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The renewable-dominant hybrid generation systems (HGSs) are increasingly important to the electric power system worldwide. However, influenced by uncertain meteorological factors, the operational robustness of HGSs must be evaluated to inform the associated decision-making. Additionally, the main factors affecting the HGS's robustness should be urgently identified under deep uncertainties, as this provides valuable guidance for HGS capacity configuration. In this paper, a multivariate stochastic simulation method is developed and used to generate uncertain resource scenarios of runoff, photovoltaic power, and wind power. Subsequently, a long-term stochastic optimization model of the HGS is employed to derive the optimal operating rules. Finally, these operating rules are used to simulate the long-term operation of an HGS, and the results are used to evaluate the HGS's robustness and identify its main sensitivities. A clean energy base located in the Upper Yellow River Basin, China, is selected as a case study. The results show that the HGS achieves greater operational robustness than an individual hydropower system, and the robustness becomes weaker as the total capacity of photovoltaic and wind power increases. Additionally, the operational robustness of the HGS is found to be more sensitive to the total capacity than to the capacity ratio between photovoltaic and wind power. [ABSTRACT FROM AUTHOR]

Carbon peaking and carbon neutrality goals have proposed by many countries, including China. Meanwhile, China has also proposed the construction of a new-type electric power system with new energy as the main body, which will have great impacts on coal-fired power generation enterprises. The transformation of coal-fired power enterprises is imperative, and the evaluation of the organizational performance of coal-fired power enterprises is urgent, which can accurately determine the development status and even can find issues related to the transformation of coal-fired power enterprises. In this paper, a hybrid evaluation model is proposed based on the Variational Auto-Encoder algorithm and fuzzy comprehensive evaluation method improved by a vague set to comprehensively evaluate the organizational performance of coal-fired power enterprises. Eight coal-fired power enterprises in North China are selected for empirical analysis. The results show that the YC coal-fired power enterprise has the best organizational performance, while the NK coal-fired power enterprise has the worst organizational performance. Moreover, sensitivity and comparative analyses are carried out to verify the robustness of the evaluation result using the proposed hybrid method in this paper. This paper focuses on the organizational performance evaluation of coal-fired power enterprises, which can provide a reference for the smooth transformation and sustainable development of coal-fired power enterprises in the context of "Dual-Carbon" goals. [ABSTRACT FROM AUTHOR]

With the promotion of carbon peaking and carbon neutrality goals and the construction of renewable-dominated electric power systems, renewable energy will become the main power source of power systems in China. Therefore, ensuring frequency stability and system security will emerge as pivotal challenges in the future development process. Created by combining a Li-ion battery and a supercapacitor, a hybrid energy storage system (HESS), which possesses robust power regulation capabilities and rapid response capabilities, holds promise for supporting the frequency stability of power systems. In this context, the assessment of the economic viability of HESSs providing multitype frequency response services becomes a critical factor in their deployment and promotion. In this paper, an economic analysis approach for a Li-ion battery–supercapacitor HESS towards a multitype frequency response is presented. First, a multitype frequency response-oriented operational mode for the HESS is designed, outlining the roles and functions of the Li-ion battery and the supercapacitor in delivering distinct services. Moreover, building upon the analysis of the power trajectory of Li-ion batteries, a lifetime model for the HESS is proposed based on the rain-flow counting method. Furthermore, considering the competitive landscape for the HESS in the frequency regulation ancillary service market, a full lifecycle economic assessment model is proposed. Finally, case studies on actual power system frequency data and PJM market data are performed to verify the effectiveness of the proposed method, and the simulation results confirm that the HESS exhibits robust performance and a competitive advantage in providing multitype frequency response services. Additionally, it demonstrates commendable economic benefits, establishing its potential as a valuable contributor to frequency response services. [ABSTRACT FROM AUTHOR]

With the promotion of carbon peaking and carbon neutrality goals and the construction of renewable-dominated electric power systems, renewable energy will become the main power source of power systems in China. How to ensure the accommodation of renewable energy will also be the core issue in the future development process of renewable-dominated electric power systems. In this context, shared energy storage (SES), a novel business model combined with energy storage technologies and the sharing economy, has the potential to play an important role in renewable energy accommodation scenarios. This paper systematically organizes the application prospect, development status and key technologies of SES in the renewable energy accommodation scenario in the context of China, providing helpful references for the promotion of the business model. Firstly, a typical SES framework for renewable energy accommodation is described, and three basic forms of SES in this scenario are presented. Moreover, the application prospect of SES in the renewable energy accommodation scenario is quantitatively analyzed based on the renewable energy generation planning under the carbon peaking goal and the current guarantee mechanism of renewable energy accommodation. Furthermore, the rules for energy storage systems that provide the peak-regulation ancillary service in typical regions and provincial administrative regions in China are summarized, and the development status of SES in the renewable energy accommodation scenario is analyzed, combined with the actual market data. Finally, the key technologies to promote the further development of SES for renewable energy accommodation are presented. [ABSTRACT FROM AUTHOR]

With the reform of electric power system, major progress has been made in the construction of the electricity market. Electricity prices are a key influencing factor in the electricity market, and each participant trades electricity based on the price of electricity. Therefore, improving the accuracy of electricity price forecasts is important for every player in the electricity market. Prediction using single-layer neural networks has limited accuracy. Due to the high accuracy of machine learning in forecasting, the method of deep belief network is used to predict the price of electricity in the future. Real data from the U.S. PJM electricity market are used for simulation and compared with the prediction models of other neural networks. The results show that the prediction accuracy of the deep belief network model is higher, and the use of the deep belief network can provide an effective method for China's electricity sales companies to predict electricity prices. [ABSTRACT FROM AUTHOR]

Under the background of renewable-dominated electric power system construction, the penetration rate of low-carbon and renewable distributed generation (DG) in distribution network is increasing, which has changed the form and operation mode of the distribution network. To deal with the output fluctuation of high penetration DG in the distribution network operations, it is necessary to evaluate the acceptance capacity of DG. The correct evaluation can realize the secure, economic and low-carbon configuration of DG. In this paper, an evaluation method of acceptance capacity of DG in the distribution network considering the carbon emission is proposed. Firstly, a multi-objective evaluation model of acceptance capacity of DG is constructed with the objectives of minimizing carbon emission in the full life cycle, minimizing node voltage deviation and maximizing line capacity margin. Secondly, the improved non-dominated sorting genetic algorithm II (NSGA-II) is employed to solve the model to determine the Pareto optimal solutions of DG configuration. Then, the comprehensive index of acceptance capacity evaluation is obtained based on entropy weight method to decide the optimal compromise solution. Finally, an actual 55-bus distribution network in China is used to verify the effectiveness of the proposed method. The simulation results show that the proposed evaluation method can comprehensively obtain the optimal compromise solution considering the reliability, economy and carbon emission benefits of distribution network operation, which guides the DG configuration in the distribution network. [ABSTRACT FROM AUTHOR]

Short-term load forecasting (STLF) is the basis of power system planning and operation. With regard to the fast-growing load in China, a novel two-stage hybrid forecasting method is proposed in this paper. In the first stage, daily load is forecasted by time-series methods; in the second stage, the deviation caused by time-series methods is forecasted considering the impact of relative factors, and then is added to the result of the first stage. Different from other conventional methods, this paper does an in-depth analysis on the impact of relative factors on the deviation between actual load and the forecasting result of traditional time-series methods. On the basis of this analysis, an adaptive algorithm is proposed to perform the second stage which can be used to choose the most appropriate algorithm among linear regression, quadratic programming, and support vector machine (SVM) according to the characteristic of historical data. These ideas make the forecasting procedure more accurate, adaptive, and effective, comparing with SVM and other prevalent methods. The effectiveness has been demonstrated by the experiments and practical application in China. [ABSTRACT FROM PUBLISHER]

The paper introduces a robust methodology for evaluating complex electricity system efficiency, making several contributions. It systematically decomposes the electric power system into various processes, including power generation, transmission, distribution, and power consumption, with parallel sub-processes for production and domestic power consumption. Employing data envelopment analysis (DEA), the paper develops a network directional slacks-based (DSB) model to evaluate the whole system and the internal processes. The model is theoretically proven to be feasible, providing efficiency scores and identifying inefficiencies in the system and its processes. A noteworthy addition is the introduction of the DSB green Luenberger productivity index and its decomposition, offering an analysis of productivity changes in electricity systems. Empirical analysis covering 30 Chinese provinces from 2013 to 2019 uncovers the performance variations among provinces and processes, pointing out inefficiencies and changes in technology and efficiency over time. The empirical findings aim to support efforts in enhancing the overall efficiency of China's interprovincial power system. • We decompose the complex electric power system into four processes with dependence. • We build a network directional slacks-based (DSB) model for the complex power system. • We give a DSB green Luenberger productivity index (DPI) for our network model. • The efficiency score and DPI of the system are decomposed into those of processes. • We apply the model and indexes to electric power systems in Chinese provinces. [ABSTRACT FROM AUTHOR]

Socio-economic development is undergoing changes in China, such as the recently proposed carbon peak and carbon neutral targets, new infrastructure development strategy and the Coronavirus disease 2019 (COVID-19) pandemic. Meanwhile, the new-round marketization reform of the electricity industry has been ongoing in China since 2015. Therefore, it is urgent to evaluate the risk of electric power grid investment in China under new socio-economic development situation, which can help the investors manage risk and reduce risk loss. In this paper, a hybrid novel multi-criteria decision making (MCDM) method combining the latest group MCDM method, namely, Bayesian best–worst method (BBWM) and improved matter-element extension model (IMEEM) is proposed for risk evaluation of electric power grid investment in China under new socio-economic development situation. The BBWM is used for the weights' determination of electric power grid investment risk criteria, and the IMEEM is employed to rank risk grade of electric power grid investment. The risk evaluation index system of electric power grid investment is built, including economic, social, environmental, technical and marketable risks. The risk of electric power grid investment under new socio-economic development situation in Inner Mongolia Autonomous Region of China is empirically evaluated by using the proposed MCDM method, and the results indicate that it belongs to "Medium" grade, but closer to "High" grade. The main contributions of this paper include: (1) it proposes a hybrid novel MCDM method combining the BBWM and IMEEM for risk evaluation of electric power grid investment; and (2) it provides a new view for risk evaluation of electric power grid investment including economic, social, environmental, technical and marketable risks. The proposed hybrid novel MCDM method for the risk evaluation of electric power grid investment is effective and practical. [ABSTRACT FROM AUTHOR]

Synchrophasors, widely used in the monitoring and analysis of power systems, evolved from the phasor method presented by Charles Proteus Steinmetz in 1893. The phasor method is a mathematical method for solving linear sinusoidal steady-state circuits and time-varying electromagnetic fields. This paper traces the history and diffusion of the phasor method in the discipline of electrical engineering in China. In 1914, Sidney Roby Sheldon, an American teacher at the Government Institute of Technology of the Communications Ministry, Shanghai, China, introduced the phasor method to his students in his Alternating Currents course. The textbook used was Elements of Electrical Engineering (Volume II) by William Suddards Franklin and William Esty. In 1920, The Electrical Magazine published a paper “Complex number and its application” by Sijiu Shi (editor of the electrical engineering section of this periodical). This is the earliest example found of Chinese literature introducing the phasor method. In the 1930s, Principles of Alternating Currents, an American electrical engineering textbook that includes the phasor method, was translated by Chinese scholars; this Chinese version promoted the use of the phasor method in China's electrical engineering field. Alternating Current Circuits, authored by the Chinese university professor Pen Tung Sah and published in 1948, may be the earliest example of the phasor method being included in a Chinese electrical engineering textbook; it played an important role in popularizing the phasor method in China. [ABSTRACT FROM AUTHOR]

This paper presents a new combined method for the short-term load forecasting of electric power systems based on the Fuzzy c-means (FCM) clustering, particle swarm optimization (PSO) and support vector regression (SVR) techniques. The training samples used in this method are of the same data type as the learning samples in the forecasting process and selected by a fuzzy clustering technique according to the degree of similarity of the input samples considering the periodic characteristics of the load. PSO is applied to optimize the model parameters. The complicated nonlinear relationships between the factors influencing the load and the load forecasting can be regressed using the SVR. The practical load data from a city in Chongqing was used to illustrate the proposed method, and the results indicate that the proposed method can obtain higher accuracy compared with the traditional method, and is effective for forecasting the short-term load of power systems. [ABSTRACT FROM AUTHOR]

In this paper, a dynamic hybrid var compensator (HVC) for distribution grid is proposed. The system is based on a combination of a small-capacity distribution static compensator (DSTATCOM) and multigroup large-capacity thyristor switched capacitor (TSC). The DSTATCOM is the continuous subsystem of HVC, and the TSCs are the discrete subsystem of HVC. A new hybrid control method based on expert decision has been proposed to make sure that the HVC has good performance. A two-level collaborative optimization arithmetic, which is used to decide the optimal capacity of each HVC, has been proposed in this paper. A dynamic energy-saving system based on HVCs has been developed for a melt factory in southern China; application results show that compared to traditional reactive power compensation systems, the proposed system can effectively correct power factor, support supply voltage, mitigate voltage flicker, and obtain good effect for energy saving with low cost. [ABSTRACT FROM AUTHOR]

A load model is one of the most important elements in power system simulation and control. Recently, the constant impedance, constant current, and constant power load in combination with the induction motor load have been widely used as the composite load model, whose parameters are all identified from the field measurements in measurement-based load modeling practices so far. However, there is virtually no research conducted on whether all these parameters could really be identified. This paper investigates the possibility on reducing the number of composite load model parameters to be identified from field measurements. This paper first shows that direct application of the IEEE load motor parameters in the composite load model may be inadequate on describing the load dynamics over different operating status. Then the perturbation method is used to derive the trajectory sensitivities of the equivalent motor parameters, based on which the reduction on the identified parameters of the composite load model is presented. Two cases of measurement-based load modeling in North China and Northeast China are studied to illustrate the validity of the reduction method. It is shown that the reduction does not lose the model's capability on describing the load dynamics. The reduction on the number of identified parameters not only provides a possible way to solve the multi-valued load model problem based on the current practices on measurement-based load modeling, but it also facilitates building of the load model with more components included in it. Meanwhile, reducing the identified parameters reduces the identification time; thus, the proposed strategy significantly enhances the efficiency of the load modeling work. [ABSTRACT FROM AUTHOR]

Due to the uneven geographical distribution between load and wind power, currently it is difficult to integrate the large-scale wind power into the State Grid in China. There are significant wind curtailments for wind farms due to system restrictions. This paper proposes a new way of utilizing wind power, i.e., in-situ consumption, as an alternative to the costly development of long-distance transmission of large-scale wind power. Electrolytic aluminum load, which is one of the most typical high energy consuming loads, is employed to absorb the excess wind power in western China. An actual isolated industrial power system for aluminum production driven by wind power and coal-fired power is described. The penetration level of wind power in the isolated power system is up to 48.8%. The power imbalance between generation and load demand caused by wind power fluctuation or the tripping of coal-fired generators can dramatically impact the frequency stability of the isolated power system, which is of small inertia. An online identification method of power imbalance based on Wide Area Measurement System (WAMS) is presented. According to the characteristics of the electrolytic aluminum load, a system frequency control method by regulating the bus voltages of aluminum loads to eliminate the power imbalance is introduced. The simulation is done in Real Time Digital Simulator (RTDS) and the results verify the validity of the proposed frequency control method. [ABSTRACT FROM PUBLISHER]

There is growing consensus that gas-fired generators will play a crucial role during the transition to net-zero energy systems, both as an alternative to coal-fired generators and as a flexibility service provider for power systems. However, malfunctions of gas networks have caused several large-scale power blackouts. The transition from coal and oil to gas fuels significantly increases the interdependence between gas networks and electric power systems, raising the risks of more frequent and widespread power blackouts due to the malfunction of gas networks. In a coupled gas–electricity system, the identification and transmission of gas network malfunction information, followed by the redispatch of electric power generation, occur notably faster than the propagation and escalation of the malfunction itself, e.g., significantly diminished pressure. On this basis, we propose a gas-electric early warning system that can reduce the negative impacts of gas network malfunctions on the power system. A proactive control strategy of the power system is also formulated based on the early warning indicators. The effectiveness of this method is demonstrated via case studies of a real coupled gas–electricity system in China. Gas-fired generators play crucial role in the transition to net-zero energy systems as an alternative to coal-fired. But malfunctions of gas networks can cause large-scale power blackouts. Here, authors apply the early warning concept to the coupled gas-electric system towards enhanced power supply security. [ABSTRACT FROM AUTHOR]

Climate change poses a huge threat to human welfare. Hence, developing a low-carbon economy has become a prevailing and inevitable trend. Decarbonization of power generation, especially converting the current power mix into a low-carbon structure, will be a critical option for CO2 emission mitigation. In this paper, an integrated power generation expansion (PGE) planning model towards low-carbon economy is proposed, which properly integrates and formulates the impacts of various low-carbon factors on PGE models. In order to adapt to the characteristics of PGE models based on low-carbon scenario, a compromised modeling approach is presented, which reasonably decreases complexities of the model, while properly keeping the significant elements and maintaining moderate precision degree. In order to illustrate the proposed model and approach, a numerical case is studied based on the background of China's power sector, making decisions on the optimal PGE plans and revealing the prospects and potentials for CO2 emission reduction. [ABSTRACT FROM AUTHOR]

Ice melting with dc is one of the key technologies to prevent the Chinese power grid from ice storms. Especially after the severe ice storm in the southern part of China in early 2008, dc ice-melting technology has drawn more attention than ever before. However, there are few satisfactory methods to select correct parameters so the ice-melting project rarely achieves desired effects in some cases when applied in Hunan, Guizhou, and other provinces in China. Therefore, it is of great significance to develop a method to estimate parameters which is applicable in the practical situation for dc ice melting. To handle this, the factors, such as wind velocity, ambient temperature, current density and ice-layer thickness were analyzed and then a dc ice-melting model is put forward in this paper. Both the results of simulations and experiments show that the ice-melting process can be divided into three stages composed of temperature rising, ice melting, and ice shedding, among which the ice melting is the key stage consuming most of the ice-melting time. In this stage, an elliptic airgap is formed and widened gradually with an influence on the ice-melting time and the temperature of the conductor. The experiments in the artificial climate chamber demonstrate that the results of the presented model are consistent with those of the experiments generally, so it can be employed to estimate the parameters of ice melting in practical engineering as reference. [ABSTRACT FROM AUTHOR]

Failure probability of system components may vary with the changes of weather, environment and other operation conditions. The time-varying or condition-based failure probability can be represented using a fuzzy model. Based on credibility theory, this paper presents a novel operation risk assessment method to handle the two-fold uncertainty combining randomness and fuzziness in power system operations. In the proposed method, a random fuzzy model is developed to accommodate impacts due to various operation conditions and other factors on the failure probability of system components. The WECC nine-bus system, IEEE 14-bus system and an actual power system in Northeast China were used to demonstrate feasibility and applicability of the presented method. The operation risk assessment module using the proposed method has been embedded in the EMS system in a district control center of a power company to perform real-time operation risk assessment. [ABSTRACT FROM AUTHOR]

Short‐term load forecasting is essential to power systems management. However, most existing forecasting methods fail to fully consider how to rationally integrate the intrinsic time‐related dimensions of electric load data and the decomposition methods into machine learning models so that their prediction accuracy and robustness still have much room for improvement. To solve this problem, this paper proposes a decomposition‐based multi‐time dimension long short‐term memory (DB‐MTD‐LSTM) model for short‐term electric load forecasting (STELF). In DB‐MTD‐LSTM, empirical mode decomposition with adaptive noise (CEEMDAN) is first introduced to smooth non‐linear non‐stationary electric load data and constrain the modal aliasing or noise of decomposed electric load data in the traditional decomposed method. A joint relevant time dimensions method (JRTDM) is then developed using autocorrelation analysis to rationally extract the temporal characteristics of decomposed data in multiple time dimensions. An improved LSTM called MTD‐LSTM is developed by combining JRTDM with LSTM, which can effectively apply multi‐dimensional time characteristics of the decomposed load to improve the predictive accuracy and robustness. Several datasets from Australia and China are performed to check the predictive performance of DB‐MTD‐LSTM. Experimental results verify that DB‐MTD‐LSTM has better predictive accuracy and satisfactory robustness compared with state‐of‐the‐art and conventional predictive models. [ABSTRACT FROM AUTHOR]

In this study, a locally weighted linear regression (LWLR) method is proposed to predict damping ratio of a dominant mode online. The LWLR method, which is nonparametric and data-oriented, is essentially proposed for nonlinear data fitting; therefore, it can track the nonlinear power system operations and help damping ratio prediction in real power systems, which is hardly achieved by the conventional linear regression. To successfully implement this method, the measurement of weighting value and the choice of weighting function as well as its parameter setting, related to prediction accuracy and numerical conditions, are extensively discussed. Simulations are carried out in a two-area four-machine system and a large complex system, China Southern Grid. Both results validate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

Chinese electric power sector (EPS) contributes 52% of China's total CO 2 emissions. Given the severe global warming situation, carbon information disclosed by Chinese electric power enterprises (EPEs) has received extensive attention. Therefore, to understand the current level of carbon information disclosure (CID) in EPS and improve the CID quality, this paper evaluates the CID quality of public companies in the EPS. Based on the characteristics of the EPEs, this paper established a CID quality evaluation system from five aspects: integrity, relevance, reliability, comprehensibility, and comparability. An ANP-Cloud model is employed to evaluate the CID quality of 62 public companies in China's EPS. The analytic network process (ANP) method can quantify the correlation among evaluation indexes. The Cloud model achieves the transformation from qualitative evaluation to quantitative scoring with consideration of the uncertainty and fuzziness of the expert's evaluation language. The integration of two models, therefore, improves the comprehensiveness and objectiveness of the evaluation results. The evaluation results indicate that: (1) "Carbon emissions", "Carbon emission reduction targets" and "Independent chapter" indexes disclosed by the EPEs have a significant impact on CID quality. (2) The CID quality of the entire EPS public companies is low. The carbon information disclosed by EPEs cannot effectively represent the carbon management behavior of enterprises. (3) From the internal perspective of the EPS, the CID quality of thermal enterprises is relatively high, while hydropower enterprises are relatively low. Finally, this paper proposes viable suggestions to improve the CID quality from three aspects: EPEs, government, and public monitoring. • Constructed a carbon information disclosure (CID) quality evaluation system for electric power sector. • Integrated analytic network process (ANP) method and Cloud model to make the evaluation result reasonable. • Evaluation results show that the overall disclosure quality is low. • Indexes concerned by the carbon information users are determined. [ABSTRACT FROM AUTHOR]

The volatility and uncertainty of wind energy has brought great challenges to its accommodation in electric power systems. To determine a wind power trading strategy in the real-time power market, the accurate assessment of wind energy accommodation capability (WAC) is of great significance. However, most current studies investigate the wind energy accommodation potential from the perspective of dispatch, but rarely provide quantitative assessment results. Additionally, the non-anticipativity of decisions has not been considered in the assessment yet. This paper proposes a novel quantitative assessment method for WAC based on the multi-stage robust optimization (RO), which addresses the anticipativity issues in the traditional two-stage method while maintaining the decision-making process' robustness. In the assessment method, the operational risk is integrated via a tractable scheme to obtain dynamic admissible WAC boundaries. To obtain the optimal solution of the proposed multi-stage RO problem, a fast robust dual dynamic programming (FRDDP) algorithm is employed, where the adaptive techniques are developed to accelerate the computation. Numerical studies on the modified IEEE 14-Bus system and a real-world system in Zhejiang Province of China validate the effectiveness of the proposed assessment model and adaptive acceleration techniques. The simulation results demonstrate the presented method brings a 18.87% reduction in operational cost, and reduces 29.34% curtailment of wind energy. Compared with the original FRDDP, the adaptive technique significantly reduces the computational consumption by 73.34% on the real-world test system. • A novel assessment method for WAC is proposed based on the multi-stage robust optimization. • Tractable risk evaluation method is integrated in the multi-stage framework. • Adaptive techniques are designed for FRDDP method to accelerate the optimal solution. • The proposed method achieves both non-anticipative and robust assessment decisions. [ABSTRACT FROM AUTHOR]

As the penetration rate of renewable energy increases in the electric power system, the issues of renewable power curtailment and system inertia shortage become more severe. Innovative solutions such as Cloud Energy Storage (CES) can be employed to address this challenge. However, the energy storage resources aggregated by the traditional CES business model mainly concentrate on Electrical Energy Storage (EES), which is still limited and expensive. It necessitates the exploration of new approaches to enhance the flexibility and cost-effectiveness of energy storage utilization, in which using District Heating System (DHS) as an equivalent energy storage resource of the power system is an effective method. Therefore, this paper proposes an optimal planning strategy of energy storage system under the CES model considering inertia support and electricity-heat coordination. Firstly, the system components and business model of the CES are described, and the framework of energy storage planning problem from the perspective of CES operator is formulated. Then the evaluation methods of energy storage utilization demand from CES users are proposed, including the evaluation of the renewable power curtailment, system minimum inertia requirement, and the equivalent energy storage ability of DHS. Based on this evaluation results, a bi-layer optimal energy storage planning model for the CES operator is established, where the upper-layer model determines the installed capacity of lithium (Li-ion) battery station and the lower-layer model determines the optimal schedules of the CES system. The numerical tests based on the operation profile of a typical city in China are carried out to demonstrate the effectiveness of the proposed method. The simulation result shows that the annual profit of the CES system can be improved by 15.26% after installing the energy storage system whose capacity is determined by the proposed method. • A CES model considering electricity-heat coordination and system inertia support is designed. • CES users' demand is evaluated by system operation simulation and inertia shortage estimation. • A bi-level optimization model of BES expansion planning is proposed for the CES operator. • Empirical study based on practical power system data in China to provide real-life experience. [ABSTRACT FROM AUTHOR]

Optimal utilization of available water resources has become more urgent due to the rapid growth of the economy and population. The joint operation of the Three Gorges cascade and Qingjiang cascade reservoirs in China was studied in this paper. Choosing maximization of hydropower generation and hydropower revenue as objective functions respectively, optimal models were established for individual and joint operation of the cascade reservoirs. The models were solved by the progressive optimality algorithm. The storage and electric compensation benefits among cascade reservoirs were analyzed. The daily inflow data of consecutive hydrological years of 1982-1987 were selected for a case study. Compared with the design operation rule, the joint operation of the multi-reservoir system can generate 5.992 billion kWh of extra power or an increase of 5.70% by the objective function of maximum hydropower generation. Through reservoir storage compensation, the spilled water of the Three Gorges and Qingjiang cascade reservoirs was decreased by 78.741 and 5.384 billion m3, respectively. [ABSTRACT FROM AUTHOR]

The Shangdu power plant has four 600-MW turbine-generators connected to the North-China Grid through two 500-kV transmissions, which are compensated with 45% fixed series capacitors. Extensive studies conducted on the system model indicate that the system suffers from multimodal subsynchronous resonance (SSR). To solve the problem, a countermeasure is developed by combining the supplementary excitation damping control (SEDC) and the torsional stress relay (TSR). In this paper, the characteristics of the SSR problem are investigated. Then the developed SEDC is presented. To validate the effectiveness of the proposed SEDC as well as the results of model studies, field tests were conducted under various operating conditions. The tests fully exposed the realistic threat of SSR in the system. Meanwhile, it is demonstrated that the developed SEDC can improve torsional damping significantly, and thus solve the multimodal SSR problem effectively. This is the first time in China that practical SEDCs have been developed and their ability to mitigate multimodal SSR has been verified in a real series-compensated system. [ABSTRACT FROM AUTHOR]

An instrumented, intelligent electrical power grid, or smart grid, is under research and is being preliminarily constructed in many parts of the world to deal with new challenges to modern power systems brought on by pressures on environment and resources. In this paper, a smart grid with the ability of multi-index self-approximate-optimal operation is considered the most distinctive difference between a smart grid and a traditional power grid. Multi-index is the index set that consists of a series of key indices for the grid operating chain, including generation, transmission, distribution, consumption, and dispatching. Self-approximate-optimal refers to the process by which the electricity grid arrives at a satisfactory operation point from an unsatisfactory point by its automated closed-loop control and regulation. In this paper, the general architecture and solution algorithm of multi-index self-approximate-optimal operation are proposed and developed. Furthermore, two realistic and promising practices in China are described to illustrate how a smart grid can be achieved under the guidance of the proposed multi-index self-approximate-optimal operation. [ABSTRACT FROM AUTHOR]

Load model is one of the most important elements in power system simulation and control. Based on more than 20 years of practice using load characteristic recorders in the measurement-based load modeling, this paper proposes the Expectation Composite Load Model to predict unseen data. The methods for load bus classification and parameter identification are also provided. The generalization capability of the proposed load modeling is validated by the measured load dynamics and system dynamics during two three-phase short circuit tests of the NE power grid in China. In order to evaluate the measurement-based load model, the Probabilistic Collocation Method (PCM) is applied to quantitatively analyze uncertainties of the simulation responses raised by the parameters. [ABSTRACT FROM AUTHOR]

With strong support from Chinese government bodies such as the National High Technology Research and Development Program of China, National Natural Science Foundation of China and the National Basic Research Program of China, the field of applied superconductivity in China has been developed in different areas. Especially in the fusion application area, the first fully-superconducting tokamak, EAST (Experimental Advanced Superconducting Tokamak), has been successfully constructed and commissioned in the last two years. Based on the requirement from the ITER project, high performance Bi-2223 HTS tape, and Nb3Sn and NbTi strands have been developed as well. In the area of HTS applications for electric power systems, R&D has been focused on superconducting power cable, superconducting magnetic energy storage, superconducting transformer, superconducting fault current limiters. In this paper, the recent progress in applied superconductivity in China is reported. [ABSTRACT FROM AUTHOR]

The significant progresses in high Tc superconducting wires or tapes have excited a great deal of research interests in power application. This paper will review the recent progresses of power application of superconductor in China. An improved bridge-type fault current limiter was tested and a 10.5 kV/1.5 kA demonstrator has been operated at a substation in Hunan Province in 2005. A 75 meter, 10.5 kV/1.5 kA three phase HTS cable has been installed and operated at the Changtong Cable Headquarter in the end of 2004, and a 30 meter, 35 kV/2 kA HTS power cable was installed at substation and has been operated since July 2004. A 10.5 kV/400 V/630 kVA HTS transformer has been installed and operated at TBEA Electric Factory in 2005. A 500 k J/150 kVA SMES unit was developed and tested. 1.0 M J/0.5 MW SMES will be installed in a power grid in 2006. Besides, a new kind equipment of fault-current-limiting SMES is being developed and a 100 kJ/25 kW prototype has been made and tested. [ABSTRACT FROM AUTHOR]

To address the global challenge of climate change and achieve sustainable development, decarbonizing the electric power system in China is considered the most imperative since the power sector is highly related to the decarbonization of other sectors. Significantly, China faces the dual challenges of rapidly growing electricity demand coupling with its commitment to of emission mitigation. This study examines the low-carbon transition and sustainable development of China's power system through 2035 using a multi-stage mixed-integer linear programming generation planning model by matching future demand growth trajectories with the least-cost power supply path. The electric power installed capacity, power generation, carbon emission, power-generating cost, and abatement potentials are analyzed through various scenarios. It is found that China's electricity demand will reach 9800–13300 Terawatt-hours in 2035 due to rapid electrification. Every 1 TWh increase in electricity demand requires 0.41–0.53 GW of newly installed capacity. Reducing the proportion of coal-fired power generation and replacing it with renewable energy is inevitable. However, for every 1 GW of coal power retired, 3.7 GW of renewable energy needs to be built. Incorporating electricity demand-side management is crucial to developing an effective decarbonization pathway for China's power sector, along with inclusive policies and technologies to meet China's requirements for dependable, affordable, and sustainable electricity. The results of this paper can provide a reference for policy makers in China as well as other emerging economies. • China's electricity consumption will continue to rise until 2035 and China will reach emission peak of power sector before 2030. • Meeting China's decarbonization requires gradually reducing coal-fired power capacity by up to the year 2020's 40.5% ty. • Every 1 GW of coal-power retirement requires the construction of 3.7 GW of renewable power capacity. • Demand-side management is crucial to easing high electricity demands for an effective power decarbonization trajectory in China. [ABSTRACT FROM AUTHOR]

Buildings' energy resilience in natural disasters is reliant on the support of the functionalities of critical infrastructure that the buildings connect to, such as highway-bridge and electric power systems. Meanwhile, as critical infrastructure systems have increasingly become interconnected and interdependent, they are more susceptible to natural hazards and less able to withstand their effects. Insufficient research has been conducted regarding computational models of effectively representing the interdependencies and interactions involved in the restoration scheduling of post-disaster critical infrastructure systems. To address this research gap, this study proposes integer programs, integrating hybrid genetic algorithms, to explicitly investigate the impact of interactions and interdependencies between electric power systems (EPSs) and highway-bridge systems (HBSs) on the energy-recovery processes of buildings. The objective is to dynamically prioritize the restoration scheduling for EPSs and HBSs while considering inspection and restoration activities. A case study based on the 2008 Wenchuan Earthquake in Sichuan province, China, is employed to validate the efficacy of the proposed method. The results of the analysis reveal that the dynamic model exhibits a substantial 6.4% improvement in building energy resilience at the seven-day mark, compared to the static model. Moreover, the proposed coupled EPS–HBS inspection–restoration joint model outperforms a disjoint EPS inspection–restoration scheduling model, yielding a remarkable 11.4% enhancement in system resilience at the seven-day mark. These findings underscore the significance of considering interdependencies and interactions within critical infrastructure systems to enhance the energy resilience of buildings in earthquake-affected areas. [ABSTRACT FROM AUTHOR]

Abstract Under the background of the structural adjustment of national energy strategic, ultra-high voltage (UHV) has been becoming an inevitable trend in the future development of the Chinese power grid. With the change of external environment, such as policy and economy, and the rapid development of the UHV, UHV project management is faced with great challenges and urgently need to establish a set of performance evaluation analysis tools. In this paper, we propose a slacks-based measure (SBM) data envelopment analysis (DEA) method for the performance evaluation and improvement of ultra-high voltage projects. Besides, we also build a set of performance evaluation index for UHV projects. Finally, we employ the preliminary planning UHV projects of a Chinese power grid company to illustrate the proposed method. Results show that our method is valid. Our method can provide an effective tool for decision support. [ABSTRACT FROM AUTHOR]

According to the perspective of multimode multimedia data, the protection technology of network information security is mainly discussed. The theoretical basic research is outlined, its meaning, level, reasons, and consequences are expounded, and the future research content and development trend are discussed. With the rapid development of online services and mobile technology, the world has entered the era of multimedia big data. There have been a large number of scientific studies in the multimedia industry, which explain the various fields of big data, including the capture, storage, reference, excavation, and search of multimedia big data. The article expounds the specific concept of power monitoring system network information security, establishes the safety regulations of electric power monitoring system, formulates the corresponding ideas for the safety guarantee level of electric power monitoring system, and promotes the long-term development of China's electric power enterprises. The safe operation of the power monitoring system is directly related to the stable operation of all power supply systems and even the social economy. At this stage, the situation of network security management in China's power monitoring system is still not optimistic. We take the multimode multimedia data, organize the research dynamics of the network security protection technology, and discuss the future research trend. [ABSTRACT FROM AUTHOR]

Yi, M.; Mo, L., and Shen, Q., 2020. Study on generation scheduling of cascade hydropower stations based on SAPSO. In: Guido Aldana, P.A. and Kantamaneni, K. (eds.), Advances in Water Resources, Coastal Management, and Marine Science Technology. Journal of Coastal Research, Special Issue No. 104, pp. 371–378. Coconut Creek (Florida), ISSN 0749-0208. With the reduction of energy and the reform of China's electric power system, it is of great help to develop clean energy such as hydropower to ease the lack of energy. Many methods are studied to solve the reservoir optimal scheduling problem, such as particle swarm optimization (PSO). In order to solve the premature problem and slow convergence of traditional PSO, simulated annealing particle swarm optimization (SAPSO) is proposed in this paper. The algorithm is improved by adding shrinkage factor and combining with simulated annealing algorithm. Establishing the maximum generation model, and SAPSO algorithm is used to optimize the power generation scheduling of four and ten hydropower stations. The case study shows that the application of SAPSO to solve the short-term optimal scheduling problem of cascade hydropower stations has achieved satisfactory results in effect and rationality. It provides a reliable method for the optimal operation of cascade hydropower stations. [ABSTRACT FROM AUTHOR]

An important goal of China's electric power system reform is to create a double-side day-ahead wholesale electricity market in the future, where the suppliers (represented by GenCOs) and demanders (represented by DisCOs) compete simultaneously with each other in one market. Therefore, modeling and simulating the dynamic bidding process and the equilibrium in the double-side day-ahead electricity market scientifically is not only important to some developed countries, but also to China to provide a bidding decision-making tool to help GenCOs and DisCOs obtain more profits in market competition. Meanwhile, it can also provide an economic analysis tool to help government officials design the proper market mechanisms and policies. The traditional dynamic game model and table-based reinforcement learning algorithm have already been employed in the day-ahead electricity market modeling. However, those models are based on some assumptions, such as taking the probability distribution function of market clearing price (MCP) and each rival's bidding strategy as common knowledge (in dynamic game market models), and assuming the discrete state and action sets of every agent (in table-based reinforcement learning market models), which are no longer applicable in a realistic situation. In this paper, a modified reinforcement learning method, called gradient descent continuous Actor-Critic (GDCAC) algorithm was employed in the double-side day-ahead electricity market modeling and simulation. This algorithm can not only get rid of the abovementioned unrealistic assumptions, but also cope with the Markov decision-making process with continuous state and action sets just like the real electricity market. Meanwhile, the time complexity of our proposed model is only O(n). The simulation result of employing the proposed model in the double-side day-ahead electricity market shows the superiority of our approach in terms of participant's profit or social welfare compared with traditional reinforcement learning methods. [ABSTRACT FROM AUTHOR]

Abstract: A novel solar building cooling heating and power (BCHP) system driven by solar energy and natural gas is proposed in this paper. The performance of the presented system is greatly dependent upon the operation strategy. The primary energy consumption (PEC) and pollutant emissions of the solar BCHP system in following the electricity loads (FEL) and following the thermal loads (FTL) operation strategies are estimated based on life cycle assessment (LCA). Furthermore, three most important energy-related environment problems and human health issues, global warming, acid precipitation and respiratory effects, are considered to assess the environmental impacts of the system. In order to evaluate the comprehensive benefits achieved by the solar BCHP system in different operation modes, grey relation theory is employed to integrate the energetic benefits with environmental performances. Finally, a numerical case of the solar BCHP system for a commercial office building in Beijing, China is applied to compare the integrated performance in the FEL operation strategy with that of the FTL operation strategy. The results indicate that the energy saving and pollutant emissions reduction potentials of the FTL operation mode are the better than that of the FEL mode. [Copyright &y& Elsevier]

Abstract: Tiered electricity price (TEP) reform is a planning policy for household electricity conservation in China. Based on TEP, several price hierarchies are provided, and additional payment will be charged if the electricity consumptions exceed the upper bound of each hierarchy. Yet, the optimal level of each price tier and the institutions for implementing TEP need further research, which are set on the basis of considering residents’ affordability and willingness to pay. Therefore, this paper aims at exploring determinants of public willingness to accept TEP and finding out the acceptable range of premium. A questionnaire survey in four urban cities of China is conducted to collect data, and an ordinary regression model is adopted in our analysis to identify the drivers and barriers to general public’s acceptance of TEP. The results show that middle income earners are the groups that are mostly opposed to TEP. Rather than just focusing on economic factors, public environmental awareness should be highlighted during the implementation of TEP, because cost is not a statistically significant determinant in this study. Moreover, the public acceptable rate of premium of TEP in the urban cities, according to our research results, may be below .05RMB/kWh. [Copyright &y& Elsevier]

Abstract: With the construction of Hainan international tourism island rising to a national strategy level, the green growth pattern based on low carbon objectives will become a significant part in the development of Hainan''s economy. In this paper, low carbon electric power system and differentiation service will be discussed, and some opinions were brought up to have a good impact on Hainan''s low carbon development. [Copyright &y& Elsevier]

Abstract: As top enterprise in China, the power supply companies should be excellent in the information tide wave, and they will realize the transformation from data processing to data mining. It is an attracting goal, but the fact is a little bit depressing, for there is a severe defect, called information isolated island, in the information system of the power supply companies. So an compatible and advanced information platform is an urgent affairs..Through the analysis of existing technology, starting from the system architecture the data center with Similar to the EXCEL is proposed, and the function implementation of the system is elaborated in this paper. [Copyright &y& Elsevier]

This paper proposed a model-based framework to optimize the energy-water-emissions nexus (EWEN) for regional electric power system (EPS) planning. The framework integrated the superiority of bi-level programming (BLP), two-stage stochastic programming (TSP), mix-integer programming (MIP), interval parameter programming (IPP) models and carbon emission trading (CET) mechanism, which could effectively deal with the planning problems in the EWEN optimization process. BLP helped decision makers make leader-follower choices when they have conflicting preferences. TSP with IPP could validly address the uncertain information expressed as interval values with unknown distribution. MIP was introduced as an efficacious tool to evaluate the capacity expansion potential in EPS. CET mechanism was applied to reinforce the CO 2 mitigation effect during the EWEN optimization process. Then the proposed framework was applied into a case study in Shanxi Province, a main thermal power base in China to optimize the EWEN. Results indicated that the power supply structure was inclined to show a low-carbon transition trend in the planning periods. Meanwhile, coupled with the strict water conservation policy, every 5% reduction in carbon emission density would lead to an average decreasing rate of 8% for SO 2 , 3% for NOx and 12% for PM. This study may help provide an effective way to deal with planning problems with conflicting and sequential goals under uncertainty and make better tradeoff strategies in EWEN optimization in EPS. • Propose a stochastic leader-follower framework for energy-water-emission nexus. • Control uncertainty by the combination of TSP and with IPP. • Interactions of CO 2 emissions and air pollution emissions are revealed. • Introduce CET mechanism to help improve the CO 2 mitigation effect. • The empirical results demonstrate the excellent performance of the framework. [ABSTRACT FROM AUTHOR]

Electric power is the foundation of the development of national economy, it is necessary to make a comprehensive evaluation of its development. Firstly, 17 secondary electric power development evaluation indexes are established from four aspects: electricity supply, electricity consumption, electrification level and carbon emission. Secondly, based on the cloud model, the subjective evaluation and analysis of the primary evaluation index for the national electric power development are realized. Then, the entropy method is used to objectively evaluate and analyze the secondary evaluation index of national electric power development. And the objective evaluation value of the primary evaluation index for the national electric power development is obtained. Thirdly, the TOPSIS method is used to integrate the subjective evaluation value obtained by the cloud model and the objective evaluation value obtained by the entropy method to comprehensively evaluate the status of national electricity development. Next, by collecting the electric power development evaluation index data of 11 typical countries, the electric power development of 11 countries was evaluated and analyzed by using the CM-EM-TOPSIS method proposed in this paper. From the results of the comprehensive evaluation of China 's electric power development, it is found that compared with other countries, the sensitivity of the queueing indicator value to the subjective evaluation weight is lower in China. Finally, according to the results of comprehensive evaluation and analysis of electric power development, the managerial implication is explored in China. • A comprehensive evaluation index system for national electric power development is established. • Cloud model is used to convert the subjective evaluation value of the primary evaluation index. • The secondary evaluation index of national electric power development is evaluated and analyzed by entropy method. • A national electric power development comprehensive evaluation method based on CM-EM-TOPSIS is proposed. • The current status of electricity power development in 11 typical countries is evaluated. [ABSTRACT FROM AUTHOR]

We propose a novel concept of the robot of energy control based on parallel cyber-physical-social systems for the next generation of energy and electric power systems. We thoroughly investigate its knowledge automation technologies and discuss its main challenges in preparation of promising evolution from Energy 4.0 to Energy 5.0 in China. [ABSTRACT FROM AUTHOR]

In China, the increasing amount of electricity imported from high voltage direct current (HVDC) transmission systems in some provinces has led to the retirement of local units. Lack of local generating capacity is adverse to the stability of system frequency and the adequacy of ancillary services. This study proposes a practical method to determine the minimum requirement of generating capacity (which is called the reliable generating capacity, RGC) in the sink side of a power grid. The relation between the minimum system frequency and the generating capacity is theoretically analysed. Based on simulation results, a function that determines RGC under a certain frequency drop constraint can be specified by data fitting. Meanwhile, the requirement of ancillary services (such as peak regulation, automatic generation control, and reserves) on typical days also imposes a floor constraint on the generating capacity. So the relation between generating capacities and ancillary services is also explored. Finally, the overall RGC value is the maximum of the above two aspects. A case study in East China Power Grid proves the effectiveness of the proposed method. The result can be used as a reference for power system planning and operation. [ABSTRACT FROM AUTHOR]

Environmental regulations are the key measure by which governments achieve sustainable environmental and economic development. This study aimed to determine the direct and indirect impacts of environmental regulations on total factor energy efficiency of regions in China. Since regions have different levels of economic development and resource endowment, we used the slacks-based measure (SBM)-undesirable model to calculate total factor energy efficiency considering regional technology heterogeneity and examined the regional impacts of environmental regulation on this efficiency using the Tobit regression model. A positive direct impact was generated in the eastern region of China by the forced mechanism, which forced enterprises to reduce fossil fuel energy demand and increase clean energy consumption; whereas a negative direct impact was generated in the middle and western regions owing to the green paradox, which is the observation that expected stringent environmental regulation prompts energy owners to accelerate resource extraction. Moreover, indirect impacts through technological progress and foreign direct investment were taken into account in the model, and the results show that the indirect impacts vary across regions. A logical response to these findings would be to develop different policies for different regions. [ABSTRACT FROM AUTHOR]

The low-carbon transition of the power system is essential for China to achieve peak carbon and carbon neutrality. However, China could suffer power shortages due to radical policies in some extreme cases. The gap between power demand and supply from March 2021 to November 2021 ranged between 5.2 billion kW·h and 24.6 billion kW·h. The main reason for the power shortage was over-reliance on renewable energy and insufficient coal power supply for the power system. The low-carbon transformation path of the electric system needs to be explored with more flexibility for power security. This study applied a modified LEAP model and carried out a forecast analysis of thermal power generation and installed capacity in 2025 and 2030 under normal and extreme weather scenarios. The results suggested that: the installed capacity of thermal power will need to account for about 44.6–46.1% of power generation in 2025 and 37.4–39.3% in 2030, with the assumption of power shortages caused by the instability and uncertainty of renewable power. In the future, China needs to pursue the development of diversified energy sources and enhance the power supply security capability while strengthening the development and utilization of renewable energy. [ABSTRACT FROM AUTHOR]

Composite insulators have been used in power system for more than 20 years in China. Compared to porcelain and glass insulators, the pollution flashover performance of composite insulators is better, whereas the icing flashover performance is worse. Shed configuration is a key factor that influences flashover voltage of composite insulators covered ice or snow in icing regions. The DC flashover tests of artificially ice-covered 110 kV composite insulators with different shed configuration were carried out in the multi-function artificial climate chamber. The test results revealed that there are huge differences between the icing flashover voltages of the composite insulators with different shed configuration. The test results indicate that icing flashover performance of the improved composite insulators for icing regions is not always superior to that of the standard composite insulators. [ABSTRACT FROM PUBLISHER]

In view of the great contribution of coal-fired units to CO2 emissions, the coupled coal and power system with consideration of CO2 mitigation is a typical sub-system of the highly emitting Chinese energy system for low-carbon studies. In this study, an inexact mix-integer two-stage programming (IMITSP) model for the management of low-carbon energy systems was developed based on the integration of multiple inexact programming techniques. Uncertainties and complexities related to the carbon mitigation issues in the coupled coal and power system can be effectively reflected and dealt with in this model. An optimal CO2 mitigation strategy associated with stochastic power-generation demand under specific CO2 mitigation targets could be obtained. Dynamic analysis of capacity expansion, facility improvement, coal selection, as well as coal blending within a multi-period and multi-option context could be facilitated. The developed IMITSP model was applied to a semi-hypothetical case of long-term coupled management of coal and power within a low-carbon energy system in north China. The generated decision alternatives could help decision makers identify desired strategies related to coal production and allocation, CO2 emission mitigation, as well as facility capacity upgrade and expansion under various social-economic, ecological, environmental and system-reliability constraints. It could also provide interval solutions with a minimized system cost, a maximized system reliability and a maximized power-generation demand security. Moreover, the developed model could provide an in-depth insight into various CO2 mitigation technologies and the associated environmental and economic implications under a given reduction target. Tradeoffs among system costs, energy security and CO2 emission reduction could be analyzed. [ABSTRACT FROM AUTHOR]

Superconducting Fault Current Limiter (SFCL) is an attractive appliance for modern electrical power system. Institute of Electrical Engineering (IEE) at the Chinese Academy of Science (CAS) has successfully demonstrated a three-phase HTS bridge-type fault current limiter (FLC) at a substation in Hunan, China. The FCL suppressed the fault current below 635 A successfully in a 3-phase-to-ground short-circuit field test. Since August 2005, it has been going on a demonstrated long-term reliable operation for one year in the live 110 kV/10.5 kV substation. [ABSTRACT FROM AUTHOR]

Depletion of fossil fuel deposits is the main current issue related to the world's power generation. Renewable energy sources integrated with energy efficiency represent an effective solution. The electrification of end-use coupled with renewable power generation integration is considered as an important tool to achieve these tasks. However, the current electric power system does not currently have the suitable features to allow this change. Therefore, in the future, it has to allow two-way direction power flows, communication, and automated controls to fully manage the system and customers. The resulting system is defined as the smart grid. This article analyses the smart grid state of play within China, the US, and the EU, assessing the completion state of each smart grid technology and integrated asset. The analysis related to these countries presented here shows that the smart grid overall state of play in China, the US, and the EU are equal to 18%, 15%, and 13%, respectively, unveiling the need related to further efforts and investments in these countries for the full smart grid development. [ABSTRACT FROM AUTHOR]