为保障项目高标准落地，天合储能项目团队结合区域电网特性与气候条件，优化储能系统配置方案；组建专项服务小组，全周期响应物流供货、安装调试等 需求，以"量身定制、全程陪伴"的服务模式推动项目建设零阻碍推进。 项目建成投运后，年均放电量可达3650万度，约等于2万户城市家庭一年的全场景用电供给。项目的投运，将显著提升四川电网调峰能力与清洁能源消纳水 平，有力支撑内江打造"钒电池集成装备生产基地"与"全国新型储能应用场景示范基地"，为区域能源转型与产业高质量发展注入绿色动能。 责任编辑：闫弘旭 近日，四川省第一批新型储能示范项目——内江经开区100MW/200MWh钒锂储能电站（一期）项目成功投运。作为内江市首个电网侧独立储能电站，该项 目由国家电投投资建设，是"川渝能源一体化应急调峰基地"的关键组成部分。 该储能项目采用大容量储能系统，其电芯具备高安全、长循环、高效率、高经济性等多重优势，完美适配电网侧储能场景的调峰、应急响应等需求。相关设 备经过多轮严苛测试，可确保在复杂工况下稳定运行，为川渝地区能源结构优化与电力保供提供坚实的基础设施支撑。 ...

Core Viewpoint - The end of the mandatory energy storage policy marks a significant shift in the energy storage industry, prompting companies to adapt to market-driven dynamics rather than relying on policy incentives [1][4]. Market Transition - The new policy allows for a market-driven approach, with existing projects benefiting from a price guarantee while new projects will determine prices through competition [2][3]. - A "rush to install" is observed as companies expedite project completions to secure expected returns before the policy changes take full effect [2]. - Predictions indicate that China's new energy storage installations may exceed 30 GW this year, with cumulative capacity projected to reach between 236.1 GW and 291.2 GW by 2030 under different scenarios [3]. Technological Innovation - The removal of mandatory energy storage requirements necessitates that companies demonstrate their value in market-driven scenarios, focusing on technological advancements [4]. - Significant advancements in energy storage systems are evident, with standard container capacities exceeding 6 MWh, and some high-end products reaching over 9 MWh, doubling the capacity compared to 2023 [5]. - Innovations in battery cell technology, such as the introduction of 700 Ah long-cycle cells, enhance system efficiency and lifespan, with some systems achieving over 15,000 cycles [5][6]. AI Integration - The integration of AI into energy storage systems is emerging as a critical trend, with companies showcasing AI-driven management systems at industry events [7][8]. - AI technologies are enhancing operational efficiency, predictive maintenance, and safety monitoring, transforming energy storage systems into intelligent entities capable of autonomous decision-making [7][8]. - Challenges remain in data processing capabilities, which hinder the full potential of AI applications in the energy storage sector [8].