In the face of the new reform of China’s “unified electricity market”, the frequency regulation ancillary service market in each region of China is still divided between using the MCP and PAB pricing mechanisms. The purpose of this paper is to explore the different impact the laws of the above two pricing mechanisms have on the frequency regulation market and to provide relevant suggestions for this electricity market reform. This paper simulates the competitive activities of the frequency regulation market based on the multi-agent simulation model, conducts a comparative experiment by changing the pricing mechanism to a single variable based on the rules of the Sichuan frequency regulation market in China, and concludes that MCP can make the market fast and stable, and that its market settlement price is low, which is suitable for the “unified electricity market”. Although PAB makes the market settlement price high, it can ensure the retention of high-performance units in the market,... [more]

Recent years have seen increasing attention to TCES technology owing to its potentially high energy density and suitability for long-duration storage with negligible loss, and it benefits the deployment of future net-zero energy systems. This paper provides a review of salt hydrate adsorption material-based TCES for space heating applications at ~150 °C. The incorporation of salt hydrates into a porous matrix to form composite materials provides the best avenue to overcome some challenges such as mass transport limitation and lower thermal conductivity. Therefore, a systematic classification of the host matrix is given, and the most promising host matrix, MIL-101(Cr)(MOFs), which is especially suitable for loading hygroscopic salt, is screened from the perspective of hydrothermal stability, mechanical strength, and water uptake. Higher salt content clogs pores and, conversely, reduces adsorption performance; thus, a balance between salt content and adsorption/desorption performance sho... [more]

Engine efficiency and emissions depend on the fuel atomization and dispersion. The fuel atomization and dispersion depend heavily on the ambient pressure and temperature. In this work, to study Diesel sprays in engine conditions, an electrically heated, constant-volume, pressurized vessel was designed and manufactured. The controlling electronics and software were developed and tested to ensure safe and precise operation. A commercial Bosch six-hole automotive Diesel injector was used. The spray spatial and temporal development were studied. In the literature, spray liquid length and cone angle are extensively used to quantify fuel dispersion. In this work, these parameters were quantified using a high-speed shadowgraph technique. Models were derived to describe the temporal evolution of the liquid core. Such models can be used to predict the Diesel spray behaviour and the engine performance.

The main task of a wastewater treatment plant (WWTP) is to reduce pollutants that adversely affect the receiving environment in which the effluent is discharged. The operation of a WWTP is a complex task due to the number of different processes that take place in its process facilities. In order to maintain the high efficiency of a WWTP, it is necessary to control the quality of the effluent at the outlet and monitor the processes taking place there. The main objective of the research presented in this study was to evaluate the possibility of using unmanned aerial vehicle (UAV) technology and multispectral images acquired with a Micasense Red-Edge MX camera to analyse the performance of an activated sludge bioreactor using the example of a municipal WWTP in Poland. Remote sensing analyses were carried out to check the relationships between the calculated spectral indices and the quality parameters in the bioreactor. The spectral indices assessed were the normalised difference vegetatio... [more]

The presence of the DC components in the grid voltage adversely affects the performance of the synchronization unit, causing oscillatory and offset errors in the estimated grid information. Several approaches were proposed to address the DC offset problem by incorporating an additional filtering stage to the synchronous reference frame phase-locked loop (SRF-PLL). Removing the DC offset using the modified delayed signal cancelation (MDSC) operator in the inner loop of the SRF-PLL shows a good DC offset elimination with a fast-dynamic response. However, neither a straightforward selection procedure for the MDSC parameters nor a general estimation technique for the grid information is provided. Hence, a generalization for the MDSC is proposed in this paper based on general mathematical expressions to cancel out the DC offset, while meanwhile estimating the grid parameters precisely and rapidly against any delay factor selection. Finally, comprehensive simulation and experimental results... [more]

Future vehicle powertrain systems with internal combustion engines must achieve higher efficiencies and further reduced pollutant emissions. This will require the application of new advanced technologies. Against this background, this paper presents a holistic approach to reduce temporally the wall heat losses, and hydrocarbon and carbon monoxide emissions with thermal coatings on the combustion chamber walls. For this purpose, an yttria-stabilized zirconia (YSZ) coating is applied and evaluated by different methods. The thin layer in combination with the low thermal effusivity of the material allows the wall temperature to follow the gas temperature and perform a so-called thermal swing. The interaction between an uncoated and a YSZ-coated wall with the flame front as well as partially burned gas was investigated. First, in terms of the coating’s potential to reduce the flame quenching distance using an optical method in a constant volume combustion chamber. Second, regarding its infl... [more]

Non-uniform temperature distributions in air-conditioned areas can reduce the energy efficiency of air conditioners and cause uncomfortable thermal sensations for occupants. Furthermore, it is impractical to use physical sensors to measure the local temperature at every position. This study developed a soft-sensing model that integrates the fundamentals of thermodynamics and transport phenomena to predict the temperature at the target position in space. Water experiments were conducted to simulate indoor conditions in an air-conditioning cooling mode. The transient temperatures of various positions were measured for model training and validation. The velocity vectors of water flow were acquired using the particle image velocimetry method. Correlation analysis of various positions was conducted to select the input variable. The soft-sensing model was developed using the multiple linear regression method. The model for the top layer was modified by the correction of dead time. The experi... [more]

The article presents the conceptual features of energy security management under a radically changed context, increasing crisis phenomena, and threats of various natures. The authors substantiate the claim that energy security is a complex category, which expresses the ability of the fuel and energy complex of the region to supply the required amount and range of energy resources to the domestic market at stable and reasonable prices; to promptly mitigate unexpected fluctuations in demand for fuel and energy resources; and to ensure uninterrupted energy supply and energy carrier parameters in real time. Based on an analysis of scientific publications and practical energy security models, the authors developed theoretical provisions, methodological principles, and management tools for energy security that meet modern requirements. In particular, the authors developed the terminological apparatus and identified the types and forms of modern energy threats and risks. The authors analyzed... [more]

In this paper, the optimal design of a hybrid energy system (HES), consisting of photovoltaic technology integrated with fuel cells (HPV/FC) and relying on hydrogen storage, is performed to meet the annual demand of a residential complex to find the minimum total net present cost (TNPC), while observing the reliability constraint as the energy-not-supplied probability (ENSP) and considering real meteorological data of the Kuala Lumpur city in Malaysia. The decision variables include the size of system components, which are optimally determined by an improved artificial ecosystem-based optimization algorithm (IAEO). The conventional AEO is improved using the dynamic lens-imaging learning strategy (DLILS) to prevent premature convergence. The results demonstrated that the decrease (increase) of the reliability constraint leads to an increase (decrease) in the TNPC, as well as the cost of electricity (COE). For a maximum reliability constraint of 5%, the results show that the TNPC and COE... [more]

Shale gas reservoirs have extremely low porosity and permeability, making them challenging to exploit. The best method for increasing recovery in shale gas reservoirs is horizontal well fracturing technology. Hence, fracturing parameter optimization is necessary to enhance shale gas horizontal fracturing well production. Traditional optimization methods, however, cannot meet the requirements for overall optimization of fracturing parameters. As for intelligent optimization algorithms, most have excellent global search capability but incur high computation costs, which limits their usefulness in real-world engineering applications. Thus, a modified genetic algorithm combined based on the Spearman correlation coefficient (SGA) is proposed to achieve the rapid optimization of fracturing parameters. SGA determines the crossover and mutation rates by calculating the Spearman correlation coefficient instead of randomly determining the rates like GA does, so that it could quickly converge to... [more]

The problem of global warming and climate change has attracted global attention, and reducing the concentration of CO2 in the atmosphere is an important step towards solving the problem. This paper mainly introduces the current development status, research hotspots, challenges and some emerging technologies of carbon capture, utilization and storage (CCUS). Among CO2 capture technologies, solvent absorption technology is currently the most mature and widely used technology, among which ionic liquid technology has great application prospects because its molecular structure can be designed and different functional groups can be connected. The surface functionalization of metal−organic frameworks in the adsorption method endows them with excellent CO2 adsorption capacity. In CO2 transportation, temperature and pressure must be considered in pipeline transportation, because they will affect the phase state of CO2 transportation. The impact of impurities on CO2 pipeline transportation is a... [more]

Gas hydrates are promising components for a wide range of industries and the national economy. This paper outlines the gas hydrate application areas with the greatest potential. Gas hydrates of methane, ethane, propane, carbon dioxide and freon were investigated. Double gas hydrates were found to be coming into use. Natural and artificial hydrates are now being exploited. The main properties and component composition of hydrates, as well as their extraction methods are described. The key aspects of using hydrates in the energy industry, gas chemistry and petrochemistry, heat exchange systems and fire safety management are highlighted. These specific aspects were identified by analyzing the known experimental findings, results of mathematical modeling, bench and field tests, as well as trial runs of industrial systems. The recent advances in science and technology in this field were analyzed. The range of tasks that need to be tackled to improve the efficiency of using gas hydrates are... [more]

Fuel cells are essential components of a large portfolio for developing a competitive, secure, and sustainable clean energy economy as they possess the ability to efficiently convert a variety of fuels into electricity. They convert chemical energy from fuels into electricity through chemical reactions with an oxidizing agent. Fuel cells are highly efficient and can produce electricity with very little pollution. They are used in a variety of applications, including powering buildings and vehicles, and as a backup power source. However, the infrastructure for fuel cells is still not fully developed and the cost of fuel cells is currently high, hindering their widespread adoption. This article discusses various advanced fuel cell types with descriptions of their working principles and applications. It provides some insights on the requirements of solar-derived chemical fuel cells as well as some novel materials for the fabrication of solar-derived chemical fuel cells. Discussions on the... [more]

Monitoring the partial discharge (PD) activity of power equipment insulation is crucial to ensure uninterrupted power system operation. PD occurrence is highly correlated to weakened insulation strength. If PD occurrences are left unchecked, unexpected insulation breakdowns may occur. The comprehensive PD diagnostic process includes the detection, localization, and classification of PD. Accurate PD source localization is necessary to locate the weakened insulation segment. As a result, rapid and precise PD localization has become the primary focus of PD diagnosis for power equipment insulation. This paper presents a review of different approaches to PD localization, including conventional, machine learning (ML), and deep learning (DL) as a subset of ML approaches. The review focuses on the ML and DL approaches developed in the past five years, which have shown promising results over conventional approaches. Additionally, PD detection using conventional, unconventional, and a PCB antenn... [more]

Even though generating electricity from Renewable Energy (RE) and electrification of transportation with Electric Vehicles (EVs) can reduce climate change impacts, uncertainties of the RE and charged demand of EVs are significant challenges for energy management in power systems. To deal with this problem, this paper proposes an optimal energy management method using the Virtual Power Plant (VPP) concept for the power system considering solar PhotoVoltaics (PVs) and Electric Vehicle Charging Stations (EVCS). The Differential Evolution (DE) algorithm is applied to manage energy in the power system to minimize the operation cost of generators and degradation costs in Energy Storage Systems (ESS) and generators. The effectiveness of the proposed approach is examined and tested on the IEEE 24 bus Reliability Test System (RTS 24) using the MATPOWER tool on the MATLAB program for calculating Optimal Power Flow (OPF). In this study, two situations before and after applying the proposed method... [more]

In three-dimensional (3D) computational fluid dynamics (CFD) simulations, the effects of injection timing and spray inclusion angle (SIA) on performance and emissions of diffusion-controlled and Premixed Charge Compression Ignition (PCCI) combustion in part load for a heavy-duty direct injection (HDDI) diesel engine are studied. The start of injection (SOI) of a 146° SIA injector is varied between −70 and −10 °crank angle (°CA) after top dead center (ATDC). For −50 °CA ATDC SOI with various SIAs between 80° and 146°, PCCI combustion reduces mono-nitrogen oxide (NOx) emissions significantly compared to conventional diesel combustion (CDC). Due to incomplete combustion in rich zones formed by droplet−cylinder wall interaction, early wide SIA injection deteriorates combustion efficiency (CE) and Indicated Mean Effective Pressure (IMEP) and increases soot and carbon monoxide (CO) emissions. Narrow-angle sprays interacting with the piston bowl elevate CE and IMEP and decrease soot and CO em... [more]

In classical power systems, frequency measurements are transferred via a specialised communication channel, resulting in time delay. The time delay plays a major role in a power system, which can reduce the dynamic performance of the load−frequency control (LFC) system and can destabilise the system. The research to date has tended to focus on developing a new algorithm to determine the delay margin (DM) rather than looking into a hybrid algorithm which includes a nature-inspired metaheuristic optimisation technique. This paper introduces a novel method for computing the DM based on grey wolf optimisation (GWO), specifically for the constant time delay. In the proposed method, GWO is employed to optimise the minimum error of the spectral radius and to determine the best design variable of the crossing frequency. With the help of the proposed method, the sweeping range is no longer required, which improves the accuracy of the result. To evaluate the proposed method, a two-area network p... [more]

The anaerobic digestion of New Zealand low-input dairy farms has previously been evaluated for energy production, but farming systems have recently become more intensive with increased feed supplementation and feed replacement; therefore, we are studying how these changes affect the overall energy production for water heating. A combination of literature review, surveys, chemical analyses, biomethane potential analysis, and modeling were used for this study. On a case study farm with a solid separator, it was found that 558 MJ/day and 176−861 MJ/day could be produced with the solid and liquid portions of effluent, respectively. There is enough biogas to satisfy the dairy farm’s water heating requirements with a tankless water heater.

Employment of a battery energy storage system to compensate for the generation-consumption mismatch is a vital element for a resilient microgrid. However, the frequent (i.e., short-term) cyclic activity and the abrupt current variations (i.e., high di/dt) have adverse effects on the energy-type battery’s lifespan. On the other hand, the power-type supercapacitor energy storage system (SCES) has almost zero lifetime degradation when it is subjected to irregular charging/discharging patterns. Therefore, the hybridization between them can reduce battery stress levels. This study proposes a droop control algorithm with multiple segments for a SCES/battery hybrid energy storage system (HESS) that is employed in a solar/wind DC microgrid. The presented control scheme is decentralized since it avoids the central controller (CC) and the communication links between the controllers of SCES and battery units. To eliminate the short-term cyclic operation of the battery, the SCES regulates the bus... [more]

The development of microgeneration plays an important part in the strategy of the decarbonization of the world economy. However, its diffusion faces different barriers, including the information and technical barriers on the side of the end-user. This paper contributes to the literature by providing a comparative cross-country analysis of the role of the corporate sector in providing the installation and technical servicing of PV solar panels and small wind turbines in the Republic of Armenia, India, Russia, and the United Arab Emirates. Business proposals from the microgeneration equipment market were analyzed by studying the official websites of companies offering autonomous and backup power supply solutions, followed by interviews with company representatives using the “mystery shopper” method. The study reveals that, of the four surveyed countries, the Republic of Armenia has the highest level of representation of service companies on the Internet (4.71 companies per million popula... [more]

A countermeasure to global warming is removing high CO2 amounts from the atmosphere and locating the emitted CO2 into long-term stable carbon storage sites. The sequestration technologies must be reliable, long-lasting, and environmentally friendly. An alternative and innovative approach that may meet the sequestration requirements is CO2 storage as clathrate hydrates in marine environments. Extensive research has been devoted to CO2-CH4 replacement in natural gas hydrates. Another option is the direct formation of CO2 hydrates into deep ocean water or into marine underfloor sediments. This article deals with the positioning of direct hydrate-based CO2 storage among the other traditional geological options and the discussion of new, by-far, state-of-the-art knowledge required for the development of a hydrate-based CO2 storage pathway that is reliable, stable, durable, efficient, and environmentally benign.

Bulk power grid interconnection and the access of various smart devices make the current grid highly complex. Timely and accurately identifying the power grid operation state is crucial for monitoring the operation stability of the power grid. For this purpose, an evaluation method of the power grid operation state based on random matrix theory and qualitative trend analysis is proposed. This method constructs two evaluation indicators based on the operation data of the power grid, which cannot only find out whether the current state of the power grid is stable but can also find out whether there is a bad operation trend in the current power grid. Compared with the traditional method, this method analyzes the power grid’s operation state from the big data perspective. It does not need to consider the complex network structure and operation mechanism of the actual power grid. Finally, the effectiveness and feasibility of the method are verified by the simulations of the IEEE 118-bus sys... [more]

This paper introduces a comprehensive examination of vector-controlled- (VC-) based techniques intended for induction motor (IM) drives. In addition, the evaluation and critique of modern control techniques that improve the performance of IM drives are discussed by considering a systematic literature survey. Detailed research on variable-speed drive control, for instance, VC and scalar control (SCC), was conducted. The SCC-based systems’ speed and V/f control purposes are clarified in closed and open loops of IM drives. The operations, benefits, and drawbacks of the direct and indirect field-oriented control systems are illustrated. Furthermore, the direct torque control (DTC) method for IMs is reviewed. Numerous VC methods established along with microprocessor/digital control, model reference adaptive control (MRAC), sliding mode control (SMC), and intelligent control (in terms of fuzzy logic (FL) and artificial neural networks (ANNs)) are described and examined. Uncertainties in the... [more]

This article presents a machine learning (ML) application to examine artificial lift (AL) selection, using only field production datasets from a Sudanese oil field. Five ML algorithms were used to develop a selection model, and the results demonstrated the ML capabilities in the optimum selection, with accuracy reaching 93%. Moreover, the predicted AL has a better production performance than the actual ones in the field. The research shows the significant production parameters to consider in AL type and size selection. The top six critical factors affecting AL selection are gas, cumulatively produced fluid, wellhead pressure, GOR, produced water, and the implemented EOR. This article contributes significantly to the literature and proposes a new and efficient approach to selecting the optimum AL to maximize oil production and profitability, reducing the analysis time and production losses associated with inconsistency in selection and frequent AL replacement. This study offers a univer... [more]

In smart grids, homes are equipped with smart meters (SMs) to monitor electricity consumption and report fine-grained readings to electric utility companies for billing and energy management. However, malicious consumers tamper with their SMs to report low readings to reduce their bills. This problem, known as electricity fraud, causes tremendous financial losses to electric utility companies worldwide and threatens the power grid’s stability. To detect electricity fraud, several methods have been proposed in the literature. Among the existing methods, the data-driven methods achieve state-of-art performance. Therefore, in this paper, we study the main existing data-driven electricity fraud detection methods, with emphasis on their pros and cons. We study supervised methods, including wide and deep neural networks and multi-data-source deep learning models, and unsupervised methods, including clustering. Then, we investigate how to preserve the consumers’ privacy, using encryption and... [more]