Electricity is attracting widespread attention for its critical role in global socioeconomic development, the clean energy transition, and climate change mitigation. Based on a newly established global database and a multi-level, multi-dimensional assessment framework, this study systematically evaluates the current status and recent progress of global electricity development and transition. Since 2020, global electricity development and transition have been characterized by four trends: electrification of energy consumption, the shift to clean electricity generation, wide-area electricity allocation, and digital-intelligent system operation. In 2024, global electricity consumption grew by approximately 4%, surpassing the growth rates of both total energy consumption and the global economy (GDP). Concurrently, the global electrification rate reached around 20%, total installed generation capacity exceeded 9.4 TW, the total length of power grid lines surpassed 80 million km, and installed energy storage capacity reached approximately 290 GW, with all metrics setting new record highs. A key transition milestone was also achieved in 2024: clean energy accounted for over 50% of global total installed capacity for the first time. The global electricity carbon intensity saw the largest drop (3%) in a decade. This study further provides a quantitative outlook to 2030, projecting that clean energy will account for 67% of global installed capacity and 59% of electricity generation, thereby achieving a clean-dominated power supply structure. Finally, it also outlines recommendations such as prioritizing power system flexibility and climate resilience, advancing research on evolving system operational dynamics, promoting the fusion and widespread adoption of new technologies and models, and enhancing international cooperation for sharing cost-effective technologies, replicable models, and expertise to address ongoing challenges and advance global targets.

Mobile hydrogen energy systems (MHESs) provide a flexible cross-regional hydrogen supply chain solution, where hydrogen is produced using surplus renewable energy, stored, and then transported to customers via tube trailers. Considering the uncertainties of renewable energy and hydrogen demands, we propose a data-driven distributionally robust chance-constrained (DRCC) dispatch model for MHESs. On the supply side, multiple operational states (production, standby, idle) and transitions of water electrolyzers are considered. On the transportation side, hydrogen delivery is formulated as a vehicle routing problem with time windows. Furthermore, the formulated DRCC model based on the Wasserstein ambiguity set is converted to a mixed-integer linear program with conditional value at risk approximation. Case studies are conducted on an MHES based on the traffic network of Xi'an City in China to verify the validity of the proposed method.

随着风电、光伏的大规模并网，电力系统面临灵活调节能力不足的挑战。水电运行灵活，通过与风光协同规划、互补运行，能有效平抑新能源出力波动，保障并网消纳。水风光协同规划的关键之一在于对水电灵活调节能力进行准确建模，其中振动区约束不容忽略。为此，提出了考虑水电振动区的水风光协同规划模型。该模型首先利用组合数学技术将水电机组振动区合成为电站振动区；然后，综合考虑振动区约束及梯级水力联系、水力发电方程等各项约束，实现对水电系统的准确建模；最后，耦合水电系统与新能源、联络线等相关运行约束形成水风光协同规划模型，并采用混合整数线性规划进行求解。以乌江流域某水风光互补系统为例，验证所提模型的有效性。

With the development direction of “two substitutions,one improvement, one return, and one transition”, the Global Energy Interconnection（GEI） promotes the large-scale development and utilization of clean energy globally. The strategic channel of time-space complementation and global configuration realizes the wide-area application of global multi-energy complementation. This paper first analyzes the connotation and relation of multi-energy complementation under the Global Energy Interconnection, and summarizes the typical application scenarios of multi-energy complementation in the GEI. Accordingly, a comprehensive planning method of multienergy complementation collaborative development based on GREAN and production simulation is proposed. Finally, through typical cases, the analysis results and benefits of the multienergy complementation of the GEI are shown.

In the process of electricity market construction, the establishment of reliability electricity price in accordance with the differentiated user demands has become an important aspect of improving the electricity pricing system. Based on the long-run incremental cost method, this paper proposes a reliability pricing method of distribution networks that takes into account differentiated user demands. Based on the reliability indexes for power supply regions, a regional reliability cost calculation model is proposed, and the reliability additional cost is further introduced. Then, the impact of the unit injection power on the economic investment horizon is analyzed to obtain the reliability electricity price for differentiated reliability demands in the distribution networks. Case studies of the RBTS-BUS 6 system shows that the proposed pricing system combining regional reliability base price and additional price can effectively balance regional power supply reliability and user differentiated demands.

在碳达峰、碳中和目标下,电力行业面临巨大的低碳转型压力.积极谋划煤电有序退出、在保证电网安全前提下加速清洁电源替代是实现双碳目标的必然选择.建立了煤电与清洁电源协同演进双层迭代优化模型.上层为电源投资决策模型,计及负荷和风光出力波动特性,以月为时间单位进行决策.下层是以运行经济性和满足调峰能力为目标的短期运行优化模型.进而,分析经济、技术、安全、环境因素对能源演进路径的影响,构建了对规划方案的综合评价指标体系,对能源演进路径薄弱环节进行辨识.最后,借助所提模型研究了某省级电力系统未来30年煤电与清洁电源协同演进路径,并对演进路径进行了综合评价,针对薄弱环节提出了相应的能源发展建议.

The rapid development of distributed energy resources (DERs) has resulted in significant integration problems. To solve them, two mainstream promotion measures ‐‐ the storage configuration mechanism and the distributed transaction mechanism, are put forward at home and abroad. This study will analyze the long-term influence of the integration mechanisms on distributed renewable energy by constructing an automated co-simulation framework with Vensim, GridLab-D and MATLAB. By combining Vensim's macro analysis ability, MATLAB's optimization control ability and GridLAB-D's micro-simulation ability together, this framework provides a more accurate tool to evaluate the performance of the integration mechanisms. Analyses of the short-term benefits and long-term development of the DERs in a test network demonstrate the effectiveness of the proposed co-simulation framework.

能源电力的充分共享是实现区域乃至世界范围内低碳可持续发展的关键途径.结合清洁低碳电源规划要求,提出一套考虑碳排放约束的跨国电源优化规划方法.根据各国未来能源电力宏观发展需求及碳排放目标,建立了跨国电源最优规划模型以及生产模拟仿真模型相结合的电源规划方法.跨国电源最优规划模型根据碳排放等宏观约束求解新建电源结构,应用考虑碳排放成本的生产模拟仿真模型针对求解电源结构进行模拟,统计分析化石能源机组的碳排放量指标,分析仿真指标与宏观发展目标的参数偏差,矫正跨国电源规划最优模型参数,再次求解电源规划方案.通过"生产模拟—优化规划"的迭代过程,将规划与运行有机结合,实现以满足碳排放约束且成本最小为优化目标的电源规划方案.采用所提出的方法,对南美洲3个主要国家2035年实现大规模联网后的发电系统进行了电源优化规划.

加快推动能源低碳转型、积极应对气候变化已成为全球共识.在英法德等国宣布退煤后,智利在2019年正式加入退煤行列,承诺在2040年退煤,2050年实现碳中和.大力开发风、光可再生能源资源,退役煤电,已成为智利实现清洁能源转型的重要一步.然而,智利煤电在电力供应结构中占比大,煤电的退出与清洁替代是电力供应结构的重大变革,将导致整个能源电力系统面临包括电力电量充裕性、可再生能源开发利用、电网输配能力、灵活性等多方面的困难和挑战.从电力供应发展的角度研究探讨了智利退煤和清洁能源转型的内在逻辑,详细分析了煤电退出后系统面临的挑战,并在此基础上研究梳理了智利应对挑战的举措.

Under the macro background of clean and low-carbon development for addressing global climate change, the current research on transnationally interconnected power systems has certain deficiencies in terms of geographic scope, time span, and multi-level coordination. We propose an orderly and coordinated framework for planning and research of transnationally interconnected power system, and introduces the key technical models such as scenario building, generation-grid collaborative planning, and environmental climate-economic-social benefit analysis. An overall work process is designed based on the “ work system” and “support system”. Taking the temperature limit of the Paris Agreement as the objective, a scenario analysis is carried out, including global power demand, power supply mix, energy flow and other issues, and the comprehensive benefits are evaluated. Finally, the planning research methods are summarized and relevant suggestions are proposed.

The construction of intercontinental power grid interconnection projects is key to realizing the vision of Global Energy Interconnection, which is to solve global energy problems in a clean and sustainable manner. These projects may be influenced by a few factors that are neither technological nor economic, such as political, social, and international factors. This paper thus presents a multi-level model for recognizing which factor from a compiled list of 14 would impact a particular intercontinental interconnection project and for assessing the degree of the factor’s influence. In the first part of the model, the Analytic Hierarchy Process (AHP) method is used to recognize the project’s most significant impact factors. Using the recognition results, the second part of the model can assess the degree of the factor’s influence on the project based on ratings provided by experts. A comprehensive evaluation can thus be provided. As a case study, the proposed Saudi Arabia-Ethiopia power grid interconnection project connecting Asia and Africa was analyzed. Derived from a combination of multiple opinions from experts, evaluations from the model will be of direct benefit to decision-makers, investors, project implementers, and engineers, providing them with a deeper insight into the project.

Cross-border grid interconnection is a critical means to achieve wide-area share of hydro and other clean energy. Economic benefit assessment of cross-border grid interconnection projects should be carefully performed during early stage. In this paper, a method based on cost-benefit economic assessment for optimal planning of cross-border grid interconnection is proposed. An economic index for comprehensively assessing the cost of a transmission project and its resulting benefits of more usage of hydro energy is designed first. A chronological production cost simulation model considering hydro energy spillage due to transmission congestion and thermal operational limitation is then proposed to calculate the economic index. A case study is performed using the proposed method to determine the optimal capacity of a potential transmission link between Brazil and Argentina, which have rich and complementary hydro energy resources.

With the development of energy industry and infor-mation technologies, the concept of energy Internet is proposed to prevent the energy crisis and reduce the environmental pollution. However, the planning of energy Internet is facing great challenges that there are large uncertainties of boundary conditions in the planning. The collection of Internet information can help solve the problem. This paper introduces the method of collecting objective data from the Internet, such as renewable energy sources data, climate data, and economic data, and the usage of the data for energy Internet planning. The method of collecting and processing fuzzy information from the Internet are introduced as well. The events related to the energy Internet planning can be perceived and be applied to the multi-scenario planning of energy Internet. Besides, the difficulties and outlooks of the usages are given.

Considering the influence of natural disasters in power network planning stage is an effective way to prevent blackout.Firstly,the initial failure order is selected based on the failure probability;then rapid identification index and algorithm of line risk considering static load factor is established,and the corresponding calculation software is compiled based on PSD-BPA program to reduce the large amount of analytical calculation.Combined with power system stability guidelines,the selection rules of typical fault sets in disaster situations are presented.Based on the typical fault sets,the transient risk assessment of actual power system is calculated by BPA transient stability program.Example analysis shows that the common-used calculation method is easy to underestimate the system risk,while the proposed algorithm is more accurate and effective.

In order to solve the defect of tradition edge betweenness which takes the shortest path as the only path of power flow,this paper proposes the weighted maximum edge betweenness.This index considers both the influences of network topology and current operation mode on subarea division,which makes the subarea division is more suitable for real power network.Then,this paper proposes the ending criterion of subarea division to effectively utilize the key branches,which reduces the computation amount and prevents the isolated nodes from being a single zone.Finally,this paper obtains the transmission sections by searching the cut sets of network based on the subarea division.A case study of practical system verifies the feasibility of this method in key section search.Compared with the existing section search methods,the proposed method can get more fragile sections and neither depends on the selection of overload branches,nor requires the calculation of all cut sets,which can be better applied to the actual power grid.

Wavelet-based data compression methods are widely used for the data compression in power systems. There are two major problems of wavelet-based data compression techniques: there is no standard for the selection of best wavelet functions and decomposition scales; most of the existing wavelet-based data compression methods are only suitable for disturbance signals with abrupt change. This paper proposed a wavelet-based universal data compression method for different types of signals in power systems, including oscillations, such as low-frequency oscillations (LFOs) and sub-synchronous oscillations (SSOs), and disturbances. Based on compression ratios (CRs) and distortion rates (DRs), this paper constructed a compression distortion composite index (CDCI) for the evaluation of compression methods, with a balanced consideration of compression and accuracy. Based on CDCI, the best wavelet functions and decomposition scales for different signals can be selected from the candidates. The universality of the proposed method was verified by analyzing the compression of different typical actual recorded signals. The results indicated that the proposed method can provide high compression ratios and low distortion rates.

Through the study on the sensitivity of system reliability index to the grid-integration scale of electric vehicles (EVs),a quantitative evaluation method of system acceptance capacity of EVs can be established from a new point of view. First,a model of the charging load of EVs and an optimization strategy with time-of-use(TOU)price are established. Sec-ond,some indicators including maximum acceptance capacity and reliability sensitivity are proposed,which can quantita-tively characterize the system acceptance capacity of EVs. Finally,with the combination of the traditional reliability assess-ment method,the quantitative evaluation method of system acceptance capacity of EVs in an ordered charging mode is put forward,and importance sampling method is also used to improve the simulation efficiency. By means of an IEEE 24-RTS test system,the feasibility of the proposed indicators and method is verified. The proposed indicators and method can be ap-plied to actual grid to ensure the security and reliability of the system by controlling the grid-integration scale of EVs.

针对我国大规模风电接入地区因系统调峰能力不足引起的大量弃风问题,提出采用大容量储能电池提高系统调峰能力、减少弃风损失的储能充放电策略。基于所提出的储能恒功率充放电策略,建立储能电站容量和布点优化的数学模型,并采用遗传算法进行求解。该模型以储能电站的投资和运行成本、网络损耗、调峰不足弃风及风电送出通道阻塞弃风损失之和最小为优化目标,考虑了储能电站的峰谷电价收益、计及了风力发电的碳减排效益,并满足电网的安全运行约束。最后,利用IEEE RTS79系统进行储能布局优化分析,验证了方法的有效性。应用该方法能够为解决大规模风电并网地区的弃风问题提供技术解决方案。

Application of battery energy storage systems (BESS) could help reducing wind power curtailment. Due to the uncertain nature of wind power as well as conventional generation and loads, it is more reasonable and accurate to determine the quantitative requirement for BESS probabilistically. Moreover, the effectiveness of using BESS to reduce wind power curtailment is affected by their charging and discharging control strategies. In this paper, a method based on sequential Monte Carlo simulation (SMCS) is proposed for probabilistically analyzing the requirement for BESS. Three practical charging and discharging control strategies of BESS are also proposed and compared both qualitatively and quantitatively as for their effectiveness in reducing wind power curtailment. The proposed method and control strategies are tested in a real large power system in northwest China.

By studying on the coordination between the system reliability level and the EV grid-integration scale, the system acceptance capacity of EVs can be assessed from a new point of view. In this paper, a model for the charging loads of three types of EVs and a coordinated strategy with time-of-use price (TOU) are established. Then, the maximum acceptable capacity, reliability sensitivity and other indicators are proposed to quantitatively characterize the system ability to accommodate EVs. Subsequently, by combining the acquired EV charging load algorithm with the traditional reliability assessment method, the quantitative evaluation approach of the system acceptance capacity of EVs considering coordinated strategy is proposed. In order to improve the simulation efficiency, the Latin hypercube method is used to sample the system state. The feasibility of proposed indicators and method is verified with test results of the IEEE24-RTS system. Furthermore, different cases are comparatively analyzed with and without the coordinated strategy, respectively. Results prove that the coordinated strategy can improve the system reliability level, and greatly enhance the system acceptance capacity of EVs.