针对风光储场站中新能源出力波动及负荷扰动导致系统功率和频率变化的问题,提出多场景下混合储能协调控制策略。首先,针对混合储能过度充放的问题,提出混合储能功率分配策略,该策略通过模糊控制对低通滤波器的时间常数进行自适应调整,基于超级电容的荷电状态(state of charge, SOC)分为5个区域,每个区域根据SOC的变化实时调整时间常数,一定程度上保证了超级电容充放电的合理性;其次,针对混合储能主动支撑风光储场站频率问题,对混合储能逆变器采用虚拟同步机(virtual synchronous generator, VSG)控制,并对转动惯量和阻尼系数进行自适应调整,降低系统因功率扰动造成的频率最大偏差;最后,在PSCAD/EMTDC中搭建风光储场站的仿真模型,通过设置多个场景验证所提策略的有效性。

To address the problem of power and frequency changes caused by fluctuations in new energy output and load disturbances in wind and solar storage stations, a hybrid energy-storage (HES)-coordinated control strategy is proposed for multiple scenarios. First, a strategy for the power distribution of HES was proposed in response to the problem of excessive charging and discharging. This strategy adaptively adjusts the time constant of the low-pass filter using fuzzy control. Based on the state-of-charge (SOC) of the supercapacitor, it is divided into five regions, and each region adjusts the time constant in real-time based on the changes in SOC, ensuring the rationality of the charging and discharging of the supercapacitor to some extent. Second, to address the frequency issue of HES that actively supports wind-solar storage stations, virtual synchronous generator control is adopted for the HES inverter, and adaptive adjustments are made to the moment of inertia and damping coefficient to reduce the maximum frequency deviation caused by power disturbances in the system. Finally, a simulation model of the wind and solar storage station is built in PSCAD/EMTDC, and the effectiveness of the proposed strategy is verified by setting up multiple scenarios.

“双碳”背景下,配合分布式光伏规划开展储能规划是目前地市供电公司规划部门的重点工作之一。文章提出了面向分布式光伏消纳的中压配电网储能选址定容实用化模型和求解方法。首先利用生产模拟仿真分析分布式光伏并网对配电网的影响;其次基于鲁棒思想提出了场景削减方法,选取分布式光伏对配电网影响严重的场景集;最后提出了中压配电网选址定容的线性优化模型,以储能每小时最大充放电功率(电量)最小为目标,利用灵敏度系数法将线路过载和节点电压越限约束表达成储能充放电功率的线性函数。对改进的IEEE 33节点系统进行案例分析,研究表明文章提出的求解方法将双层优化问题化简成为单层优化问题降低了问题的复杂度,场景削减减少了约束条件数量,线性优化能快速有效地确定储能的位置和容量。

Under the dual carbon background, a key task of the planning department of the local power supply company is to carry out energy storage planning in conjunction with distributed photovoltaic planning. This paper presents a practical model and solution method for energy storage location and capacity determination for distributed photovoltaic consumption in medium-voltage distribution networks. First, production simulation is used to analyze the impact of distributed photovoltaic grid connection on the distribution network. Second, a scenario reduction method is proposed based on a robust idea, whereby the scenario with the most serious impact on distributed photovoltaic consumption in a distribution network is selected. Finally, a linear optimization model is proposed for the location and capacity of the medium-voltage distribution network. With the goal of minimizing the maximum charging and discharging power (electricity) per hour of energy storage, the line overload and out-of-limit node voltage constraints are expressed as a linear function of the charging and discharging power of energy storage, using the sensitivity coefficient method. The case study of the improved IEEE33 bus system shows that the solution method proposed in this paper reduces the complexity of the problem by simplifying the two-layer optimization problem into a single-layer, thereby reducing the number of constraints by narrowing the scenarios for linear optimization to quickly and effectively determine the location and capacity of energy storage.

Little has been done in the study of these intriguing questions, and I do not wish to give the impression that any extensive set of ideas exists that could be called a "theory." What is quite surprising, as far as the histories of science and philosophy are concerned, is that the major impetus for the fantastic growth of interest in brain processes, both psychological and physiological, has come from a device, a machine, the digital computer. In dealing with a human being and a human society, we enjoy the luxury of being irrational, illogical, inconsistent, and incomplete, and yet of coping. In operating a computer, we must meet the rigorous requirements for detailed instructions and absolute precision. If we understood the ability of the human mind to make effective decisions when confronted by complexity, uncertainty, and irrationality then we could use computers a million times more effectively than we do. Recognition of this fact has been a motivation for the spurt of research in the field of neurophysiology. The more we study the information processing aspects of the mind, the more perplexed and impressed we become. It will be a very long time before we understand these processes sufficiently to reproduce them. In any case, the mathematician sees hundreds and thousands of formidable new problems in dozens of blossoming areas, puzzles galore, and challenges to his heart's content. He may never resolve some of these, but he will never be bored. What more can he ask?