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As the adoption of renewable energy sources grows, ensuring a stable power balance across various time frames has become a central challenge for modern power systems. In line with the "dual carbon" objectives and the seamless integration of renewable energy sources, harnessing the advantages of various energy storage resources and coordinating the operation of long-term and short-term storage have become pivotal directions for future energy storage deployment. To address the complexities arising from the coupling of different time scales in optimizing energy storage capacity, this paper proposes a method for energy storage planning that accounts for power imbalance risks across multiple time scales. Initially, the Seasonal and Trend decomposition using the Loess (STL) decomposition method is utilized to temporally decouple actual operational data. Subsequently, power balance computations are performed based on the obtained data at various time scales to optimize the allocation of different types of energy storage capacities and assess the associated imbalance risks. Finally, the effectiveness of the proposed approach is validated through hourly applications using real-world data from a province in southern China over recent years. [ABSTRACT FROM AUTHOR]

The demand for the power grid system's capacity to undergo peak-shaving is increasing as the proportion of renewable energy rises. In China, nuclear power units usually only provide a base load operation in the view of safety and economic considerations, but they do not provide load adjustment services, which undoubtedly increases the pressure of grid load adjustment. In this paper, a novel flexibility load adjustment strategy of the CHP nuclear unit is studied, which is achieved by introducing the thermal storage tank (TST) into the Rankine cycle without changing the output of the nuclear reactor. The AP1000 pressurized water reactor nuclear power unit for combined heat and power is taken as an example, and the thermodynamic model is established through the water vapor equation. Furthermore, the reference system is simulated for the goal of minimizing the imbalance between power supply and demand, and the flexibility–environment–economy benefits are evaluated. The results show that the heat storage/release of the TST may achieve power output flexible adjustment of the nuclear unit, and the power imbalance of the reference energy system is reduced from 1107.99 MWh to 457.24 MWh, a reduction of 58.73%. The introduction of a 600 MWh TST can enable the reference unit to contribute 335 MWh of peak electricity within the reference day. From the perspective of replacing the power generation output increment of coal-fired power units with equal amounts, it can achieve a reduction of 106.09 tons of coal consumption in the case day, which means that 277.73 tons of CO2 emissions can be reduced. The profit of the reference unit can be improved by CHY 70,125 via participating in load adjustment in the case day if following the time-of-use electricity price. [ABSTRACT FROM AUTHOR]

The large-scale centralized development of wind and PV power resources is the key to China's dual carbon targets and clean energy transition. The vast desert–Gobi–wilderness areas in northern and western China will be the best choice for renewable energy development under multiple considerations of resources endowment, land use constraints, technical conditions, and economic level. It is urgent to carry out a quantitative wind and PV resource assessment study in desert–Gobi–wilderness areas. This paper proposed a multi-dimensional assessment method considering the influence of the power grid and transportation infrastructure distributions, which includes three research levels, namely, the technical installed capacity, the development potential, and the development cost. Nine main desert–Gobi–wilderness areas were assessed. The wind and PV technical installed capacities were 0.6 TW and 10.7 TW, and the total development potentials were over 0.12 TW and 1.2 TW, with the full load hours of 2513 and 1759 and the average development costs of 0.28 CNY/kWh and 0.20 CNY/kWh. Finally, this paper proposed the meteorological–electrical division distribution. A case study in the Kubuqi and Qaidam Deserts was carried out on wind–wind and wind–PV collaborative development across different meteorological–electrical divisions, which can reduce by 58% the long-term energy storage capacity and decrease the total system LCOE from 0.488 CNY/kWh to 0.445 CNY/kWh. [ABSTRACT FROM AUTHOR]

With the increasing severity of climate change, the power industry, as one of the main sources of carbon emissions, is playing an extremely important role in the process of low-carbon energy transformation. The purpose of this paper is to try to find a general method to solve the optimal path for the low-carbon evolution of the power supply structure so as to meet the challenges faced by the low-carbon transformation of the power industry in the future. This paper first uses the capacity coefficient index (CCI) to represent the power generation ability of different technologies and proposes a forecasting method for the CCI of renewable energy generation. In this paper, a two-layer optimization model considering multiple constraints is established and solved using the MPC method. The results show that China's installed capacity of renewable power could account for more than 50% in 2030, while the carbon emissions will decrease after reaching a peak in 2023. On the premise of ensuring sufficient reserve adjustment capacity of thermal power units, increasing the proportion of renewable energy generation is an important way to realize emission reduction in the power industry. [ABSTRACT FROM AUTHOR]

Solar hydrogen production technology is a key technology for building a clean, low-carbon, safe, and efficient energy system. At present, the intermittency and volatility of renewable energy have caused a lot of "wind and light". By combining renewable energy with electrolytic water technology to produce high-purity hydrogen and oxygen, which can be converted into electricity, the utilization rate of renewable energy can be effectively improved, while helping to improve the solar hydrogen production system. This paper summarizes and analyzes the research status and development direction of solar hydrogen production technology from three aspects. Energy supply mode: the role of solar PV systems and PT systems in this technology is analyzed. System control: the key technology and system structure of different types of electrolytic cells are introduced in detail. System economy: the economy and improvement measures of electrolytic cells are analyzed from the perspectives of cost, consumption, efficiency, and durability. Finally, the development prospects of solar hydrogen production systems in China are summarized and anticipated. This article reviews the current research status of photovoltaic-photothermal coupled electrolysis cell systems, fills the current research gap, and provides theoretical reference for the further development of solar hydrogen production systems. [ABSTRACT FROM AUTHOR]

To address the complexity of siting and sizing for the renewable energy and energy storage (ES) of offshore oil–gas platforms, as well as to enhance the utilization of renewable energy and to ensure the power-flow stability of offshore oil–gas platforms, this paper proposes a hierarchical clustering-and-planning method for wind turbine (WT)/photovoltaic (PV) ES. The proposed strategy consists of three stages. First, the WT/PV power generation is forecast by a LightGBM model. The WT/PV siting and sizing at each node of the distribution network is optimized with a particle swarm optimization (PSO) algorithm, with the objectives of economy and stability. In the second stage, the distribution network is partitioned into sub-clusters, based on a voltage and loss-sensitivity index. Finally, the ES siting and sizing is optimized with PSO to minimize the line loss and the voltage fluctuation for each sub-cluster. The relationship between the economic and stability indicators is conducted quantitatively in the joint-planning approach. Considering the 10 kV distribution network of an oil–gas platform in the Bohai Sea of China as an example, our experiments demonstrated that by adjusting the WT/PV ES capacity for different gas-turbine power outputs, line losses can be reduced by 55–66% and voltage fluctuations can be reduced by 30.4–47.5%. [ABSTRACT FROM AUTHOR]

The introduction of the new round of electricity reform policies has made the electricity sales companies' trading environment increasingly complex. In the medium- and long-term market and spot market, following the new policy-oriented optimization of trading decisions is the focus of electricity sales companies. The main objective of this study is to consider the impact of the latest policies of China's current electricity reform on each subject of electricity trading and to propose a method for electricity sales companies to make optimal decisions on renewable energy source (RES) power and conventional energy source (CES) power mixed with power trading in the medium- and long-term and spot markets to improve the efficiency of electricity market trading, promoting the consumption of renewable energy and helping the synergistic development of the electricity market and the tradable green certificate (TGC) market. This paper first discusses the impact of the new electricity reform policies on the transactions of various subjects in the electricity market and constructs the model of the consumer utility function, the profit model of an electricity sales company, and the profit model of power generators with energy storage. Considering the complex power supply and demand relationship among the various subjects of the electricity market, a game model is established for the decision on mixed trading between the medium- and long-term market, the spot market, and the tradable green certificate market to minimize the comprehensive power purchase cost of an electricity sales company. To reduce the decision-making risk caused by the uncertainty of spot price, the prophet model is used to predict the spot price; finally, through the analysis of the decision-making model of the electricity sales companies, the optimal transaction decisions of the electricity sales companies in different trading periods and different scenarios are solved. The test results show that the proposed model can significantly improve the profitability of the electricity sales companies and provide a decision-making reference for electricity sales companies to participate in the medium- and long-term market and spot market. [ABSTRACT FROM AUTHOR]

LVDC buildings use a low-voltage direct current (LVDC) distribution system for energy transmission and integrate photovoltaic (PV), battery energy storage (BES) and the utility grid as building energy resources. This technology can reduce energy loss in conversion to a certain extent and increase renewable energy compared with traditional AC distribution systems. Under the national goal of carbon peaking and carbon neutrality, LVDC buildings have been proven to be a new approach to energy conservation and emission reductions, and have been applied in engineering in China. However, the construction methods and integrated technologies of those projects are not clear, and technical barriers and policy constraints for the engineering application of LVDC buildings are not systematically discussed yet. This paper presents the latest study of LVDC building engineering applications the advantages and drawbacks of LVDC development in China. First, relevant policies and standards which support the development of LVDC building industries are summarized. More than 60 practical LVDC projects are investigated, and the application characteristics and the technology status of building types, and their capacity and design methods, etc., are analyzed. The attitudes of stakeholders toward LVDC buildings are surveyed to determine the policy direction according to the demands of this technology, with reference to building practitioners who intend to engage in LVDC projects. [ABSTRACT FROM AUTHOR]

The deployment of a green power alternative within an isolated network, powered by renewable energy sources, in the "Three North" region of China can facilitate the substitution of high-energy-consuming industrial loads with green power. However, an inadequate power supply configuration may lead to economic and reliability issues. To address this problem, effective capacity allocation within the green power alternative isolated network is proposed. The capacity allocation process starts with the design of a network structure that aligns with local conditions. Subsequently, a capacity allocation model is developed, considering economic factors, renewable energy utilization efficiency, and system reliability. The gray wolf optimizer is enhanced to establish a capacity allocation method for the green power alternative isolated network. This method is then employed to simulate and assess the performance of the network. The results indicate that the green alternative isolated grid can successfully facilitate green power substitution, satisfying the energy requirements of the loads. [ABSTRACT FROM AUTHOR]

The high demand for energy resources due to the increasing number of electronic devices has prompted the constant search for different or alternative energy sources to reduce energy consumption, aiming to meet the high demand for energy without exceeding the consumption of natural sources. In this context, the objective of this study was to examine research trends in the machine-learning-based design of electrical and electronic devices. The methodological approach was based on the analysis of 152 academic documents on this topic selected from Scopus and Web of Science in accordance with the preferred reporting items for systematic reviews and meta-analyses (PRISMA) statement. Quantity, quality, and structural indicators were calculated to contextualize its thematic evolution. The results showed a growing interest in the subject since 2019, mainly in the United States and China, which stand out as world powers in the information and communication technology industry. Moreover, most studies focused on developing devices for controlling, monitoring and reducing energy consumption, mainly in 5G and thermal comfort devices, primarily using deep-learning techniques. [ABSTRACT FROM AUTHOR]