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建筑中电池储能系统的能量管理与控制:实验验证与盈利性评估
Energy Management and Control of Battery Storage Systems in Buildings: Experimental Validation and Profitability Assessment
| 作者 | Lysandros Tziovani · Lenos Hadjidemetriou · Stelios Timotheou |
| 期刊 | IEEE Transactions on Industry Applications |
| 出版日期 | 2025年8月 |
| 技术分类 | 储能系统技术 |
| 技术标签 | 储能系统 |
| 相关度评分 | ★★★★★ 5.0 / 5.0 |
| 关键词 | 电池储能系统 能量管理 优化方案 模型预测控制 财务分析 |
语言:
中文摘要
电池储能系统(BESS)可集成到建筑物中,以在可变电价方案下降低电费成本。然而,电池老化以及电池 - 逆变器组合系统的非线性效率给电池储能系统的优化管理带来了重大挑战。本研究针对建筑物中的电池储能系统,考虑电池老化和近似的逆变器 - 电池功率损耗模型,开发了一种能量管理优化方案。所提出的方案被构建为一个线性规划问题,可在长期时间范围内快速且可靠地求解,使其可用于运行和规划策略。利用该优化方案,提出了一种模型预测控制(MPC)方法,以解决因使用近似功率损耗模型而产生的建模误差问题。此外,利用该优化模型进行了财务分析,基于一栋住宅建筑的实际数据,通过计算净现值和内部收益率来评估电池储能系统的长期盈利能力。开发了一个集成了模型预测控制方法的实验装置,用于在能量管理应用中对实际电池储能系统进行监测和控制。实验结果验证了所提出的模型预测控制方法在存在建模误差的情况下,对实际电池储能系统进行有效管理、控制和运行的有效性。
English Abstract
Battery energy storage systems (BESSs) can be integrated into buildings to reduce the electricity cost under variable electricity pricing schemes. However, battery degradation and the nonlinear efficiency of combined battery-inverter systems pose significant challenges to the optimal management of BESSs. This work develops an optimization scheme for the energy management of BESSs in buildings considering battery degradation and an approximate inverter-battery power loss model. The proposed scheme is formulated as a linear program that can be solved fast and reliably over long-term time horizons, enabling its usage for both operating and planning strategies. Using the optimization scheme, a model predictive control (MPC) approach is proposed to address modeling inaccuracies arising from the utilization of the approximate power loss model. Moreover, a financial analysis is performed using the optimization model to assess the long-term BESS profitability by calculating the net present value and internal rate of return based on real data from a residential building. An experimental setup that integrates the MPC approach is developed to enable the monitoring and control of a real BESS in energy management applications. Experimental results validate the effectiveness of the proposed MPC approach to effectively manage, control, and operate a real BESS under modeling inaccuracies.
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SunView 深度解读
该建筑储能能量管理技术对阳光电源ST系列储能变流器和PowerTitan系统具有重要应用价值。研究中的优化控制策略可直接应用于C&I工商业储能场景,通过精准的峰谷套利算法和电池寿命管理模型,提升iSolarCloud云平台的智能调度能力。文章验证的电池老化与经济性平衡方法,可优化阳光电源ESS集成方案中的BMS与EMS协同控制策略,特别是在分时电价机制下实现充放电策略的动态优化。该技术还可与SG系列光伏逆变器形成光储一体化解决方案,通过实验验证的盈利性评估模型为客户提供精准的投资回报分析,增强阳光电源在建筑储能市场的竞争力。