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The Internet of Things (IoT) is rapidly changing the number of connected devices and the way they interact with each other. This increases the need for an automated and secure onboarding procedure for IoT devices, systems and services. Device manufacturers are entering the market with internet connected devices, ranging from small sensors to production devices, which are subject of security threats specific to IoT. The onboarding procedure is required to introduce a new device in a System of Systems (SoS) without compromising the already onboarded devices and the underlying infrastructure. Onboarding is the process of providing access to the network and registering the components for the first time in an IoT/SoS framework, thus creating a chain of trust from the hardware device to its hosted software systems and their provided services. The large number and diversity of device hardware, software systems and running services raises the challenge to establish a generic onboarding procedure. In this paper, we present an automated and secure onboarding procedure for SoS. We have implemented the onboarding procedure in the Eclipse Arrowhead framework. However, it can be easily adapted for other IoT/SoS frameworks that are based on Service-oriented Architecture (SoA) principles. The automated onboarding procedure ensures a secure and trusted communication between the new IoT devices and the Eclipse Arrowhead framework. We show its application in a smart charging use case and perform a security assessment., IEEE Access

Hydropower contributes a lot to electricity generation. Myanmar has enormous potential for water resources which can guarantee domestic electricity supply and export surplus power to neighbouring countries. This paper analyses the status-quo of water resources and obstacles of Myanmar’s hydropower development, and concludes that: (1) Myanmar harbours great potential for hydropower development and utilization; (2) the spatial distribution of hydropower stations and the supply of electricity are unbalanced; (3) main obstacles for hydropower development and utilization include weak governance over water resources, lack of fund and technology, natural disasters and environmentalism resistance. To achieve full electrification in 2030, it is essential for Myanmar to promote the construction of both small-scale and responsible large-scale hydropower stations.

A high proportion of new energy sources are connected to the grid, which not only alleviates the energy shortage, but also brings hidden dangers to the safe and stable operation of the grid. Aiming at the inadequate consideration of uncertainty caused by new energy sources such as wind power being connected to the grid, a method for identifying voltage-dominant cascading fault types is proposed. A voltage-dominant fault analysis model in the sense of probability is established. Based on the fault data, the nonlinear mapping relationship between the initial fault and the fault propagation characteristics is established through the neural network. Finally, the effectiveness of the method proposed in this paper is verified in the IEEE39-bus system, and the simulation results show that the method proposed in this paper can effectively identify the fault types of high-proportion new energy systems.

With the increase of mining depth of coal seam, the impact pressure has severely restricted the coal mine safe and efficient mining, drilling pressure is a kind of through the construction of borehole in the coal seam, achieve the purpose of partial discharge, pressure relief effect is very obvious, the larger the aperture effect of pressure, the better, by comparing the 150 mm in diameter and 300 mm diameter CT detection construction surrounding rock displacement change. Compare the pressure relief effect of 150 mm drilling and 300 mm drilling.

Shearer is an indispensable and important equipment for coal mining and the mining efficiency of shearer depends on the performance of pick to a great extent. In this paper, we conducted a series experiments of single pick cutting on the coal and rock cutting testbed. Simultaneously, we built the single pick cutting coal seam model, based on which, considering the strength condition of coal seam and coal–rock interface, the rotary cutting mechanical model of pick cutting coal seam with coal–rock interface is established. According to the crushing theory of coal and rock interface, this paper analyzed stress strain and strength condition of the area surround the interface, which ensured the basics for the further research. The data of picking force in the cutting process under different experimental conditions was collected by the sensor installed on the drum, a phenomenon appeared in the amplitude domain analysis of the data that the bigger force arising along with the greater compressive strength difference between coal seam and coal–rock interface, which means the force is positively correlated with the compressive strength. The results of time domain analysis shown that some basic properties of the cutting load changes over times.

This paper takes an industrial extraction heating unit as the research object, introduces a heat storage device into the steam bypass and proposes two schemes for discharging, one for electricity users and the other for heat users. The unit’s original peak shaving plan, bypass peak shaving plan, and bypass heat storage combined peak shaving plan were analyzed in this paper by building a unit analysis model in Ebsilon software. The results show that the bypass heat storage combined peak shaving scheme for power users has the largest peak shaving range, it has increased by 163.87MW compared with the original unit when the heat supply get to the largest. In one storage and discharge cycle, the scheme of bypass heat storage combined peak shaving discharging to electricity users has the highest cycle thermal efficiency and the highest operating profit, compared with the bypass peak shaving scheme, the operating revenue of the scheme has increased by 16.85%.

Considering the failure mechanism of pick cutting coal & rock, combined with the cutting load test, the single pick load of cutting coal & rock is obtained and analyzed,​ based on the load of single coal & rock caving load change process in time domain analysis, establish the fold catastrophe theory model of cutting load, qualitative analysis, the change rule of cutting load and provide theoretical basis for the further study of cutting load. The single fracture load equation in cutting was obtained by numerical fitting, the load characteristics and change rule were analyzed by catastrophe theory, the coal–rock cutting system dynamics model was established. The mutation characteristics of coal and rock breaking process for pick pressing into the coal and rock until spallation are revealed, and the mutation mechanical model taking the load as disturbance factor is established. The stiffness of the cutting system plays an important role in cutting. The dynamic crushing load change process of coal–rock cutting mechanical system can be well described by catastrophe theory.

In the Tokamak device of controllable nuclear fusion, the poloidal field power supply (PFPS) provides the dynamic magnetic field inside the device. The power level of full-controllable devices has been improved with the rapid development of high-power semiconductor technology, which promotes the upgrade of poloidal field power supply. The PFPS adopts an AC–DC–AC circuit structure, which makes the load coil operate in four quadrants. Because the load is a superconducting magnet coil, the power of the load coil will change for a period of time to meet the demand of the internal magnetic field of Tokamak, resulting in the instability of DC bus voltage. This paper proposes an optimized bidirectional buck–boost active storage unit (ASU) with unidirectional inductor current, which can quickly make the bus voltage stable. In the circuit structure, the direction of the inductor current is unidirectional, which avoids the slow response of the inductor current in the reverse direction of the traditional buck–boost converter; And the inductor has a controllable freewheeling circuit, which can reduce the disturbance of inductor current to bus charging. The number of inductors is small, which avoids the large volume of traditional dual-inductor DC–DC converter; Compared with the traditional buck–boost converter, the buck–boost ASU with unidirectional inductor current improves the energy utilization of the bus capacitor. By establishing the mathematical model of the circuit topology, the dual closed-loop controller and modulation strategy are used to control the stable operation of the system. The simulation results show that the circuit structure can balance the bus voltage well and keep stable, when the load power changes suddenly.

In recent years, power grid enterprises have continuously promoted the construction of intelligent operation inspection system. Pilot applications of various equipment status sensors, online monitoring devices, intelligent wearable devices, mobile terminals and Beidou navigation satellite system have been gradually carried out. The configuration range of intelligent equipment such as UAV and robot has been continuously expanded, and big data analysis technology, artificial intelligence diagnosis technology have also been preliminarily applied. With the continuous development and breakthrough of key technologies such as edge computing and wireless transmission, it provides favorable conditions for the intelligent, diversified and ecological development of the construction and application of the IOT for power transmission and transformation equipment. This paper mainly introduces the overall architecture and functional positioning of the construction of power transmission and transformation IOT, and combined with the business needs of some typical application scenarios in the operation of power grid equipment, to promote the integrated application of IOT technology and power grid equipment operation and inspection business, and also establish an open, shared and symbiotic IOT ecosystem of power transmission and transformation equipment, so as to lay the foundation for intelligent equipment management.

In this paper, bulk water abstractions and a purification process in terms of water pumped energy consumption, is modelled and simulated. The study proposes an optimal energy consumption-rate management system, using real-time data. The aim is to achieve the goal of obtaining potable water by scheduling the pumping process, to obtain the cheapest energy-rate at any given load demand. Considering the loss due to the effect of evaporation, the effect of precipitation (or rainfall) and seepage losses. As a baseline, an electronic timer switching system for the powering of electrical pumps, used to pump water from one level to another, is incorporated. An optimal control system is included that looks at the energy cost before scheduling the pumping sequence in such a way that pumping occurs during the more affordable energy costing period and ensures that the water demand from consumers matches the water pump level in the storage reservoir. The configuration involved the time of use (TOU) tariff; in the context of the South African electricity tariff. The optimal control output, compared to an electronic timer switching system, shows an end-of-day cost reduction of 1994 ZAR in water-pumped energy consumption from the grid. This reduction in energy consumption is therefore a direct reflection of the reduction in the cost of water supply to consumers.

Based on the analysis of the operation characteristics of photovoltaic cells, a novel virtual synchronous generator adaptive power regulation strategy for two-stage three-phase photovoltaic system with high permeability of clean energy is proposed. By improving the maximum power point tracking process of photovoltaic cells, the variable power point tracking control of photovoltaic cells is realized, and the control effect of DC/DC converter on the output power of photovoltaic cells is fully exerted. Without additional energy storage equipment, the energy supply required for inertia support and primary regulation of virtual synchronous generator is accurately realized. Combined with inverter VSG control strategy, the control of photovoltaic virtual synchronous generator is realized.

Natural-gas fired units (NGFU) occupy an increasingly important position in the power system, leading to a closer connection between the power system and natural gas system, especially in the distribution level. To utilize the residual differential pressure energy and reduce operation costs, the conversion model of the generator using residual differential pressure energy is formulated, and then the cooperation model of the power system and natural gas system is built in this paper. Due to the original optimization model of power system and natural gas system in the distribution level is non-convex, the second-order cone programming (SOCP) based on a modified convex concave procedure (CCP) algorithm is used to handle the NP-hard problem. The simulation results show operation costs are reduced via the proposed strategy, and the SOCP based on the modified CCP algorithm achieves good performance in fast solution with the constraint of Weymouth equation.

The chemical looping hydrogen production (CLHP) process is a new approach for hydrogen ( H 2 ) fuel production. The proposed process consists of three reactors which are air reactor (AR), fuel reactor (FR) and steam reactor (SR). In this study, the gas solid flow behaviour in a cold model of the proposed CLHP process was simulated using computational fluid dynamics (CFD) with kinetic theory of granular flow. The effect of drag coefficient models on the pressure profile of each reactor was investigated and the results from the modified Syamlal–O’Brien drag model agreed well with the experimental data. The model was further used to investigate effects of the operating parameters on the hydrodynamics profiles of each reactor. The solid flux increased with the increasing of inlet velocity of AR and FR but decreased with the increasing of the inlet velocity of SR. At the same time, the solid flux increased with the increasing of the solid inventory.

With the rapid development of clean energy and the deepening of the interaction between supply and demand, power grid investment upgrading measures involve many new elements, such as clean energy installation and distribution automation. Traditional investment decision-making models are difficult to establish and solve. In view of this, this paper analyzes the investment benefit mechanism directly from the perspective of investment input–output relationship, and designs an interactive auxiliary investment decision-making system based on correlation rule mining. The system constructs an investment benefit mapping model from power grid investment measures to benefit output by means of deep transfer learning, and provides three objective functions, which consider the optimal economy, performance improvement and comprehensive index optimization, thus assisting decision makers to formulate investment alternatives according to different investment needs. A case demonstrates the decision-making process based on an actual power grid, and verifies the practicability and effectiveness of the system.

Nowadays, the scale of power grid is remarkably increasing and there is a continuous reinforcement of AC–DC hybrid systems. Thus, the single-phase grounding fault currents on the AC grid-side of rectifier and inverter stations increase significantly, which may exceed the capacity limit of the circuit breakers. The large short-circuit currents would result in problems during equipment selection and threaten the safety of equipment and personnel. To solve such issue, the effect of the converter transformer on the single-phase grounding fault current on the grid-side is analyzed. The mechanism of high short-circuit current in DC near region is revealed. Also, the feasibility of neutral point earthing via small reactor at HVDC converter transformer to suppressing the single-phase grounding fault current is verified. In addition, the principle of selecting the suitable small reactor is summarized. The results show that the neutral point earthing via small reactor at converter transformer can effectively limit the single-phase grounding fault current on the AC-side. However, it would lead to an increase of overvoltage at the neutral point of HVDC transformer. Therefore, neutral grounding by small reactor might be implemented when the insulation level is satisfied.

Insulators are the most crucial part of power systems. The insulation performance of insulators is vital for the sustainability of power systems. Recently, silicone rubber (SiR) insulators are used frequently in all sections of the power systems. In this paper, a SiR insulator currently used in power transmission systems has been analyzed under combined AC-DC voltage using the finite element method. In the analysis, positive and negative DC voltages in different amplitude ratios were superimposed over the phase-earth operating voltage of the insulator. Analyses in the study were made in time-dependent. Only DC voltage was applied to the insulator for the first 60 s, AC + DC voltage was applied between 60 to 120 s. Thus, the electric field behavior of the SiR insulator under combined AC-DC voltage has been obtained. The change of electric field based on positive and negative DC components was investigated. As a result of the study, the effect of the polarity of the DC component in the combined voltage was observed. As a result, effect of the polarity of the DC component in the combined voltage on the maximum electric field intensity was observed. (C) 2021 The Author(s). Published by Elsevier Ltd.

An energy harvesting system requires a power converter with its compact size and high power efficiency. Following the trend, this study suggests a new switched capacitor converter (SCC). The proposed converter is designed by a parallel- and cross-connecting two Fibonacci topologies. This connection leads the proposed SCC to generate its multilevel outputs as well. The proposed SCC has the lowest output resistors under five times conversion ratios from the theoretical analysis and comparison of two different SCC topologies. Simulation results confirm that the proposed SCC can be operated over 90% power efficiencies under 100 mW.

Masses of user-side smart meter data provide a foundation for utilities to acquire users’ electricity consumption patterns and promote refined energy management. Therefore, the charging load of electric vehicles can be identified non-intrusively through the smart meter data of residential users, which provides flexible resources for the demand side response of power grid enterprises and is beneficial to the power dispatching decision making. Meanwhile, revealing residential energy consumption behavior from smart meter data is treated as energy privacy leakage. Extensive data collection from smart meters has raised privacy risk, which could lead to the reduction of trust in utilities from households. Aiming at this problem, the paper proposes a non-intrusive method to extract residential electric vehicles, and on this basis, discusses the privacy protection. In this paper, DWT method is used to decompose the total power of smart meter to extract the charging load of electric vehicle, and similar charging load patterns are added to smart meter data to preserve the residential EV charging behavior privacy. Practical households with EVs are used to test the proposed method and the result shows its feasibility for the performance of privacy-preserving.

Along with the deepening of the power system reform, the input and output evaluation and analysis of asset became more and more important. Arounding the goal of comprehensive optimization of safety, efficiency and cost throughout the life cycle of assets, this paper constructed a quantitative evaluation model for asset input–output analysis, and put forward an input–output analysis method combining the boston matrix method and the equivalent analysis method. Actual substations’ input cost and output efficiency analysis verified the method feasibility, which could provide decision-making support for optimizing power grid asset management strategies and enhancing asset value operation benefits.

The difference between load demand in the off-peak and peak period is usually high in the context of Nepal, and the high peak load for a short time is the main reason for insufficiency in electricity, frequent electricity outage, and poor power quality. This paper investigates the effectiveness of the time of use (TOU) strategy to reduce peak demand and to improve power quality. TOU electricity price is one of the electric demand response (DR) strategies, which may motivate the customers to reduce their consumption in peak periods and shift load in the off-peak period, which propel the electricity industry towards a higher efficiency compared to that of common flat prices. In this paper, a process based on an equal step length iteration algorithm is used to obtain an optimal period partition. Using the particle swarm optimization (PSO) algorithm, a TOU-based optimization model is proposed to find the optimal electricity price. Then, its impact on peak demand reduction and voltage fluctuation is analyzed. The impact of TOU price on peak demand reduction is investigated in the hourly load profile of Nepal, which indicates the significant reduction in peak demand. Similarly, the impact on voltage fluctuation is analyzed through a case study of the IEEE 33-bus radial distribution test system, which shows voltage profile is improved.

South Africa power system has undergone several power reforms from the pre-apartheid to post-apartheid era under various administrations in a bid to meet the increasing energy demand of its populace. Her enormous available renewable energy sources give hope for a revolutionized power sector with minimal environmental pollution. This research will therefore review the energy transition phases of South Africa power sector from the pre-apartheid to post-apartheid era, highlighting the various strides made by South African government towards the realization of a dominant renewable energy sourced grid. Furthermore, performance evaluation of the renewable energy driven programmes and its impact in promoting renewable energy sourced grid will be carried out based on five key performance metrics which are energy accessibility, energy diversification and enhancement, energy governance, environmental impact, and economic impact. In addition, the prevailing challenges of the South Africa energy system is highlighted, while a proposed model towards achieving a dominant renewable energy sourced grid is put forward.

A hybrid solar lighting/ thermal system utilized a parabolic solar dish as a solar collector illustrated in this paper. A two-axis tracking system was developed and employed to improve the energy output of a concentrating solar system (CSP) that produces hot water and light. During the daytime, sunlight is transmitted by fiber optics to an indoor photovoltaic PV device to generate electricity, or it can be used directly as daylighting. The heat generated is used to heat water. The findings show that the proposed system is a low-cost, high-performance approach for solar energy use in building energy efficiency, and readily available tracking components and tools. The experimental work shows that the maximum efficiency of the hybrid solar lighting/ thermal system controlled with a dual-axis solar tracking system was 32.2%.

Thermoelectric generator can directly convert thermal energy into electrical energy, and applying it to recover waste heat from automobile exhaust is conducive to energy saving. In this paper, a thermoelectric generation experimental system is built, the power output performance and channel power consumption of the flat-plate thermoelectric power generation system under different exhaust gas flow rates are experimentally studied. The results show that when the exhaust flow rate is 40 Nm3/h and the exhaust inlet temperature is 400 °C, the maximum output power of the system is 26.8 W, and the maximum net output power is about 23.3 W. In addition, the exhaust flow rate is changed from 10 Nm3/h to 40 Nm3/h, and the proportion of power consumption in the hot air channel is changed from 1.91% to 12.85%, which has increased by more than six times.

The Chinese Fusion Engineering Test Reactor (CFETR) aims to bridge the gap between the International Thermonuclear Experimental Reactor and the demonstration fusion power plant. Its coil power supply system (CPSS) will be connected to an external high-voltage power grid for producing large pulsed active power and reactive power to feed its superconducting coils. To analyze the impact of its active power on the connected high-voltage grid, the active power signal should be modeled initially. Herein, the characteristics of the active power of the CPSS are analyzed by comparing with the pulsed load, photovoltaic power, and wind power. It is modeled as a combination of periodic and decaying components, which are decomposed by the fast Fourier transform (FFT) and improved Prony methods, respectively. The proposed Prony constraint is diagnosed, and the mode size is changed to avoid exceeding the parameters. Both the calculated signal-to-noise ratio and fitting curves show the high accuracy of the proposed estimation procedure. Numerical results show that the number of selected FFT signals has no distinct influence on the estimation accuracy. The optimum Prony mode size of the decaying component estimation may be half the actual signal size when both the computing time and accuracy are considered.

The DC transformer based on the Modular Multilevel Converter (MMC) structure has the advantages of robust scalability, low output voltage harmonic content, easy realization of back-to-back connection, and high power transmission efficiency. It is widely used in DC distribution networks. However, traditional control methods hardly provide inertia for the DC distribution network, thereby reducing the stability of the distribution network when new energy output fluctuations, DC distribution network failures, or other disturbances occur. Aiming at the problem that the DC bus voltage is easily affected by power fluctuations, the paper proposes a virtual inertia control method applied to the DC transformer with MMC structure. Similar to the introduction of virtual synchronous generators in the AC distribution network to enhance the system inertia, the paper designs a control strategy for dynamically adjusting the virtual inertia with a virtual capacitor added, which is based on the traditional two-phase shift control. The paper also presents the calculation method of the virtual capacitance. When the power in the DC microgrid fluctuates significantly, the strategy can effectively enhance the inertia of the DC distribution network and suppress the voltage fluctuation of the DC bus. The paper finally establishes a DC distribution network model with distributed power sources in the PLECS simulation software, and verifies the effectiveness of the control strategy compared with the traditional strategy.

To handle the multiple-objective problem including carbon emission reduction and economic operation of integrated energy system (IES), this paper proposes an optimal scheduling model for IES considering combined weights for low-carbon and economic operation. In the dispatch model of IES, we mainly use the combined cold heat and power (CCHP) to optimize the energy distribution, and use the charge and discharge power of electric vehicles (EVs) to enhance the regulation capability of CCHP. Furthermore, aiming at the lowest carbon dioxide emission and economic cost, and the highest renewable energy accommodation, a multi-objective function considering combined weights is proposed, which combines subjective weights with objective weights. The balance constraints of electricity, heat and cold for the IES are established. Finally, the particle swarm optimization algorithm is used to optimize the multi-objective model based on the energy balance and unit constraints of IES. The proposed method is verified by the case studies. The results show that the proposed model can improve the accommodation of renewable energy and reduce carbon dioxide emissions.

We first comprehensively analyze determining the generating capacities of each type, then discuss the heat distribution across interconnected district-level heat energy systems (“the hubs”) containing both low-scale and centralized heat plants; discussion is presented from the standpoint of primary energy consumption and costs. The applied tool includes a flexible heat generation model and an accurate objective function. The set of constraints and the Jacobian matrix are configured manually. We apply the fixed-point iteration approach to solve an equation system. In order to evaluate the consequences of all possible scenarios, we analyze a novel district heating (DH) system with low-scale solar collectors and heat pumps against central combined heat-and-power (CHP) plant fueled with fossil fuels and biomass. The proposed system is evaluated from the standpoint of the state-of-the-art, future prospects, and environmental impact. For each specific type of capacities, we herein present maximum achievable net generation of heat. System layout sketch is based on the data on the actual districts of Canberra, Australia. All the hubs are studied as a whole with due account of heat redistribution. The configuration made implies construction renewable energy facilities with a heat generation of 6.5+ MW, which will suffice to cover about a fifth of the peak load. This approach is quite novel for Australia. With greater electricity and heat supplies, renewable resources can cover an even greater share of such supplies. To sum up, a significant difference between the costs of a natural gas-based DHS and a coal-fired DH one lies in the fixed costs of operating the CHPPs and in the fuel costs. The self-generation of a hub may be inconsistent with the total energy balance, which is the total of eigen-production, energy inflows and outflows. The total system performance is considerably better when coal-fired CHPPs account for the bulk of net production.

In this paper, the steam production of the power plant from four biomass types has been investigated via the combination of the neural network (NN) model and constrained particle swarm optimization (CPSO) methods. First, the power plant modeling was accurately developed using NN simulation. Then, the model was applied to the optimization step, where the CPSO (the modified algorithm from the classical PSO) was introduced. The proposed method included real operation constraints to the algorithm, such as biomass feed availability and minimum steam production rate. In the optimization step, the COP has been defined as the cost function to check the present operation’s economic viability. To obtain the minimum production cost (COP), the CPSO suggested feeding wood bark from sources C and D with the amount of 104.1 and 463.8 tons/day, respectively. The result has been extensively validated by the real operation. The calculation framework in this study then applies to various production systems. Besides, by integrating the cost function in the optimization model with other indicators such as environmental impact indices, the output would provide an additional holistic picture of economic and environmental aspects.

In the two-stage converter such as PV renewable energy system, the second harmonic fluctuation exists in the DC voltage due to the power coupling between the DC-link and AC system. The second harmonic voltage in the DC link could increase the system loss and decrease the stability of the converter system, and its generation process and transmission mechanism are analyzed in this paper. The mathematical expression of second harmonic voltage in DC-link has been derived. A second band passing filter (BPF) feedback control loop is used to feedback the second harmonic ripple voltage in DC link into the statable modulation index. This strategy can decrease the second harmonic voltage in the DC-link and the third harmonic voltage in the AC sides. Finally, the control parameters are implemented using a simulation platform, and the match suppression strategy is validated by the simulation results.

The flow dynamics inside cavities associated with turbulent incoming flow and oscillations of the cavity shear layer is an important field of study that has attracted many researchers aiming to understand the complex flow features using both numerical and experimental techniques. Such a flow exists in many industries, such as in the automobile industry for flows over the sunroof of vehicles, and in the energy industry such as in finned heat-exchangers, combustion chambers, and turbines that utilizes wind energy harvesting in buildings. Most of those studies focused on the aero-acoustic mechanism and its control. Despite its wide industrial applications, heat transfer in cavity with oscillating shear layer remains less studied in the literature. The present paper presents a literature review of various studies that focuses on the heat transfer mechanism in those cavity configurations and how it is affected by the flow parameters.

The use of lower global warming potential refrigerants as an alternative to hydrochlorofluorocarbons and hydrofluorocarbons from an environmental perspective is the need of an hour. The feasibility and possibility of alternative refrigerants in the existing refrigeration system can be recognized using exergy assessment. This will lead to improving the thermal performance of the refrigeration systems. In this paper, exergy assessment of a multistage multi-evaporator vapor compression refrigeration system is performed using the Simulink model. A total of eighteen refrigerants are considered for the analysis from the environmental perspective, safety considerations, etc. The evaporator-1, evaporator-2, and condenser temperatures are varied from 0 °C to 15 °C, −15 °C to −5 °C, and 25 °C to 33 °C respectively. The highest exergy destruction among all the components is found for both the compressors, followed by the condenser, evaporators, expansion devices, and internal heat exchanger. Refrigerants R141b, R123, R245ca, R245fa, and R152a showed better thermal performance than hydrofluoroolefins refrigerants, but have high GWP values. R1234ze(E), and R1234yf are environmentally friendly and achieved similar performance to conventional refrigerants.

The use of renewable energy to realize decarbonization is rapidly increasing, and considerable research is being performed to achieve highly efficient high-voltage direct current (HVDC) transmission for offshore wind power generation over long distances. However, in the case of onshore AC power transmission and distribution systems, with the mass introduction of distributed energy resources (DERs), voltage and frequency fluctuations often occur. It is thus necessary to implement the control function of smart inverters, which can facilitate the stabilization of the AC system, in the grid-connected inverters of DERs. Virtual synchronous generator (VSG) control is a smart inverter control strategy that can contribute to the stability of the AC system. In this study, conventional power control and VSG control were applied to the control strategy of modular multi-level converter-based poles of the HVDC transmission system, and the AC system fault tolerances of the entire system were examined.

When renewable energy is applied to the power grid, it will cause problems such as harmonic interference and changes in grid frequency, resulting in harmonic distortion of the inverter and other renewable energy grid-connected equipments output current. So the grid-connected environment of weak grid puts forward higher requirements on the performance of phase-locked loop (PLL). Therefore, these renewable energy grid-connected equipments require Phase-Locked Loop (PLL) with higher technical performance. Aiming at the control requirements of inverter and other grid-connected equipments in weak grid, an optimization method based on a novel PLL is proposed. The method uses a dual enhanced novel cascade second-order generalized integrator (DENCSOGI) to simultaneously filter out the fundamental voltage negative sequence (FVNS) component and the DC offset (DCO) voltage component, and it can speed up the dynamic response and phase-locked accuracy of the PLL. The proposed PLL is verified by the simulation experiment platform. The performance of the approach is excellent and the grid-connected power quality of the renewable energy grid-connected equipments is guaranteed.

The ongoing energy revolution has led to the gradual replacement of traditional synchronous generators by renewable enecorresponding authorrgy. This transformation of power generation mode reshapes power system dynamics and poses many challenges to reliable and efficient grid operation. With the continuous improvement of the penetration level of renewable energy represented by wind power in the power system, the synchronous mode of wind turbine will gradually become one of the main modes of system synchronization. In the case of coexistence of multiple synchronization modes, the synchronization mechanism of the whole power system will be fundamentally changed; at the same time, due to the response characteristics of wind turbine to the frequency and voltage dynamics of power grid and the traditional power supply, the synchronous mode of wind turbine will gradually become one of the main modes of system synchronization The frequency and voltage stability of power system also faces new challenges. The virtual synchronous generation technology can make the grid connected inverter simulate the operation mechanism of step generator and provide an effective method to solve the above problems. In this paper, the main technical routes to realize virtual synchronous control of wind turbines are summarized. From the aspects of stability analysis, control system optimization, performance analysis and evaluation, the research and engineering status of virtual synchronization technology in wind turbines are introduced, and the problems to be solved and technical requirements are prospected.

The solar radiation is a critical metric for design and optimal operation of the solar energy system. Most of the locations available solar radiation records are not available due to high cost for buying and maintaining the measuring instruments. Aim of this paper is building an efficient neural network model that can reliably estimate solar radiation. In this work, different ANN models with three popular algorithms admired from the literature are investigated. The models were trained using meteorological data collected over a year from six different places from the hot area locations of Tamil Nadu, India. Based on minimal Mean Absolute Deviation (MAD), Mean Square Error (MSE), Root Mean Square Error (RMSE) and Mean Absolute Percentage Error (MAPE), the optimum ANN algorithm and model are determined (R). Furthermore, the research illustrates that the ANN model’s prediction performance is dependent on the entire set of data utilised to train the network. Also, this article aims at finding out the accurate number of hidden layer neurons for the developed model. The proposed ANN model offers improved accuracy and applicability for estimating hourly average global radiation for the purpose of designing or evaluating photovoltaic (PV) installations in areas without meteorological data collection facilities.

Energy is one of the most important requirements for countries and serves as an indicator of the development level of a country. Developments in social, economic and industrial areas have increased the energy needs of countries. Solar energy is one of the most promising renewable energy sources to meet increased energy demands. Photovoltaic (PV) models used to generate electricity from solar energy are among the most popular renewable energy systems. To obtain maximum efficiency from PV models, it is very important to estimate parameters based on current–voltage data, simulate and control PV models for electricity generation. To achieve maximum efficiency for PV models, their parameters should be estimated in an optimum way. Therefore, tree seed algorithm (TSA) developed inspired by nature was proposed in this study. TSA is a meta-heuristic algorithm inspired by the connection between trees and seeds and proposed for solving continuous optimization problems. Parameters of three different PV models (single diode model, double diode model and PV module) were optimized with TSA. Various analyses were performed to prove the success of the proposed method in parameter optimization of PV models. The results were also compared with those of similar studies in the literature. The analysis results indicated that the proposed method yielded very successful, effective and reliable results, and it was concluded that it was a competitive method compared to other methods in the literature.

This paper presents the PLC-Based system for controlling the SCR power module which is AC–DC converter proposes to linearity output voltage with trigger signal. The technique converted the trigger signal by arccosine function and analog module in the PLC. Converted signal from PLC system is fed to SCR power module instant the traditional signal. Proposed of this paper describes the PLC hardware configuration, compute/math and trigonometric functions with Studio 5000 software. In addition, the interfacing, parameters configuration, and monitoring are considered for testing. The technique with PLC-based, devices configuration and experimental results have been presented will be useful for electric power supply in the industry with more and more demand to apply the PLC system to develop the traditional industry to semi or automatic control in the industry.

With the continuous deepening of power market reforms, studying the interaction of multi-stakeholder in multi-microgrid (MMG) energy trading is of great significance to improve the economic performance of the distribution network. In order to analyze the economic optimization method of multiple stakeholders in the distributed energy system, this paper proposes a multi-stakeholder benefit optimization method based on Stackelberg game theory (SGT), and establishes a local market energy transaction model. The model is composed of external distribution network, leader-intermediary agent (IA) and follower-microgrids (MGs), and uses the master–slave game method to solve the optimization strategy. Under this mode, the profit of each stakeholder in MMG increased by 2.64%, 4.24%, 1.38% respectively. The case results show that based on the method in this paper, multi-stakeholder in MMG can improve economic performance and can increase the level of energy autonomy of MMG.

In this work, the influence of cooling the back surface of the PV on its electrical power generation and efficiency was experimentally investigated. The proposed cooling technique is not only considered simple and cheap but can also introduce an efficient way for preheating the feed water of reverse osmosis desalination system. Two identical PV modules were simultaneously tested; with and without cooling. The results showed that the power generation of the PV was improved by about 14.1% when the proposed cooling system is implemented. The electrical efficiency also reached 19.8% when the PV module with cooling system was tested compared to 17.4% obtained without cooling.

System integration for process automation promoted the technologies that were accessed to functions and data of field device, controller, and SCADA system. In addition, the data from filed devices can apply to solve device diagnostic and preventive maintenance. This paper describes the practical technique to configure and implement of control and SCADA system that focus on integration of field device, PLC controller, and SCADA system. The paper presents case study of Allen-Bradley (AB) PLC by using WirelessHART device to temperature control and device diagnostic through SCADA system. PLC’s input/output (I/O) modules are installed that consists of Modbus module, digital I/O module, analog I/O module. In addition, Prosoft configuration builder and Studio 5000 software are new software to build add on Modbus instruction and ladder diagrams, respectively. The experiments perform in case study of temperature control by using Proportional–Integral–Derivative (PID) function in the AB PLC. Wonderware InTouch SCADA software is implemented to monitor the process mimic, trend, and alarm. Moreover, the technique can support the operators and engineers to make decision for process control and devices diagnostic.

In the collection and transmission of power big data, the problem of data missing exists. In response to this problem, this paper proposes a power data detection and repair method based on SOM-LSTM. Firstly, a large amount of collected power data is analyzed and the type of missing data is determined. Then, the SOM is used to classify the power data. The LSTM is trained according to the characteristic values of different users to complete the detection and repair of different types of missing power data. Finally, the analysis is based on actual data in some regional loads of China. Experimental results show that, compared with the extreme learning machine (ELM) and LSTM, the proposed SOM-LSTM model reduces the mean absolute error (MAE) by 0.2498 and 0.3425, and the root mean square error (RMSE) by 0.1048 and 0.1469, respectively.

The employment of 1D model of the thermal stratification in the tank of an air to water heat pump (AWHP) may accurately predict the evolution of the temperatures at the different layers. The study predicted the water temperatures at different levels in a 150 L tank coupled with 1.2 kW heat pump unit. A data acquisition system was designed and built to monitor the input and output parameters used in the model to evaluate the evolution of the water layers’ temperatures. The results depicted that the 1D linear model accurately predicted the evolution of the water temperatures at each layer due to thermal stratification with a determination coefficient ( R 2) and root mean square error (RMSE) of 0.9932 and 0.9253. The modelled validation showed a very good R 2 and RMSE of 0.9940 and 0.8595. The average thermal energy gained and the average COP due to the first hour heating rating (the withdrawal of 150 L of the hot water) was 5.67% lowered under the stratification condition when compared to the scenario without stratification. The p -values show no significant differences among the water temperatures at the different layers due to first hour heating rating. The study will encourage researchers and energy service companies to highlight the impact of thermal stratification regarding to the dynamics of an AWHP.

Solar grid systems are widely used especially in remote locations where electricity accessibility from the grid is limited. The major issue frequently encountered in microgrid-connected photovoltaic (PV) systems are voltage overshoots, transient response and steady state errors causing instability of microgrid during unsymmetrical temporary faults in the distribution network and damages the sensitive loads. PV-grid solely depends on solar hours per day and is not reliable at location with variable weather conditions. Therefore, the generated power per day is reduced as per daily demand and would create power quality issues in a distribution line. Additionally, the PV-grid system exposed to weather experiences unsymmetrical faults due to severe weather conditions that affects the reliability of the grid and electricity supplies. This study presents a technique to enhance the stability of microgrid by using dynamic voltage restorer in a three-phase grid connected system to mitigate power quality issues arising from PV-grid side in a harsh weather condition. The most significant extreme weather conditions such as thunderstorms and high winds are potential causes affecting the instability of transmission network by generating faults such as double line-to-ground, single line-to-ground, lightning strike or impulse transients, and power outage in a distribution line. The proposed technique enhances the transient stability of microgrid and provides symmetrical operating conditions for the load. The control mechanism extracts the fault signal and stabilize the error signal. In the proposed configuration, hysteresis-band PWM generator drives the inverter with the PV based battery storage system connected at DC-Link. The simulation results are verified by using IEEE519 standards limits in four case studies to mitigate power quality issues arising due to severe weather conditions by injecting compensating voltage to protect load and act as microgrid in case of power outage.

Affected by high switching speed and parasitic parameters, crosstalk problem of eGaN HEMT in a phase-leg configuration cannot be ignored. By decreasing gate driver turn-off voltage, the false turn-on phenomenon of device caused by crosstalk can be avoided, but it is hard to realize the minimization of total power loss. Thus, we analyze the influence of gate driver turn-off voltage on eGaN HEMT reverse conduction loss, switching loss and crosstalk voltage, and propose an optimized design rules for determining turn-off voltage value in a phase-leg configuration. By reasonably choosing gate driver turn-off voltage, a balance between optimal loss and reliable operation is achieved, thereby effectively alleviating the conflict between efficiency and reliability in the power electronic system.

The temperature-sensitive electrical parameter (TSEP) method is widely used in the extraction and prediction of junction temperature ( T j ) of power semiconductor devices. In this paper, turn-off loss ( E off ) and turn-off time ( t off ) are taken as temperature-sensitive electrical parameters. It is proved that the junction temperature of the insulated-gate bipolar transistor (IGBT) changes abruptly during switching. The common defects of a single temperature-sensitive electrical parameter, including collector current requirements and poor junction detection accuracy, are considered. Therefore, after proving the linear relationship between junction temperature, turn-off time, and turn-off loss, a hybrid model based on turn-off loss ( E off ) and turn-off time ( t off ) is proposed to accurately extract junction temperature. The experimental results show that this method has the advantages of high precision and strong anti-jamming ability.

Because the gas insulated switchgear (GIS) is closed, it is impossible to directly see the actual position of internal contacts. The image recognition technology can be used to collect, analyze and process the images of the switches in different states, and finally obtain the actual opening and closing state. In addition, some potential flaws can also be identified in advance. Considering the particularity of the GIS internal environment, wireless charging system can be used to supply power for internal video sensor. In this paper, a new type of coupling coil structure, DC coil, is proposed, which supplies power for video sensor through GIS observation window by wireless power transfer (WPT) technology. The proposed DC coil is analyzed theoretically, optimized by genetic algorithm (GA), and verified by finite element method (FEM). The experimental results indicate that the proposed structure can achieve the same transfer performance in lateral and rotation misalignment, while the conductor and space is saved by 8.49% and 22.22% compared with the traditional DD coil. The proposed DC coil is feasible to be applied in the actual GIS scene.

This paper presents a stochastic model to quantify the impact of the electric vehicle (EV) on China’s electricity load profiles. Most of the existing literature utilized travel data to model EV charging behavior and ignored the influence of people’s social attributes that are significant for the accuracy of EV charging behavior. Based on the dataset of the national household travel survey, the most significant influencing factors, e.g. age, location, and weekday/weekend, are identified. Markov-chain is used to construct a sequence of destinations of each vehicle trip, depending on EV’s driver, day of the week, and time of day. Vehicle-driven distance, driving time, and parking duration are used to model electricity demand and potential EV charging flexibility. The charging infrastructure accessibility in a certain parking location has an influence on EV charging decisions. The model’s outputs are used to assess the impacts of various EV charging strategies on electricity load profiles on a national scale. It is found that at 60% gasoline vehicle replacement with EVs by 2050, the electricity demand of EV will be 510 TWh, accounting for 4.5% of the national demand in 2050. The national peak loads will further increase by 8.2% under the unmanaged charging strategy of EV. In contrast, implying last-minute charging strategy only increases peak demand by 2.6% relative to the unmanaged charging strategy.

Nowadays, the applications of machine learning techniques have widely been implemented in various domains of the power system and especially to predict three-phase transmission line faults. This paper compares the results obtained from two powerful machine learning techniques such as Concurrent Neuro-Fuzzy and Decision Tree applied to predict faults classification and their location on a nine-phase transmission line system. The results obtained demonstrated that the utilization of these artificial intelligence techniques which have been well applied on various and diversified systems could also been applied on a future nine-phase transmission line system that carry 750 kV over 200 km to classify and locate various fault types and then, to increase the yield of the line.

Due to long-term exposure to the natural environment, insulators are prone to self-blast, threatening the safety and reliability of transmission lines. Because of the different sizes of the insulator self-blast area and the complicated background, it is inevitable that the missed and false detections occur. To solve this problem, this paper proposes a deep neural network called Mina-Net (Multi-Layer INformation Fusion and Attention Mechanism Network). Mina-Net is based on YOLOv4. First, the shallow feature map with more detailed texture information is fused into the feature pyramid. Then, an improved SENet is applied to recalibrate the features of different levels in the channel direction. The experimental results on the actual dataset show that Mina-Net has increased the average precision by 4.78% compared with the YOLOv4.

Natural disasters threaten the sustainability of electric power supply. This fact highlights the importance of enhancing technological resourcefulness to handle the upcoming events. Once a natural disaster occurs, the most urgent undertaking is to rapidly pinpoint and assess component damages and dispatch the repair crews towards the most critical impaired elements. Practical efforts confirm that utilising a drone, which is an unmanned aerial vehicle, can notably reduce the duration of post‐disaster distribution system damage assessment (DA) and increase the resilience of power systems. This study presents an optimisation model to determine the optimal number and type of drones required for DA. The main goal is to minimise the time duration of the DA mission, which includes scanning the grid and identifying the damaged components. As a matter of fact, the financial resources are limited, so the problem is subject to the available budget constraint. Besides, the technical capacity of purchased drones for inspecting the grid is considered. The optimisation problem is formulated as a mixed‐integer programme with a guaranteed optimum solution. Case studies confirm the applicability of the model and the optimality of the results. As the major conclusion, the best allocation is a compromise between the speed and price of drones.