基于在线优化的风电场POWER-SONIC蓄电池-氢混合储能系统抑制并网功率偏差研究
2026-06-08 20:41:27 点击： 次
为处理风电场并网功率误差的多氢储与电池储能单元协同操控问题，本研讨提出一种根据丈量反应的电池-氢混合储能体系在线优化战略。首先，鉴于氢储能充放电损耗较高且电池储能能量密度较低的特色，建立了使电池-氢混合储能体系完成自适应能量调理的运转优化方针。随后，构建了一个以最小化混合体系运转本钱为方针的在线优化模型，在满足氢储能与蓄电池运转束缚条件下按捺并网功率误差。终究，使用氢储能与蓄电池能量状况的在线丈量数据，规划了一种根据丈量反应的在线优化战略。事例研讨结果表明：在平滑风电动摇前后，功率超出并网功率上下限的时刻别离占总时长的24.1%与1。45%，所提战略能有用将风电场并网功率误差操控在允许范围内。氢储能与蓄电池别离承担长周期与短周期充放电使命，明显下降了电池-氢混合储能体系的充放电损耗并提高其运转功率。
风能与其它可再生动力的开发与使用对完成低碳方针至关重要。但是受风速等天然因素影响，风力发电具有不确定性与间歇性[1]，当大比例风电接入电网时会对电力体系安全运转构成明显威胁，从而约束风能的大规模开发与使用。氢储能与电池储能可完成电能的时刻转移并具有快速呼应特性[2]，有用缓解并网风电功率动摇，使其成为保障大规模风电并网安全运转的有用处理方案。由电池储能与氢储能构成的混合储能体系，可以互补不同类型储能的优劣势，处理单一类型储能存在的缺陷[3]，提高储能体系全体性能[4]。针对此类多类型储能体系，规划有用的操控战略至关重要。
At present, a lot of research results have been made in the research on long-term energy storage to solve the problem of supply and demand imbalance. In reference [5], an hourly-level coordinated optimization strategy for a Battery-hydrogen integrated system, including hydrogen fuel vehicles, was proposed. Reference [6] presented an improved bi-level robust planning approach to smooth the fluctuations of renewable energy generation, maximizing the complementary benefits of Battery-hydrogen energy storage. Reference [7] proposed a dual-battery energy storage model and compared two switching strategies, synchronous and asynchronous, to reduce the switching frequency in a single-battery mode. Reference [8] proposed a multi-time-scale rolling optimization control method based on the rolling optimization idea of model predictive control to address the low reliability of optimization results due to uncertainties in wind and solar output and load. Reference [9] presented an energy storage response strategy aiming to minimize the cost of a hybrid energy storage system, based on the multi-time-scale demand of users. Reference [10] proposed a peak-shaving and valley-filling strategy for a park energy system with a Battery-thermal hybrid energy storage system. Reference [11], in light of the escalating penetration of renewable energy to counterbalance the variability of wind and solar energy and the demand issue for compressed air energy storage capacity, has formulated a least-cost power system founded on the combination of wind, solar, and compressed air energy storage technologies. Reference [12], for the research concerning the utilization of a substantial amount of energy storage to mitigate the variability of wind and solar power systems, has put forward a novel least-cost approach. Through the comparative analysis of the above literature, the comparison results are shown in Table 1.
表1. 根据长时刻标准的不同储能方式比照[5,7,10]
| 参数 | 电池-氢能-热能Multi动力体系 | 双电池-氢能混合储能体系 | 电池-氢混合储能体系 |
|---|---|---|---|
| 电池储能容量/功率 | 1 兆瓦/2 兆瓦时 | 4 兆瓦/8 兆瓦时 | 2 兆瓦/4 兆瓦时 |
| 氢能储存容量/功率 | 7兆瓦/9米3/7兆瓦 | 30兆瓦/35米3/30兆瓦 | 15兆瓦/15米3/16 MW |
| 寿数（年） | 10年 | 5–25 年 | 5–10 年 |
| 产氢才能（Nm3/h） | 1400 | 2500 | 200 |
| 功率（%） | 60–95 | 72–95 | 65–95 |
| 功率密度（W/cm2) | 0.1–0.3 | 0.1–0.5 | 0.1–0.4 |
| 能量密度（Wh/kg） | 150–200 | 100–120 | 120–200 |
上述研讨探讨了长时间储能体系的运转优化战略，但其时刻标准大多在小时级以上，难以应对更短时刻标准的操控使命。针对此问题，文献[13]提出了一种适用于电池-氢混合储能体系的二级协调运转办法，该办法可优化荷电状况、进步可再生动力使用率，一起下降体系运转本钱。文献[14]提出了一种混合储能协调战略，用于平滑光伏并网功率动摇并下降混合储能体系的运转损耗。参考文献[15]提出了一种快速操控战略，旨在下降电池储能充放电循环频率。参考文献[16]构建了考虑负荷侧需求呼应与电热装备用户群的概括动力体系氢储能双层优化模型，该模型可提高新动力消纳水平。参考文献[17]提出了一种考虑多时刻标准储能的概括动力微电网优化调度模型。18]建立了电池-氢混合储能微电网的多方针运转模型，该模型可进步清洁动力使用率并下降微电网运转本钱与用户用电费用。19]针对微型风氢耦合体系提出了一种猜测操控战略，明显提高了氢储能体系的调理才能。参考文献[20]提出了一种考虑碱性电解槽运转特性的电池-氢混合储能体系操控战略。文献[21]介绍了一种具有自适应时刻常数调理功用的多类型储能频率操控战略。上述针对电池-氢混合储能体系的短时标准（分钟级、秒级）操控战略有利于完成快速功率分配。但是，大多数战略仍依赖于滤波或启发式分配办法[22]，这约束了它们在特定操控方针和场景中的适用性。
为此，本文提出一种根据丈量反应的电池-氢混合储能体系在线优化战略。该战略可以快速优化多组电池与氢储能单元间的充放电功率分配，一起按捺风电并网误差。考虑风电并网误差按捺需求及电池/氢储能物理运转特性，构建了电池-氢混合储能体系自适应能量调整的在线优化模型。经过使用氢储能与电池储能单元能量状况的实时丈量数据，规划了根据丈量反应的在线优化战略。Simulation结果表明，所提战略能将风电并网误差有用按捺在允许范围内。氢能与电池储能别离承担长周期与短周期的充放电使命，从而下降储能体系全体充放电损耗并提高其运转功率。
本文的主要贡献整体可概括为以下三方面：
咱们开发了一种用于电池-氢混合储能体系能量自适应调理的在线优化模型。该模型使用氢储能平抑长时间风电动摇，选用电池储能缓解短期风电动摇。
（2）与启发式算法比较，本文提出的战略可以更快速地在多组储氢与电池单元之间进行功率分配，一起对优化方针和束缚条件具有更高的精度把控。
本文结构安排如下：第一部分介绍电池-氢混合储能体系的运转操控架构；第二部分详细讨论电池-氢混合储能体系模型，该模型概括考虑按捺风电并网功率误差的需求与电池储能、氢储能的物理运转特性。经过使用氢储能单元与电池储能单元能量状况的实时丈量数据，规划了一种根据丈量反应的在线优化战略。
The structure of this paper is organized as follows: The first section introduces the operational and control architecture of the Battery-hydrogen hybrid energy storage system. The second section discusses the model of the Battery-hydrogen hybrid energy storage system in detail, considering the need to suppress wind power grid-injected deviations and the physical operating characteristics of battery and hydrogen storage. By utilizing the real-time measurement of energy states in hydrogen and battery storage units, an online optimization strategy based on measurement feedback is designed. The third section conducts an analysis based on practical case studies by setting parameters for the wind farm energy storage station, analyzing the power and State of Health (SOH) of multiple hydrogen storage units, as well as the power and State of Charge (SOC) of the energy storage units. Finally, the fourth section summarizes the main research findings of this paper and outlines future research directions. The appendix includes the main proof processes and formula derivations.