tectonic fractures were developed in the target layer. The fractures were mainly low-angle and oblique fractures, while the high-angle fractures were less developed. According to the int... [more]

This paper presents the study and detailed analysis of converter losses at different stages together with the series-series (S-S) compensating coils in wireless power transfer (WPT) systems, via two distinct approaches to control the power converters. The two approaches towards wireless DC−DC power flow control are termed as the Single Active High-Frequency Wireless Power Transfer (SAHFWPT) system and the Dual Active High-Frequency Wireless Power Transfer (DAHFWPT) system. The operation of converters in SAHFWPT and DAHFWPT are controlled by the extended phase shift (EPS) and dual phase shift method respectively. The general schematic of the SAHFWPT system consists of an active bridge and a passive bridge, while the schematic of the DAHFWPT system consists of both active bridges. The efficiency evolutions of ideal SAHFWPT and DAHFWPT are far away from the real ones. Moreover, this article analyzes the operation and losses of the uni-directional power flow of the WPT system, i.e., from t... [more]

The global energy and environmental crisis promotes the development of electric vehicles (EVs), and the rational planning of EV fast charging stations is an important influencing factor for their development. In this paper, for the EV fast charging station capacity planning problem, a joint-optimization model for optimal planning of EV fast charging stations and the economic operation of a distribution network is constructed, considering the impact of user preference selection and EV access on the regional distribution network. To address the problems of low efficiency and local convergence found in traditional heuristic optimization algorithms, an improved krill swarm optimization algorithm (CKHA) that introduces chaotic optimization parameters to make the initial population as uniformly distributed as possible is proposed to find the optimal planning scheme for EV fast charging stations. The case results show that the optimal planning model and its solution method are effective.

Energy consumption is increasing rapidly; hence, the energy demand cannot be fulfilled using traditional power resources only. Power systems based on renewable energy, including solar and wind, are effective and friendly for the environment. Islanded hybrid microgrid systems (IHMS) are relatively new in this industry and combine two or more sustainable sources, such as wind turbines, solar photovoltaic (PV), and other renewable alternatives, ocean, wave, and geothermal energy, etc. While sustainable, long-lasting power sources are the best choice to satisfy the growing energy demands, they are still not yet ready to be used on a large scale due to their stochastic characteristics. Furthermore, integrating these sources into the existing energy system can cause high technical difficulties, due to the stochastic nature of solar and wind in the conventional grid system and common stand-alone framework. A review of research and applications of the effective hybridization of renewable energ... [more]

The economic operation of an electric vehicle (EV) parking lot under different cases are explored in the paper. The parking lot is equipped with EV charging stations with a vehicle-to-grid (V2G) function, renewable energy sources (RESs), and energy storage system (ESS). An optimisation problem is formulated to maximise the profit of the parking lot from EV charging and feed-in energy to the grid under various charging modes while considering the uncertain factors, ESS degradation, and diverse EV parking conditions. The electricity market price, solar radiation and wind speed are considered as uncertain factors, and the scenred toolbox of MATLAB is used to generate scenarios. Based on the parking time of different EVs, the model classifies the EVs entering the charging station and dynamically determines the charging price according to their charging demand through a linear price-demand relationship. The efficacy of the proposed model is verified by the comparison with two other models u... [more]

This paper mainly studies the optimal control problem of turbine-based combined cycle (TBCC) engines in the mode-transition stage. Based on the TBCC scheme proposed by Xiamen University, an aerothermodynamic model is established as a verification model for the validity of control laws. To reduce the complexity of control design, a control-oriented linear parameter-varying (LPV) model with Mach number as a scheduling variable is established under a given flight path. The design of mode-transition points and distribution of air-flow-rate among paths during the mode-transition process are transformed into linear quadratic (LQ) optimal control problems for an LPV system under the initial and terminal as well as process constraints. By optimizing the opening of the splitters of the inlet and the fuel flow in each channel, the optimal mode-transition points are found to achieve coordinated control and complete the high-precision thrust tracking during the mode-transition process.

Gas and downhole water sink-assisted gravity drainage (GDWS-AGD) is a new process of enhanced oil recovery (EOR) in oil reservoirs underlain by large bottom aquifers. The process is capital intensive as it requires the construction of dual-completed wells for oil production and water drainage and additional multiple vertical gas-injection wells. The costs could be substantially reduced by eliminating the gas-injection wells and using triple-completed multi-functional wells. These wells are dubbed triple-completion-GDWS-AGD (TC-GDWS-AGD). In this work, we design and optimize the TC-GDWS-AGD oil recovery process in a fictitious oil reservoir (Punq-S3) that emulates a real North Sea oil field. The design aims at maximum oil recovery using a minimum number of triple-completed wells with a gas-injection completion in the vertical section of the well, and two horizontal well sections—the upper section for producing oil (from above the oil/water contact) and the lower section for draining wat... [more]

The synchronous generators (SGs) supplying non-linear loads have harmonically distorted terminal voltages. Hence, these distorted terminal voltages adversely affect the performance parameters of the supplied loads such as the power factor, current distortion, losses, and efficiency. To mitigate the harmonic voltages and currents, passive and active filters are generally employed. However, passive filters cause resonance problems, while active filters can cause high costs. On the other hand, in several recent studies to reduce the SG’s terminal voltage harmonic distortion, which depends on the constructional design under the no-loading condition, the conventional DC excitation current has been modulated with AC harmonic components. These field current modulation methods have high computational complexity, and require extra hardware for their implementation. In the present paper, firstly, for the reduction of the terminal voltage harmonic distortion of the SG under non-linear loading con... [more]

The application of additive manufacturing in the field of aviation hydraulics greatly improves the design freedom of hydraulic valve internal flow channels. Pressure loss in hydraulic valve internal flow channels is a primary factor that designers need to consider, and the rapid prediction of pressure loss is very helpful for flow channel design. At present, most studies only focus on how much the pressure loss in an additive manufacturing (AM) hydraulic channel is reduced compared with an original hydraulic channel, and a mathematical model of pressure loss in an AM curved channel is still lacking. In this paper, the pressure loss in a curved flow channel was firstly studied, and the main parameters affecting the pressure loss were determined using the dimensionless analysis method. Using computational fluid dynamics simulation, the relationships between the flow channel diameter, the flow channel length, the flow channel curvature radius, the fluid velocity and pressure loss were stu... [more]

In grid-connected operations, a microgrid can solve the problem of surplus power through regeneration; however, in the case of standalone operations, the only method to solve the surplus power problem is charging the energy storage system (ESS). However, because there is a limit to the capacity that can be charged in an ESS, a separate energy management strategy (EMS) is required for stable microgrid operation. This paper proposes an EMS for a hybrid AC/DC microgrid based on an artificial neural network (ANN). The ANN is composed of a two-step process that operates the microgrid by outputting the operation mode and charging and discharging the ESS. The microgrid consists of an interlinking converter to link with the AC distributed system, a photovoltaic converter, a wind turbine converter, and an ESS. The control method of each converter was determined according to the mode selection of the ANN. The proposed ANN-based EMS was verified using a laboratory-scale hybrid AC/DC microgrid. Th... [more]

The use of fossil-fueled power stations to generate electricity has had a damaging effect over the years, necessitating the need for alternative energy sources. Microgrids consisting of renewable energy source concepts have gained a lot of consideration in recent years as an alternative because they use advances in information and communication technology (ICT) to increase the quality and efficiency of services and distributed energy resources (DERs), which are environmentally friendly. Nevertheless, microgrids are constrained by the outbreaks of faults, which have an impact on their performance and necessitate dynamic energy management and optimization strategies. The application of artificial intelligence (AI) is gaining momentum as a vital key at this point. This study focuses on a comprehensive review of applications of artificial intelligence strategies on hybrid renewable microgrids for optimization, power quality enhancement, and analyses of fault outbreaks in microgrids. The us... [more]