Search

Considering the complex coupling of multiple energies and the varying load forecasting errors for an integrated energy system (IES), this study proposes a dynamic time-scale scheduling strategy based on long short-term memory (LSTM) and multiple load forecasting errors. This strategy dynamically selects a hybrid timescale which is suitable for a variety of energies for each month. This is obtained by combining the mean absolute percentage error (MAPE) curve of the load forecasting with the error restriction requirements of the dispatcher. Based on the day-ahead scheduling plan, the output of the partial equipment is selectively adjusted at each time-scale to realize multi-energy collaborative optimization and gives full play to the comprehensive advantages of the IES. This is achieved by considering the differences in the response speed for each piece of equipment within the intra-day scheduling. This study uses the IES as an example, and it dynamically determines the time scale of the energy monthly. In addition, this investigation presents a detailed analysis of the output plan of the key equipment to demonstrate the necessity and the advantages of the strategy.

The close proximity and the necessity of coordination between multiple high-voltage direct currents (HVDCs) raise the issue of grid partitioning in multi-infeed HVDC systems. A multi-objective partition strategy is proposed in this paper. Several types of relationships to be coordinated and complemented are analyzed and formulated using quantitative indices. According to the graph theory, the HVDC partition is transformed into a graph-cut problem and solved via the spectral clustering algorithm. Finally, the proposed method is validated for a practical multi-HVDC grid, confirming its feasibility and effectiveness.

Fast charging stations play an important role in the use of electric vehicles (EV) and significantly affect the distribution network owing to the fluctuation of their power. For exploiting the rapid adjustment feature of the energy-storage system (ESS), a configuration method of the ESS for EV fast charging stations is proposed in this paper, which considers the fluctuation of the wind power as well as the characteristics of the charging load. The configuration of the ESS can not only mitigate the effects of fast charging stations on the connected distribution network but also improve its economic efficiency. First, the scenario method is adopted to model the wind power in the distribution network, and according to the characteristics of the EV and the driving probability, the charging demand of each station is calculated. Then, considering factors such as the investment cost, maintenance cost, discharging benefit, and wind curtailment cost, the ESS configuration model of the distribution network is set up, which takes the optimal total costs of the ESS for EV fast charging stations within its lifecycle as an objective. Finally, General Algebraic Modelling System (GAMS) is used to linearize and solve the proposed model. A simulation on an improved IEEE-69 bus system verifies the feasibility and economic efficiency of the proposed model.

With the integration of renewable energy resources, the inertia of power systems significantly reduces, thereby making the system sensitive to operational disturbances. A disturbance-based method is presented herein to estimate inertia, uncovering the influence of renewables on system-resilient operations. The Gaussian process regression method is then used to predict the power system trajectory after disturbance. Extensive tests demonstrate the data-driven method mathematically estimates the inertia of the system as well as predicts the dynamics operations of power grids subject to disturbances. Numerical results also offer insights into the enhancement of system resilience by strategically designing the inertia of power systems.

Owing to increasing environmental concerns and resource scarcity, integrated energy system shave become widely used in communities. Rural energy systems, as one of the important links of the energy network in China, suffer from low energy efficiency and weak infrastructure. Therefore, it is particularly important to increase the proportion of electricity consumption and build an integrated energy system for rural electrification in China (IESREIC) with a rural distribution network as the core, in line with national conditions. In this study, by analyzing the Chinese regional differences and natural resource endowments, the development characteristics of the IESREIC are summarized. Then, according to the existing rural energy problems, key technologies are proposed for the IESREIC, such as those for planning and operation, value sharing, infrastructure, and a management and control platform. Finally, IESREIC demonstration projects and business models are introduced for agricultural production, rural industrial systems, and rural life. The purpose is to propose research concepts for the IESREIC, provide suggestions for the development of rural energy, and provide a reference for the construction of rural energy systems in countries with characteristics similar to those of China.

Electric system planning with high variable renewable energy (VRE) penetration levels has attracted great attention world-wide. Electricity production of VRE highly depends on the weather conditions and thus involves large variability, uncertainty, and low-capacity credit. This gives rise to significant challenges for power system planning. Currently, many solutions are proposed to address the issue of operational flexibility inadequacy, including flexibility retrofit of thermal units, inter-regional transmission, electricity energy storage, and demand response (DR). Evidently, the performance and the cost of various solutions are different. It is relevant to explore the optimal portfolio to satisfy the flexibility requirement for a renewable dominated system and the role of each flexibility source. In this study, the value of diverse DR flexibilities was examined and a stochastic investment planning model considering DR is proposed. Two types of DRs, namely interrupted DR and transferred DR, were modeled. Chronological load and renewable generation curves with 8760 hours within a whole year were reduced to 4 weekly scenarios to accelerate the optimization. Clustered unit commitment constraints for accommodating variability of renewables were incorporated. Case studies based on IEEE RTS-96 system are reported to demonstrate the effectiveness of the proposed method and the DR potential to avoid energy storage investment.

Development of the medium and low voltage DC distribution system is of great significance to a regional transmission of electric energy, increasing a penetration rate of new energy, and enhancing a safety of the operation of the AC/DC interconnected grid. This paper first summarizes the medium and low voltage DC distribution system schemes and plans put forward by many countries, and then elaborate status of under-construction medium and low voltage DC distribution system project cases in China. Based on these project cases, this paper analyzes key issues involved in the medium and low voltage DC distribution system topologies, equipment, operation control technologies and DC fault protections, in order to provide theoretical and technical reference for future medium and low voltage DC distribution system-related projects. Finally, this paper combines a current China research status to summarize and give a prediction about the future research direction of medium and low voltage DC distribution system, which can provide reference for the research of medium and low voltage DC distribution system.

Distributed energy resources have been proven to be an effective and promising solution to enhance power system resilience and improve household-level reliability. In this paper, we propose a method to evaluate the reliability value of a photovoltaic (PV) energy system with a battery storage system (BSS) by considering the probability of grid outages causing household blackouts. Considering this reliability value, which is the economic profit and capital cost of PV+BSS, a simple formula is derived to calculate the optimal planning strategy. This strategy can provide household-level customers with a simple and straightforward expression for invested PV+BSS capacity. Case studies on 600 households located in eight zones of the US for the period of 2006 to 2015 demonstrate that adding the reliability value to economic profit allows households to invest in a larger PV+BSS and avoid loss of load caused by blackouts. Owing to the differences in blackout hours, households from the 8 zones express distinct willingness to install PV+BSS. The greater the probability of blackout, the greater revenue that household can get from the PV+BSS. The simulation example shows that the planning strategy obtained by proposed model has good economy in the actual operation and able to reduce the economic risk of power failure of the household users. This model can provide household with an easy and straightforward investment strategy of PV+BSS capacity.

To promote the utilization of renewable energy, such as photovoltaics, this paper proposes an optimal flexibility dispatch method for demand-side resources (DSR) based on the Stackelberg game theory. First, the concept of the generalized DSR is analyzed and flexibility models for various DSR are constructed. Second, owing to the characteristics of small capacity but large-scale, an outer approximation is proposed to describe the aggregate flexibility of DSR. Then, the optimal flexibility dispatch model of DSR based on the Stackelberg game is established and a decentralized solution algorithm is designed to obtain the Stackelberg equilibrium. Finally, the actual data are utilized for the case study and the results show that, compared to the traditional centralized optimization method, the proposed optimal flexibility dispatch method can not only reduce the net load variability of the DSR aggregator but is beneficial for all DSR owners, which is more suitable for practical applications.

Predicting wind power generation over the medium and long term is helpful for dispatching departments, as it aids in constructing generation plans and electricity market transactions. This study presents a monthly wind power generation forecasting method based on a climate model and long short-term memory (LSTM) neural network. A nonlinear mapping model is established between the meteorological elements and wind power monthly utilization hours. After considering the meteorological data (as predicted for the future) and new installed capacity planning, the monthly wind power generation forecast results are output. A case study shows the effectiveness of the prediction method.

Distribution networks in China and several other countries are predominantly neutral inefficiently grounding systems (NIGSs), and more than 80% of the faults in distribution networks are single-phase-to-ground (SPG) faults. Because of the weak fault current and imperfect monitoring equipment configurations, methods used to determine the faulty line sections with SPG faults in NIGSs are ineffective. The development and application of distribution-level phasor measurement units (PMUs) provide further comprehensive fault information for fault diagnosis in a distribution network. When an SPG fault occurs, the transient energy of the faulted line section tends to be higher than the sum of the transient energies of other line sections. In this regard, transient energy-based fault location algorithms appear to be a promising resolution. In this study, a field test plan was designed and implemented for a 10 kV distribution network. The test results demonstrate the effectiveness of the transient energy-based SPG location method in practical distribution networks.

Interconnected power systems that link several countries and fully utilize their individual resources in a complementary manner are becoming increasingly important. As these systems enhance accommodation of renewable energy, they also represent a move toward low-carbon and low-emission power systems. In this paper, a low-carbon dispatch model is proposed to coordinate the generation output between several countries where the carbon emission constraint is a priority. An adjustable robust optimization approach is used to find the optimal solution under the worst-case scenario to address the uncertainties associated with renewable energy resources. A specific constraint is that the area control error for each country should be self-balanced. Furthermore, a reformation using participation factors is presented to simplify the proposed robust dispatch model. Simulation results for practical interconnected power systems in northeast Asian countries verify the effectiveness of the proposed model.

To ensure the safety and stability of power grids with photovoltaic (PV) generation integration, it is necessary to predict the output performance of PV modules under varying operating conditions. In this paper, an improved artificial neural network (ANN) method is proposed to predict the electrical characteristics of a PV module by combining several neural networks under different environmental conditions. To study the dependence of the output performance on the solar irradiance and temperature, the proposed neural network model is composed of four neural networks, it called multi- neural network (MANN). Each neural network consists of three layers, in which the input is solar radiation, and the module temperature and output are five physical parameters of the single diode model. The experimental data were divided into four groups and used for training the neural networks. The electrical properties of PV modules, including I–V curves, P– V curves, and normalized root mean square error, were obtained and discussed. The effectiveness and accuracy of this method is verified by the experimental data for different types of PV modules. Compared with the traditional single-ANN (SANN) method, the proposed method shows better accuracy under different operating conditions.

For the implementation of power market in China, medium- and long-term security checks are essential for bilateral transactions, of which the electricity quantity that constitutes the generation feasible region (GFR) is the target. However, uncertainties from load forecasting errors and transmission contingencies are threats to medium- and long-term electricity trading in terms of their influences on the GFR. In this paper, we present a graphic distortion pattern in a typical three- generator system using the Monte Carlo method and projection theory based on security constrained economic dispatch. The underlying potential risk to GFR from uncertainties is clearly visualized, and their impact characteristics are discussed. A case study on detailed GFR distortion was included to demonstrate the effectiveness of this visualization model. The result implies that a small uncertainty could distort the GFR to a remarkable extent and that different line-contingency precipitates disparate the GFR distortion patterns, thereby eliciting great emphasis on load forecasting and line reliability in electricity transactions.

Due to the shortage of fossil energy and the pollution caused by combustion of fossil fuels, the proportion of renewable energy in power systems is gradually increasing across the world. Accordingly, the capacity of power systems to accommodate renewable energy must be improved. However, integration of a large amount of renewable energy into power grids may result in network congestion. Hence, in this study, optimal transmission switching (OTS) is considered as an important method of accommodating renewable energy. It is incorporated into the operation of a power grid along with deep peak regulation of thermal power units, forming an interactive mode of coordinated operation of source and network. A stochastic unit commitment model considering deep peak regulation and OTS is established, and the role of OTS in promoting the accommodation of renewable energy is analyzed quantitatively. The results of case studies involving the IEEE 30-bus system demonstrate that OTS can enable utilization of the potential of deep peak regulation and facilitate the accommodation of renewable energy.

Congo River has abundant hydropower resources, and large-scale cascade power stations, such as the Grand Inga, can be constructed in downstream locations. However, the fragile economic foundations of the Democratic Republic of the Congo and neighboring Central African countries, and the small-scale regional power consumption market prohibit the implementation of large-scale hydropower projects. As the high-voltage, long-distance power transmission technology matures, hydropower from the Grand Inga can be delivered to load centers in other regions of Africa. This study establishes a 6 dimensional comprehensive assessment model using the best–worst method to evaluate large-scale, long-distance, cross-border power interconnection projects.The model is applied to evaluate all the candidate inter-regional power delivery schemes of the Inga III hydropower station, and the evaluation results can effectively help investment institutions and policy makers in policy making and potential market targeting.

The analysis of a supervision environment is the first step for a company to enter the new electricity market. Transmission and distribution assets are the main investment targets of a company. The overseas power market belongs to the regulated industry; whether it is a stock M&A project or a green land bidding project, the regulatory environment determines the assets. The level of return and investment risk that guides the operation strategy of existing overseas assets, has a significant impact on the investment and operations of international companies. A comprehensive and rapid assessment of the regulatory environment can help the project teams of international companies understand the macroenvironment of the target electricity market within a short period, quickly identify investment risks, qualitatively analyze the return level of the underlying assets, shorten the decision time, capture investment opportunities, and enhance the team. Efficiency and quality of work are factors of great importance.

Partial discharge (PD) detection is an effective means of discovering insulation faults in gas-insulated switchgear (GIS). One of the most extensively used methods in PD detection has historically been the ultrahigh frequency (UHF) method. This study evaluates the chromatic processing methodology and its key factors for feature extraction of UHF signals in GIS. Three types of artificial defects are installed in the GIS tank at 0°, 90°, and 180°, respectively. The features of the UHF signals are extracted in the chromatic space, and PD discrimination of the defects is achieved. The influences of processors are studied before the feature selections are suggested. The time-stepping method is proposed to determine the rules of UHF signal frequency characteristics that vary with time. Finally, the process and options of the chromatics-inspired methodology are summarized.

Owing to the large-scale grid connection of new energy sources, several installed power electronic devices introduce sub-/supersynchronous inter-harmonics into power signals, resulting in the frequent occurrence of subsynchronous oscillations (SSOs). The SSOs may cause significant harm to generator sets and power systems; thus, online monitoring and accurate alarms for power systems are crucial for their safe and stable operation. Phasor measurement units (PMUs) can realize the dynamic real-time monitoring of power systems. Based on PMU phasor measurements, this study proposes a method for SSO online monitoring and alarm implementation for the main station of a PMU. First, fast Fourier transform frequency spectrum analysis is performed on PMU current phasor amplitude data to obtain subsynchronous frequency components. Second, the support vector machine learning algorithm is trained to obtain the amplitude threshold and subsequently filter out safe components and retain harmful ones. Finally, the adaptive duration threshold is determined according to frequency susceptibility, amplitude attenuation, and energy accumulation to decide whether to transmit an alarm signal. Experiments based on field data verify the effectiveness of the proposed method.

The growing demand for electricity in large Brazilian cities and the distance to the region with the largest energy production have encouraged the construction of transmission lines thousands of kilometers long, crossing several states of the federation. Therefore, the heterogeneity of requirements in federal, state and district environmental laws tend to lead to uncertainty for the investor regarding procedures and investments necessary for the completion of the project, as well as the time that the requirements will take to be fulfilled. In the present study, we identify and compare the criteria used by the various environmental licensing agencies for classifying transmission system projects in the different procedures (simplified and ordinary) of environmental licensing. It was possible to expose the differences and demonstrate some inconsistencies in the legislation of some Brazilian states. In particular, we note an absence of proportionality between the licensing requirements and the expected environmental impacts for projects on the physical, biological and social environments. Additionally, it was identified subjectivity in the requirement for social participation through public hearings, demanded by the legislation for the projects classified in the ordinary procedure.

In China, regions with abundant wind energy resources are generally located at the end of power grids. The power grid architecture in these regions is typically not sufficiently strong, and the energy structure is relatively simple. Thus, connecting large-capacity wind power units complicates the peak load regulation and stable operation of the power grids in these regions. Most wind turbines use power electronic converter technology, which affects the safety and stability of the power grid differently compared with conventional synchronous generators. Furthermore, fluctuations in wind power cause fluctuations in the output of wind farms, making it difficult to create and implement suitable power generation plans for wind farms. The generation technology and grid connection scheme for wind power and conventional thermal power generation differ considerably. Moreover, the active and reactive power control abilities of wind turbines are weaker than those of thermal power units, necessitating additional equipment to control wind turbines. Hence, to address the aforementioned issues with large-scale wind power generation, this study analyzes the differences between the grid connection and collection strategies for wind power bases and thermal power plants. Based on this analysis, the differences in the power control modes of wind power and thermal power are further investigated. Finally, the stability of different control modes is analyzed through simulation. The findings can be beneficial for the planning and development of large-scale wind power generation farms.

The inertia response and primary frequency regulation capability of synchronous grids are declining owing to the increasing penetration of inverter-based resources. The fast frequency response (FFR) of inverter-based resources is an important mitigation option for maintaining grid security under the conditions of low inertia and insufficient primary frequency response capability. However, the understanding and technical characteristics of the FFR of inverter-based resources are still unclear. Aiming at solving the aforementioned problems, this paper proposes a definition for FFR based on the impact mechanism of FFR on system frequency. The performance requirements of FFR are clarified. Then, the effects of FFR on system frequency characteristics are further analyzed based on steady-state frequency deviation, the initial rate of change of frequency, and the maximum transient frequency deviation. Finally, the system requirements for FFR and its application effects are verified by simulating an actual bulk power grid, providing technical support for subsequent engineering application.

The bidding strategies of power suppliers to maximize their interests is of great importance. The proposed bi-level optimization model with coalitions of power suppliers takes restraint factors into consideration, such as operating cost reduction, potential cooperation, other competitors’ bidding behavior, and network constraints. The upper model describes the coalition relationship between suppliers, and the lower model represents the independent system operator’s optimization without network loss (WNL) or considering network loss (CNL). Then, a novel algorithm, the evolutionary game theory algorithm (EGA) based on a hybrid particle swarm optimization and improved firefly algorithm (HPSOIFA), is proposed to solve the bi-level optimization model. The bidding behavior of the power suppliers in equilibrium with a dynamic power market is encoded as one species, with the EGA automatically predicting a plausible adaptation process for the others. Individual behavior changes are employed by the HPSOIFA to enhance the ability of global exploration and local exploitation. A novel improved firefly algorithm (IFA) is combined with a chaotic sequence theory to escape from the local optimum. In addition, the Shapley value is applied to the profit distribution of power suppliers’ cooperation. The simulation, adopting the standard IEEE-30 bus system, demonstrates the effectiveness of the proposed method for solving the bi-level optimization problem

Africa is embracing new opportunities featured with industrialization, urbanization and regionalization. Based on co-development of ‘Electricity, Mining, Metallurgy, Industry and Trade’ and grids interconnection proposed by Global Energy Interconnection Development and Cooperation Organization (GEIDCO), the high-quality hydropower resource of the Congo River can be exploited in large scale under the wide-range interconnected framework of African Energy Interconnection (AEI), forging a new engine for Africa economy. The transmission distance of the Congo River hydropower reaches 6,000 km at its farthest end in North Africa, which brings forth challenges to economics of proposed projects. Under this novel continental energy interconnection scheme in Africa, economics of those projects have not yet been in detail studied. This paper has implemented China’s mature engineering experiences and analytical tools of UHVDC project planning into the AEI structure, through exploring the economic behavior of ultra-long distance UHVDC projects in the scope of conductor selection in the Congo River hydropower transmission for the first time, and has provided concerned parties with a technical and analytical results of their economics comparison. This paper has chosen the D.R. Congo - Guinea ±800 kV UHVDC project as a typical example. Its preliminary system planning is introduced and three types of conductor are selected for scheme comparison. Later in this paper, the transmission loss, total investment and equivalent annual cost of the project have been calculated and analyzed. In the final part, sensitivity analysis results of the annual cost to utilization hours, transmission loss, loss tariff and construction cost has been provided

Recently, power electronic transformers (PETs) have received widespread attention owing to their flexible networking, diverse operating modes, and abundant control objects. In this study, we established a steady-state model of PETs and applied it to the power flow calculation of AC–DC hybrid systems with PETs, considering the topology, power balance, loss, and control characteristics of multi-port PETs. To address new problems caused by the introduction of the PET port and control equations to the power flow calculation, this study proposes an iterative method of AC–DC mixed power flow decoupling based on step optimization, which can achieve AC–DC decoupling and effectively improve convergence. The results show that the proposed algorithm improves the iterative method and overcomes the overcorrection and initial value sensitivity problems of conventional iterative algorithms.

A photovoltaic array is environmentally friendly and a source of unlimited energy generation. However, it is presently a costlier energy generation system than other non-renewable energy sources. The main reasons are seasonal variations and continuously changing weather conditions, which affect the amount of solar energy received by the solar panels. In addition, the non-linear characteristics of the voltage and current outputs along with the operating environment temperature and variation in the solar radiation decrease the energy conversion capability of the photovoltaic arrays. To address this problem, the global maxima of the PV arrays can be tracked using a maximum power point tracking algorithm (MPPT) and the operating point of the photovoltaic system can be forced to its optimum value. This technique increases the efficiency of the photovoltaic array and minimizes the cost of the system by reducing the number of solar modules required to obtain the desired power. However, the tracking algorithms are not equally effective in all areas of application. Therefore, selecting the correct MPPT is very critical. This paper presents a detailed review and comparison of the MPPT techniques for photovoltaic systems, with consideration of the following key parameters: photovoltaic array dependence, type of system (analog or digital), need for periodic tuning, convergence speed, complexity of the system, global maxima, implemented capacity, and sensed parameter(s). In addition, based on real meteorological data (irradiance and temperature at a site located in Addis Ababa, Ethiopia), a simulation is performed to evaluate the performance of tracking algorithms suitable for the application being studied. Finally, the study clearly validates the considerable energy saving achieved by using these algorithms.

With the rapid development of technologies such as big data and cloud computing, data communication and data computing in the form of exponential growth have led to a large amount of energy consumption in data centers. Globally, data centers will become the world’s largest users of energy consumption, with the ratio rising from 3% in 2017 to 4.5% in 2025. Due to its unique climate and energy-saving advantages, the high-latitude area in the Pan-Arctic region has gradually become a hotspot for data center site selection in recent years. In order to predict and analyze the future energy consumption and carbon emissions of global data centers, this paper presents a new method based on global data center traffic and power usage effectiveness (PUE) for energy consumption prediction. Firstly, global data center traffic growth is predicted based on the Cisco’s research. Secondly, the dynamic global average PUE and the high latitude PUE based on Romonet simulation model are obtained, and then global data center energy consumption with two different scenarios, the decentralized scenario and the centralized scenario, is analyzed quantitatively via the polynomial fitting method. The simulation results show that, in 2030, the global data center energy consumption and carbon emissions are reduced by about 301 billion kWh and 720 million tons CO2 in the centralized scenario compared with that of the decentralized scenario, which confirms that the establishment of data centers in the Pan-Arctic region in the future can effectively relief the climate change and energy problems. This study provides support for global energy consumption prediction, and guidance for the layout of future global data centers from the perspective of energy consumption. Moreover, it provides support of the feasibility of the integration of energy and information networks under the Global Energy Interconnection conception.

Due to low investment cost and high reliability, a new scheme called DR-HVDC (Diode Rectifier based HVDC) transmission was recently proposed for grid integration of large offshore wind farms. However, in this scheme, the application of conventional control strategies for stability operation face several challenges due to the uncontrollability of the DR. In this paper, a coordinated control strategy of offshore wind farms using the DR-HVDC transmission technology to connect with the onshore grid, is investigated. A novel coordinated control strategy for DR-HVDC is proposed based on the analysis of the DC current control ability of the full-bridge-based modular multilevel converter (FB-MMC) at the onshore station and the input and output characteristics of the diode rectifier at the offshore. Considering the characteristics of operation stability and decoupling between reactive power and active power, a simplified design based on double-loop droop control for offshore AC voltage is proposed after power flow and voltage–current (I–V) characteristics of the offshore wind farm being analyzed. Furthermore, the impact of onshore AC fault to offshore wind farm is analyzed, and a fast fault detection and protection strategy without relying on communication is proposed. Case studies carried out by PSCAD/EMTDC verify the effectiveness of the proposed control strategy for the start up, power fluctuation, and onshore and offshore fault conditions.

A hybrid of line commutated converters (LCCs) and modular multi-level converters (MMCs) can provide the advantages of both the technologies. However, the commutation failure still exists if the LCC operates as an inverter in a hybrid LCC/MMC system. In this paper, the system behavior during a commutation failure is investigated. Both half- bridge and full-bridge MMCs are considered. Control strategies are examined through simulations conducted in PSCAD/ EMTDC. Additionally, commutation failure protection strategies for multi-terminal hybrid LCC/MMC systems with AC and DC circuit breakers are studied. This paper can contribute to the protection design of future hybrid LCC/MMC systems against commutation failures.

In many regions, international power system interconnections provide economic, energy-security, environmental, and technical benefits. In contrast, such interconnections remain scarce in Northeast Asia. In 2016, after approving a joint memorandum of understanding between major electric power companies from China, Japan, South Korea, and Russia, related initiatives regained momentum in the region. Nevertheless, the corresponding developments in Japan remain limited, mainly owing to the lack of involvement of Japanese electric power companies. This study represents a pioneering attempt to provide an economic assessment based on power exchange prices of a power system interconnection between Japan and South Korea regarding the competitiveness of electric power companies in terms of competitive business segments and strategic consequences. We found that although the position of Japanese generators may slightly deteriorate, that of the supply segment would substantially improve, thus suggesting that more opportunities than threats are derived from the interconnection. This promising outcome may foster the adoption of an interconnection with South Korea considering the positive economic and business perspectives in Japan. Furthermore, realizing the interconnection may improve the energy security and air quality in the region.

In the process of large-scale, grid-connected wind power operations, it is important to establish an accurate probability distribution model for wind farm fluctuations. In this study, a wind power fluctuation modeling method is proposed based on the method of moving average and adaptive nonparametric kernel density estimation (NPKDE) method. Firstly, the method of moving average is used to reduce the fluctuation of the sampling wind power component, and the probability characteristics of the modeling are then determined based on the NPKDE. Secondly, the model is improved adaptively, and is then solved by using constraint-order optimization. The simulation results show that this method has a better accuracy and applicability compared with the modeling method based on traditional parameter estimation, and solves the local adaptation problem of traditional NPKDE.

Power transmission across the sea is an important part of global energy interconnection (GEI). To support the construction of GEI and to serve the needs of future clean energy trans-sea transportation and offshore wind power development, this study a) analyzes the requirements of the GEI backbone network pertaining to direct current (DC) submarine cable technology, and b) defines the key technical and economic indices of ultrahigh-voltage direct current (UHVDC) submarine cable based on theoretical computations. The research is based on the thermoelectric coupling model and the finite element method. It is shown that the dielectric strength of the insulating materials of the ± 800 kV ~±1100 kV/ 4000 MW ~ 12000 MW UHVDC submarine cable (extrusion insulation) should be not less than 43 ~ 65 kV/mm, while the heat resistance is not less than 110 °C. As the cost of submarine cable is 5 ~ 10 times higher than that of the overhead line, the project investment need to be decreased to a level within the economical carrying capacity to guarantee extensive applicability of the HVDC submarine cable technology.

Based on the energy storage cloud platform architecture, this study considers the extensive configuration of energy storage devices and the future large-scale application of electric vehicles at the customer side to build a new mode of smart power consumption with a flexible interaction, smooth the peak/valley difference of the load side power, and improve energy efficiency. A plug and play device for customer-side energy storage and an internet-based energy storage cloud platform are developed herein to build a new intelligent power consumption mode with a flexible interaction suitable for ordinary customers. Based on the load perception of the power grid, this study aims to investigate the operating state and service life of distributed energy storage devices. By selecting an integrated optimal control scheme, this study designs a kind of energy optimization and deployment strategy for stratified partition to reduce the operating cost of the energy storage device on the client side. The effectiveness of the system and the control strategy is verified through the Suzhou client-side distributed energy storage demonstration project.

The European power grid is one of the largest regional interconnected power grids in the world. It realizes a multinational grid operation, which is rare. The total installed capacity of the European power grid is the largest throughout the world. In addition, the integration and utilization of renewable energy in this grid is a great benchmark for other countries and can help promote energy transformation and achieve a high proportion of renewable energy consumption. Based on the analysis of the existing status of the European interconnected power grid and the development history of this power grid, this paper summarizes four key development stages of the European power grid. In addition, the characteristics of each stage and the development prospect of the European power grid are analyzed. On this basis, this paper gives suggestions for the development and construction of China’s energy internet; this can provide valuable reference for further studies on China’s energy internet.

Large-scale integration of wind power into a power system introduces uncertainties to its operation and planning, making the power system operation scenario highly diversified and variable. In conventional power system planning, some key operation modes and most critical scenarios are typically analyzed to identify the weak and high-risk points in grid operation. While these scenarios may not follow traditional empirical patterns due to the introduction of large-scale wind power. In this paper, we propose a weighted clustering method to quickly identify a system’s extreme operation scenarios by considering the temporal variations and correlations between wind power and load to evaluate the stability and security for system planning. Specifically, based on an annual time-series data of wind power and load, a combined weighted clustering method is used to pick the typical scenarios of power grid operation, and the edge operation points far from the clustering center are extracted as the extreme scenarios. The contribution of fluctuations and capacities of different wind farms and loads to extreme scenarios are considered in the clustering process, to further improve the efficiency and rationality of the extreme-scenario extraction. A set of case studies was used to verify the performance of the method, providing an intuitive understanding of the extreme scenario variety under wind power integration.

Solar photovoltaic (PV) power represents one of the most promising future sources of energy in the world. Considered the cleanest form of energy, extensive research is being undertaken to widen its use. Notably, mega projects are being considered for installation in the Middle East and North Africa (MENA) region because of its high solar potential, with hopes of eventually feeding Europe from the PV electricity generated in this region and transported through high voltage direct current (DC) lines. However, current implementation of PV systems has shown that their reliability and efficiency depend upon surrounding environmental factors, such as the ambient temperature, wind, and rainfall, as well as soiling, pollution, and aging. The aim of this study was to investigate, through experimental tests, the effects of such factors on the power output of a grid connected PV station. The results showed that the output power and efficiency are deeply affected by various environmental factors, which are weather dependent. These findings may help us develop appropriate solutions to overcome these drawbacks. Keywords: Grid connected PV, Power losses, Soiling, Dust, Aging

The amount of solar PV installed capacity has steadily increased to 44.5 GW at the end of FY2017, since the introduction of the Feed in Tariff (FiT) to Japan in 2012. On the other hand, since the first curtailment of solar PV was conducted on October 13th, 2018 in the Kyushu area, the curtailment has been frequently executed including wind power after that. In this study, cross-regional interconnector and pumped hydro energy storage (PHES) are focused on mitigating curtailment.In Japan, there are 9 electric power areas which connected each other by cross-regional interconnectors. According to the historical operation, cross-regional interconnectors were secured as emergency flexible measures, but after the implicit auction was started from October 2018, it is used on merit order. Regarding a PHES in Japan, they have been built with nuclear power plants for several decades. Because the output of nuclear power generation is constant, so the PHES is used to absorb the surplus at nighttime when the demand declines. All nuclear power plants in Japan have been shut down after the accident at the Fukushima Daiichi Nuclear Power Plant following the Great East Japan Earthquake that occurred on March 11th, 2011. There are several nuclear power plants that have been restarted (9 reactors, as of August 2019).In this study, the amount of curtailment for solar PV in the Kyushu area is sent to the Chugoku area using the cross-regional interconnector (Kanmon line). Then, the PHES in the Chugoku area is pumping with low price. Because the spot price in the market is low when the curtailment is executed. After that, the PHES is generating at night with high price when the solar PV is not generating. It makes a profit by the deference for the cost of pumping and the revenue of generating by the PHES. As a calculation result, for one week from May 2nd to 8th, 2019, a profit becomes 152.2 million JPY (about 1.22 million EUR). For this purpose, it is necessary to raise the operation capacity of the cross-regional interconnector up to the rated capacity with the frequency control function of solar PV instead of the capacity to keep frequency in the event of an accident. This will allow the further introduction of solar PV in Japan. Keywords: Solar PV, Cross-regional interconnector, Pumped hydro energy storage (PHES), Curtailment

When a maintenance and operations ship is berthing, there is a chance the ship may collide into the wind turbine. When these ships collide into wind turbine structures, this can result in significant changes to the foundation and structure of the wind turbine. In this paper, the structural load of a 4 MW offshore wind turbine was analyzed during a collision with an operations and maintenance ship. The variations in the wind speeds on hub height, waves, and the sea currents were measured. The dynamic simulation of the wind turbine was carried out using the test data as the input parameters. As a result, the load condition of the turbine without a collision was obtained. Finally, the measured turbine load was compared with the simulation results. This study shows that the collision of the operation and the maintenance ship increases the bending moments at the tower’s bottom and the blade’s roots. Keywords: Offshore wind turbine, Ship collision, Offshore experiment, Wind-wave-current coupling filed

In order to promote the development of the Internet of Things (loT), there has been an increase in the coverage of the customer electric information acquisition system (CEIAS). The traditional fault location method for the distribution network only considers the information reported by the Feeder Terminal Unit (FTU) and the fault tolerance rate is low when the information is omitted or misreported. Therefore, this study considers the influence of the distributed generations (DGs) for the distribution network. This takes the CEIAS as a redundant information source and solves the model by applying a binary particle swarm optimization algorithm (BPSO). The improved Dempster/S-hafer evidence theory (D-S evidence theory) is used for evidence fusion to achieve the fault section location for the distribution network. An example is provided to verify that the proposed method can achieve single or multiple fault locations with a higher fault tolerance. Keywords: Internet of Things, Multi-source information, D-S evidence theory, Binary particle swarm optimization algorithm, Fault tolerance

Various methods including photocatalysis have been used for degradation and removal of phenolic compounds, which classified as hazardous materials in the environment. Nanomaterials exhibited significant advantages for photocatalytic degradation of phenolic compounds compared to the conventional oxidation approaches such as traditional biological and physical methods. In this study, zirconia (ZrO2)/graphitic carbon nitride (g-C3N4) nanocomposites were successfully synthesized using ultrasonication method and used for photodegradation of 4-chlorophenol (4-CP) in water under visible light. The g-C3N4 nanosheets, ZrO2 nanoparticles (NPs), and ZrO2/g-C3N4 nanocomposite were characterized by N2 adsorption, X-ray diffraction (XRD), UV–vis diffuse reflectance spectroscopy (DRS), Fourier transform infrared spectroscopy (FT-IR), field emission scanning electron microscopy (FESEM), transmission electron microscope (TEM), photoelectrochemical (PEC) measurements, and photoluminescence spectroscopy (PL). The incorporation of ZrO2 NPs enhanced the surface area and light absorption capacity of pristine g-C3N4. The photocatalytic activity of ZrO2/g-C3N4 nanocomposite sample was evaluated by the degradation of 4-CP in aqueous medium. Results exhibited an increase in photocatalytic activity of ZrO2/g-C3N4 nanocomposite compared to unmodified ZrO2 NPs and pristine g-C3N4. In addition, reusability experiment of ZrO2/g-C3N4 nanocomposite for photo-catalytic degradation, as well as for 4-CP adsorption showed the ZrO2/g-C3N4 nanocomposites can be effectively used for several cycles.

The demand for fresh water is constantly increasing among all water users. Irrigation in Ethiopia consumes a large amount of water extracted from various sources. Hence, efficient water use and management are currently the major concerns in the country. Thus this paper aims to review the advancements, challenges, and opportunities regarding improving irrigation water use efficiency in Ethiopia. Irrigation in Ethiopia started in the 1950s with traditional irrigation systems. Now modern irrigation, including sprinkler and drip irrigation, is practiced in some parts of the country. The review showed that even though the farmers have practicing irrigation for a long time, still they cannot surpass subsistence farming. Furthermore, improvements in irrigation water use efficiency through proper scheduling and on-farm management are not satisfactory. The paper revealed the challenges that hinder water use efficiency improvement includes crop diseases, socio-economic factors, institution and policy-related issues, limitation in technical and human capacity, lack of agricultural input as well as market and nature-related factors. In the future, increased use of remote sensing techniques, more versatile sensors, simulation, and quantitative models are likely to be seen to improve water use efficiency. In most cases where water is saved as a result of the efficient use of technologies, the spare water ends up being used to expand the irrigation area, which results in an increased income for the household. Hence, to achieve net water savings, water-efficient technologies and practices need to be used in combination with other measures such as incentives for conservation and proper use. Besides, appropriate regulations should be set that limit water allocation and usage. The government and partners should allocate resources for capacity building of farmers regarding irrigation, which in extension will lead to enhancement in WUE.

The water management in various countries of the world provides a comprehensive understanding of the international movement on healthy watershed management. Watershed characteristics including River basin management in the UK, eco-health watershed management in Canada, sustainable water management in Korea, integrated watershed management in Japan, and healthy watershed management in the US. have been examined in this review. Pioneering countries utilize green infrastructural applications to improve their resilience against climate change by adopting adaptive solutions and mitigating pollution sources. This paper includes an overview of the implementation of green infrastructure exemplified by bioretention in urban development and ecosystem maintenance. The good engineering practice for bioretention was established by applying data collected from other research. Biomantle and semi-direct injection of storm water are the two methods for sustaining bioretention functionalities for peak flow reduction and soil stability enhancement. Maximum pollutants reduction efficiencies by bioretention were reported in the past research, including 99% of phosphorus, 82% of nitrate, 92% of heavy metals, and 96% of suspended solid. Lastly, a conclusive benefit analysis of green infrastructure from environmental, economic, and social perspectives was conducted.

Development within the energy sector is notably limited by scarce water resources in the energy bases of northwest China. Analyzing changes to the water consumption within the energy sector and the driving forces behind these changes offers an important way to understand the water-energy nexus and provide recommendation for the stakeholders. Taking the typical energy base of Ningxia in northwest China as an example, an empirical study is performed by analyzing changes in the direct and indirect water consumption of a regional energy sector using the input–output method. The driving forces of changes in the water consumption of the regional energy sector is identified using the LMDI (Logarithmic Mean Divisia Index) method. The results reveal the following: (1) In the period of 2011–2016, the water consumption of Ningxia's energy sector exhibited negative growth, and its direct and indirect water consumption decreased by 1.5914 million m3 and 11.664 million m3, respectively. (2) The increase in water-use efficiency in energy production was the primary driving force for the decrease in water consumption, followed by the decrease in total energy production. (3) Energy production restructuring from coal products to petroleum and electric power products resulted in an increase in water consumption. (4) The water-use stress faced by Ningxia's energy sector may be alleviated only by using alternative fuels to generate electric power whenever possible and continuously strengthening the popularization of water conservation techniques in Ningxia's energy sector. The above results provide scientific support for promoting sustainable economic and social development for typical energy bases in northwest China. Furthermore, the study proposes a method for quantitatively analyzing the contribution of multiple factors leading to changes in the water consumption within the energy sector.

Alarming level water pollution is a serious concern in heavily industrialized countries. The development of advanced waste water treatment techniques and their utilization is sought for effective removal of pollutants especially pharmaceutical and pesticide compounds (PPCs). Doped TiO2 nanomaterials mediated photocatalytic degradation of waste water has shown great potential in removing these complex organic pollutants. Improvement in properties of doped TiO2 nanomaterials resulted in the effective utilization of visible light and solar light as light source. Doped TiO2 nanomaterials show great potential to water and energy concerns by fulfilling two key features i.e., effective in removing pollutants which are persistent in nature and cost-effective energy consumption. In this context, doped TiO2 nanomaterials mediated waste water treatment process and its role in water energy nexus is briefly addressed. Application of doped TiO2 nanomaterials against PPCs under different light sources are also discussed in this review.

As the world's population grows, food and energy supply will be one of the most important challenges. Agriculture, as the most important food producer, is not only a consumer of water and energy but also a major supplier of energy. Consequently, a balance must be struck between the harvest and utilization of production resources and the amount of agricultural production. The UN's Third Millennium Goals are on the agenda of achieving sustainable long-term development of human societies and ensuring food, water, and energy availability for future generations. To accomplish these goals, researchers have developed numerous interdisciplinary and specialized frameworks and approaches to achieve a dynamic and optimal balance of production and resource utilization, one of which being water, energy, and food. The water, energy and food Nexus approach is an overall vision of sustainability that strives to balance the various goals, interests, and needs of people and the environment by quantifying water, energy and food relationships through qualitative and quantitative modeling as well as advancing research for Integrate modeling and management to deliver important sustainable development strategies in today's dynamic and complex world. Given the environmental and water crises that threaten the Iranian nation's food and energy security, water, energy, and food, Nexus management can bring about change and balance in different sectors, depending on the needs and participation of all stakeholders. In this paper, a novel model for the Nexus approach governance model using the multi-layer visionary is being developed for the Iranian region for the water and food crisis the country is facing today.

Nuclear power plants (NPP) installed on a river bank use once-through or recirculating wet cooling systems. While the quantitative assessment of mainly local evaporation of river water by a recirculating cooling system (RC) does not involve any major difficulty, the same cannot be said for the once-through cooling system (OTC) for which evaporation (called forced evaporation) occurs in the downstream aquatic environment. Our study applies an energy-balance temperature model to the Rhone River downstream from Lake Geneva. Our results show the approximate figure of 1.5 m3/MWh of forced evaporation per electricity produced (put forward in 2002 by EPRI and widely used in the literature) is debatable for setting a freshwater balance in a watershed because it does not consider the saltiness of the river downstream. The retention time of water bodies in the downstream freshwater stretch, the cross-section shape and regional weather characteristics appear to be key factors to take into account. In particular, for the three NPP with OTC systems installed along the French Rhone, we find an average forced evaporation between 0.3 and 0.7 m3/MWh of net electricity generated in the freshwater river stretch through to Arles between 1994 and 2015. These values are between three to eight times lower than those obtained for the evaporation generated by the plants with RC system installed along the river stretch.

The Global Energy Interconnection is an important strategic approach used to achieve efficient worldwide energy allocation. The idea of developing integrated power, information, and transportation networks provides increased power interconnection functionality and meaning, helps condense forces, and accelerates the integration of global infrastructure. Correspondingly, it is envisaged that it will become the trend of industrial technological development in the future. In consideration of the current trend of integrated development, this study evaluates a possible plan of coordinated development of fiber-optic and power networks in the Pan-Arctic region. Firstly, the backbone network architecture of Global Energy Interconnection is introduced and the importance of the Arctic energy backbone network is confirmed. The energy consumption and developmental trend of global data centers are then analyzed. Subsequently, the global network traffic is predicted and analyzed by means of a polynomial regression model. Finally, in combination with the current construction of fiber-optic networks in the Pan-Arctic region, the advantages of the integration of the fiber-optic and power networks in this region are clarified in justification of the decision for the development of a Global Energy Interconnection scheme. Keywords: Energy Interconnection, Data center, Network traffic, Integrated development of energy and information networks, Global Energy Interconnection

In order to meet the pressing demand for wide-area communication required by the Global Energy Interconnection (GEI), accelerating the construction of satellite-terrestrial integrated networks that can achieve network extension and seamless global coverage has become the focus of power communication technology development. In this study, we propose a satellite-terrestrial integrated network model that can support interconnection and interoperation on the IP layer between the satellite system and the terrestrial segment of the existing power communication system. First, the composition and function of the satellite-terrestrial collaborative network are explained. Then, the IP-based protocol stack is described, and a typical application experiment is conducted to illustrate the particular process of this protocol stack. Finally, a use case of IP interconnection that depends on GEO satellite communication is detailed. The experimental study has showed that the satellite-terrestrial collaborative network can efficiently support various IP applications for the GEI. Keywords: Global Energy Interconnection (GEI), Satellite-terrestrial integrated network, IP network

This paper focuses on pumped hydro energy storage (PHES) plants’ current operations after electricity system reforms and variable renewable energy (VRE) installations in Japan. PHES plants have historically been developed to create electricity demand at night in order to operate base load power plants, such as nuclear power plants, in stable conditions. Therefore, many PHES plants are located midway between nuclear power plants and large demand areas. However, all nuclear power plants had to - at least temporarily - shut down after the Great East Japan Earthquake followed by a nuclear accident at Fukushima Daiichi in 2011, and renewable energy power plants have been deployed rapidly after the introduction of a feed-in-tariff (FIT) scheme. Therefore, PHES plants are being used to mitigate fluctuations of VRE, especially in areas where renewable energy has been significantly installed. The daily highest capacity ratio of PHES plants in Kyushu area has recorded three times higher than it in the other areas where the past operating mode is still conducted. But those operations on PHES plants are simply followed as a dispatch rule of the Organization for Cross- regional Coordination of Transmission Operators (OCCTO), market-based operations have not been conducted enough yet. The market design shall be changed to harmonize VRE installation and PHES plants’ operations are necessary to make the transition from the past operating mode of PHES plants across Japan. Keywords: Pumped hydro energy storage plant, Nuclear power plant, Variable renewable energy, Solar photovoltaic, Market design

ASEAN is an interesting case study of regional power connectivity in Asia and the Pacific due to its geographic location and ongoing power connectivity within and beyond ASEAN. This paper reviews ASEAN’s power connectivity within ASEAN and between ASEAN and its neighbours (hereafter ASEAN connectivity). Through literature survey, it identifies challenges to the ASEAN connectivity from political, legal, economic and technical perspectives. Based on these analyses, it then explores what, how and when regional cooperation may be able to facilitate ASEAN power connectivity. Keywords: Power connectivity, ASEAN, China, ASEAN Power Grid, GMS