储能具备灵活的功率调节与电能时移能力，其与系统多类型调控资源的协调优化有望为新型电力系统低碳、经济、可靠运行提供有力支撑。针对储能提升高比例新能源基地低碳、经济、可靠性能的效益进行研究。首先，建立了高比例新能源基地发电碳排放计量模型，提出高比例新能源基地低碳、经济、可靠性能量化评估指标；其次，建立了储能与高比例新能源基地的联合运行模拟模型，为含储能高比例新能源基地的优化运行提供决策依据；最后，针对蒙西区域电网开展全年时间尺度精细化运行模拟，分析不同储能容量配比下对系统低碳、经济、可靠运行性能的提升效益。算例结果验证了所提运行模拟模型的有效性，并指出随储能容量提升其对系统低碳、低碳、经济及可靠性能提升的边际效益逐步下降，优化制定储能配置容量有利于最大化其投资运行效益。

Energy storage possesses flexible power regulation and energy time-shifting capabilities, and its coordination and optimization with multiple types of regulatory resources in the system is expected to provide strong support for the low-carbon, economic, and reliable operation of new power systems. Research on the benefits of low-carbon, economic, and reliable performance of high proportion renewable energy bases for energy storage improvement is conducted. Firstly, a carbon emission measurement model for power generation in high proportion renewable energy bases is established, and evaluation indicators for low-carbon, economic, and reliable energy utilization in high proportion renewable energy bases are proposed. Secondly, a joint operation simulation model is established for energy storage and high proportion renewable energy bases, providing decision-making basis for the optimized operation of renewable energy bases with high proportion of energy storage. Finally, a fine-grained annual time scale operation simulation will be conducted for the Mengxi regional power grid to analyze the benefits of improving the low-carbon, economic, and reliable operation performance of the system under different energy storage capacity ratios. The calculation results have verified the effectiveness of the proposed operational simulation model and pointed out that as the energy storage capacity increases, the marginal benefits of improving the low-carbon, economic, and reliable performance of the system gradually decrease. Formulation optimization of energy storage configuration capacity is beneficial for maximizing its investment and operational benefits.

目的 电池储能是保证光伏发电系统可靠性、提高光伏发电利用率的有效手段之一，但在光储电站中存在功率波动平抑难、储能容量配置不合理等问题，为解决这些问题，开展了相关研究。 方法 针对能量型电池储能，分析了调度模式和自主模式特性，提出了一种基于储能运行在调度模式的光储系统限功率平抑策略，以实现功率平抑和减少储能充放电频繁切换。建立了以最小光储系统弃电损失为优化目标，以功率波动越限概率等作为约束条件的优化模型，并利用算法对储能配置进行求解和优化。以西藏朗明桑珠孜50 MW光储电站为例，验证了所提平抑策略的有效性。 结果 所提平抑策略在不增加储能充放电切换次数的前提下，将光储系统并网功率波动越限概率由25.64%降至6.41%，且并网功率波动越限概率为5%时，该50 MW并网光伏电站储能系统最优配置为14.5 MW/94 MW⋅h。 结论 所提抑策略及储能优化配置方法可为并网光储电站优化设计和运行提供技术参考。

Objectives Battery energy storage system is one of the effective means to ensure the reliability of photovoltaic (PV) power generation system and improve the utilization rate of PV power generation. However, there are some problems in the PV-energy storage power station, such as the difficulty of power fluctuation suppression and the unreasonable configuration of energy storage capacity. In order to solve these problems, relevant research was carried out. Methods For energy-based battery energy storage, the characteristics of scheduling mode and autonomous mode were analyzed, and a power-limited suppression strategy of PV-energy storage system based on energy storage operation in scheduling mode was proposed to realize power suppression and reduce the frequency of energy storage charge/discharge switching. The optimization objective of minimizing abandoned power losses in the PV-energy storage system was established, with constraints such as the probability of power fluctuation exceeding the limit. An algorithm was used to solve and optimize the energy storage configuration. Taking the 50 MW Sangzhuzi PV-energy storage power station in Langming, Tibet as an example, the effectiveness of the proposed grid-connected power suppression strategy was validated. Results The proposed grid-connected power suppression strategy can reduce the probability of power fluctuation exceeding the limit from 25.64% to 6.41% without increasing the frequency of energy storage charge/discharge switching. When the probability of grid-connected power fluctuation exceeding the limit is 5%, the optimal configuration for the energy storage system of the power station is determined to be 14.5 MW/94 MW⋅h. Conclusions The proposed power fluctuation suppression strategy and energy storage optimization configuration method can provide technical reference for the optimal design and operation of grid-connected PV-energy storage system.

With the establishment of the "double carbon" goal, various industries are actively exploring ways to reduce carbon emissions. Cloud data centers, represented by cloud computing, often have the problem of mismatch between load requests and resource supply, resulting in excessive carbon emissions. Based on this, this paper proposes a complete method for cloud computing carbon emission prediction. Firstly, the convolutional neural network and bidirectional long-term and short-term memory neural network (CNN-BiLSTM) combined model are used to predict the cloud computing load. The real-time prediction power is obtained by real-time prediction load of cloud computing, and then the carbon emission prediction is obtained by power calculation. Develop a dynamic server carbon emission prediction model, so that the server carbon emission can change with the change of CPU utilization, so as to achieve the purpose of low carbon emission reduction. In this paper, Google cluster data is used to predict the load. The experimental results show that the CNN-BiLSTM combined model has good prediction effect. Compared with the multi-layer feed forward neural network model (BP), long short-term memory network model (LSTM ), bidirectional long short-term memory network model (BiLSTM), modal decomposition and convolution long time series neural network model (CEEMDAN-ConvLSTM), the MSE index decreased by 52, 50, 34 and 45 respectively.© 2024. The Author(s).