（记者 王晓波） 每经头条（nbdtoutiao）——核电建设热潮下，设备厂忙到"飞起"！订单已排至2028年，员工三班倒， 产线24小时不停 每经AI快讯，上海电力1月30日晚间发布业绩预告，公司预计2025年度实现归属于上市公司股东的净利 润为25.11亿元到29.88亿元。与上年同期相比，将增加4.65亿元到9.42亿元，同比增加22.71%~46.03%。 业绩变动主要原因是，公司扎实开展提质增效工作，强化全要素挖潜，燃料成本、资金成本等持续下 降。为客观反映公司资产状况和经营成果，确保会计信息真实可靠，公司按照《企业会计准则》和公司 财务制度的相关规定，对存在减值迹象的资产采取必要的减值测试和评估。2025年度拟计提应收款项信 用减值损失约3亿元。 ...

证券简称：上海电力 证券代码：600021 编号：临 2026-007 （一）业绩预告期间 2025 年 1 月 1 日至 2025 年 12 月 31 日。 （二）业绩预告情况 上海电力股份有限公司 2025 年年度业绩预告 本公司董事会及全体董事保证本公告内容不存在任何虚假记载、误导性陈述 或者重大遗漏，并对其内容的真实性、准确性和完整性承担法律责任。 重要内容提示 1.公司预计2025年度实现归属于上市公司股东的净利润为25.11亿元到 29.88亿元。与上年同期（法定披露数据）相比，将增加4.65亿元到9.42亿元， 同比增加22.71%到46.03%。 2. 公司2025年度实现归属于上市公司股东的扣除非经常性损益的净利润预 计为23.50亿元到27.97亿元。与上年同期（法定披露数据）相比，将增加4.55 亿元到9.02亿元，同比增加24.03%到47.60%。 一、本期业绩预告情况 （一）公司扎实开展提质增效工作，强化全要素挖潜，燃料成本、资金成本 等持续下降。 经财务部门初步测算，公司预计 2025 年度实现归属于上市公司股东的净利 润为 25.11 亿元到 29.88 亿元。与上年同期（法定 ...

专利摘要显示，本发明涉及电动汽车与电网协同规划技术领域，具体提供基于历史发展特征与饱和状态 的电动汽车规模预测方法，包括构建Verhulst模型的微分方程，将累加序列带入微分方程，得到累加序 列的预测值，包括：将微分方程离散化，通过拟合得到初始增长速率参数和初始饱和抑制参数；通过遗 传算法对初始增长速率参数和初始饱和抑制参数进行优化，得到优化增长速率参数和优化饱和抑制参 数；将优化增长速率参数和优化饱和抑制参数带入Verhulst模型的时间响应公式，得到累加序列的初始 预测值；通过充电设施覆盖率对初始预测值进行修正，得到累加序列的预测值；对累加序列的预测值进 行处理，得到电动汽车的规模预测序列；解决因电动汽车增长的非线性特性难以准确预测的问题。 国家知识产权局信息显示，国网上海市电力公司;清华四川能源互联网研究院申请一项名为"基于历史发 展特征与饱和状态的电动汽车规模预测方法"的专利，公开号CN121413447A，申请日期为2025年11 月。 声明：市场有风险，投资需谨慎。本文为AI基于第三方数据生成，仅供参考，不构成个人投资建议。 财经频道更多独家策划、专家专栏，免费查阅>> ...

Core Insights - Elon Musk stated that China's decisive advantage in the AI race lies in its large-scale power supply capabilities, highlighting the critical role of electricity in AI development [2] - The rapid advancement of AI technology has led to explosive growth in data center construction, which significantly increases electricity demand and is a major driver of power consumption [2] Industry Overview - The electricity demand driven by data centers is becoming a core growth engine, contributing to the power supply gap [2] - The current valuation of the electricity sector is at a historical low, with the China Securities Index for public utilities showing a price-to-earnings ratio (PE-TTM) of approximately 17 times, below most of the past decade's valuation levels, indicating a certain margin of safety [10][16] ETF and Market Composition - The Huabao Electric ETF tracks the China Securities Index for public utilities, which includes various power generation methods: thermal power (40.81%), hydropower (24.81%), wind power (14.25%), nuclear power (11.83%), and solar power (6.87%) [6][14] - The top ten weighted stocks in the index include leading companies such as Changjiang Electric Power, China Nuclear Power, and Three Gorges Energy, collectively accounting for 52.07% of the index [7][14] Key Stocks and Market Data - Key stocks in the index include: - Changjiang Electric Power: Market Cap 665.29 billion, Weight 10.02% [8] - China Nuclear Power: Market Cap 177.91 billion, Weight 8.36% [8] - Three Gorges Energy: Market Cap 116.92 billion, Weight 6.87% [8] - Guodian Power: Market Cap 89.89 billion, Weight 5.28% [8] - The index is classified into four levels by the China Securities Index Company, with data as of December 31, 2025 [6][14]

Group 1 - The core viewpoint of the news highlights a decline in the National Green Power Index by 1.44%, with major stocks like Tianfu Energy and others experiencing significant drops amid rising electricity demand due to winter conditions [1] - The national peak electricity load has surpassed 1.417 billion kilowatts for the first time in winter, with a rapid increase of 150 million kilowatts within three days, driven by cold weather [1] - A joint guideline for "Zero Carbon Factory Construction" has been issued, aiming to select benchmark zero-carbon factories starting in 2026, particularly in key industries such as photovoltaics and lithium batteries, to support green electricity consumption and demand growth [1] Group 2 - In 2025, the national electricity market transaction volume reached 66,394 billion kilowatt-hours, a year-on-year increase of 7.4%, with green electricity transaction volume at 3,285 billion kilowatt-hours, up 38.3%, indicating a maturing market mechanism [1] - The top ten weighted stocks in the National Green Power Index as of December 31, 2025, include major companies like China Nuclear Power and Yangtze Power, collectively accounting for 54.68% of the index [2] - The Green Power ETF (159625) closely tracks the National Green Power Index, providing a convenient tool for investors to gain exposure to the overall performance of green power-related listed companies [2]

Group 1 - The core viewpoint of the articles highlights the increasing electricity demand in China, driven by the rapid growth of AI, with the national winter electricity load surpassing 1.417 billion kilowatts for the first time [1] - The actual reserve rate of the electricity system is under pressure during the 14th Five-Year Plan period, indicating a tightening supply-demand balance in the electricity sector [1] - By 2025, the total electricity consumption in China is expected to exceed 10 trillion kilowatt-hours, reflecting continuous industry demand expansion [1] Group 2 - The article suggests that the improvement of capacity pricing and green electricity trading mechanisms, along with rising electricity price standards, will enhance the profitability stability of the electricity industry [1] - The market is shifting towards dividend value, making the electricity sector's allocation value more apparent [1] - The article recommends focusing on the Huabao Electric ETF (159146), which covers various electricity utility sectors, including thermal, hydro, wind, nuclear, and solar power, benefiting from AI-driven energy opportunities and electricity reform policies [1] Group 3 - On January 27, the A-share market experienced a general pullback, with the electricity sector weakening and all constituent stocks declining [3] - Among the notable declines, Jiaze New Energy fell by 5%, while Shanghai Electric, Xiexin Energy Technology, and JinkoSolar dropped by 4% [3] - The Huabao Electric ETF (159146) saw a decline of over 1%, reaching a new low since its listing, although there was a significant inflow of 8 million shares, indicating investor interest in future AI-driven energy opportunities [3]

27日早盘，A股普遍回调，电力板块走弱，成份股全线飘绿。其中，嘉泽新能领跌5%，上海电力、协 鑫能科、晶科科技等多股下挫4%。热门ETF方面，电力ETF华宝（159146）场内价格跌逾1%下探上市 新低，资金进场揽筹800万份，或看好未来AI驱动下的能源机遇。 | | | 分时 多日 1分 5分 15分 30分 ■ | | | | | | | F9 盘船盘后 露加 九转 画纸 工具 @ 2 > | | | 电力ETF华审 | | 159146 | | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | | 1.028 | | | | | | 159146(电力ETF华应] 09:59 价 0.996 涨跌 -0.015(-1.48%) 均价 1.002 服交量 84 | | | | | | 0.996 | | -0.015 -1.48% | | | | | | | | | | | | | | SZSE CNY 9-59-39 DURCH | | / 0 + | | 1.019 | | ...

本报记者 杜雨萌 1月份以来，受寒潮天气影响，我国用电需求持续攀升，先后创下冬季单日用电量突破300亿千瓦时、全国电力负荷突破14 亿千瓦的纪录。其中，入冬以来，华北、西北、东北等3个区域电网和新疆、西藏等12个省级电网负荷75次创历史新高，对迎 峰度冬保暖保供形成严峻考验。 燃煤是冬季供热的"口粮"，对于承担超9.6亿平方米民生供热任务的中国大唐集团有限公司（以下简称"中国大唐"）而言， 确保燃煤库存足、供应稳，是其筑牢供热根基的关键。 记者从中国大唐获悉，作为京津唐电网关键电源支撑点，内蒙古大唐国际托克托发电有限责任公司承担着呼和浩特市总面 积达6300万平方米区域的供热使命。截至目前，燃料库存可用天数在20天以上，为冬储煤库存稳步提升提供了可靠支撑。大唐 黑龙江发电有限公司哈尔滨第一热电厂利用厂外储煤利好政策，存煤量同比增长20%，创建厂以来同期最高水平。大唐国际发 电股份有限公司张家口发电分公司坚持"优质长协+低价市场"采购模式，单日卸煤最高达4.06万吨。大唐鸡西第二热电有限公司 全面优化库存煤结构，当前储煤量可满足30天用煤需求，为供热备足"口粮"。总的来看，本次供热季以来，中国大唐供热达 186 ...

Group 1 - The core issue revolves around the crackdown on stock influencers (known as "大V") who have been manipulating the market and misleading retail investors, leading to significant financial losses for the latter [2][3][37] - On January 19, the Zhejiang Securities Regulatory Bureau issued a penalty of over 83 million yuan to a stock influencer named Jin Yongrong, also known as "Jin Huo," for market manipulation [3][39] - The regulatory actions included the permanent banning of 22 influencer accounts on the Snowball platform, which were known for long-term stock recommendations and had large followings [2][37][61] Group 2 - Jin Yongrong's account had approximately 130,000 followers and was involved in promoting stocks across multiple platforms, including WeChat and Xiaohongshu, significantly increasing his influence [4][39] - His trading activities included buying stocks before recommending them and then selling them at a profit to retail investors, which led to a calculated illegal gain of approximately 41.6 million yuan [8][41][42] - The regulatory body emphasized that disclaimers in his posts did not absolve him of responsibility, as they were merely formalities that did not change the nature of his actions [7][40] Group 3 - Other platforms like Ant Group, Douyin, and Tencent have also announced measures to combat misleading financial content, with Ant Group reporting the removal of over 58,000 pieces of illegal financial promotional content [28][32][61] - The crackdown is part of a broader initiative to address issues such as excessive speculation, inducement of follow-on trading, and the dissemination of false information in the capital markets [26][59] - The actions taken against these influencers reflect a growing concern over the integrity of the capital markets and the protection of retail investors from fraudulent practices [2][37][58]

Group 1 - Regulatory actions have intensified against stock influencers, with a notable case involving a prominent influencer fined 83 million yuan for market manipulation [1][2][11] - The Zhejiang Securities Regulatory Bureau identified the influencer, Jin Yongrong (known as "Jin Huo"), as having manipulated the market through repeated stock recommendations, significantly impacting stock prices and trading volumes [6][10] - Jin Huo's activities included promoting stocks across multiple platforms, leading to a surge in followers and engagement, particularly after a viral article on the new energy sector [4][5] Group 2 - The crackdown on influencers has led to the permanent banning of 22 accounts on the Snowball platform, which were involved in misleading stock recommendations [1][31] - Major platforms like Ant Group, Douyin, and Tencent have also announced initiatives to combat fraudulent financial content, with significant numbers of accounts being penalized for spreading false information [31][32] - The regulatory focus includes addressing excessive speculation, illegal investment consulting, and the dissemination of false information, indicating a broader effort to stabilize the capital market [30][32] Group 3 - The case of Jin Huo exemplifies a larger trend where influencers engage in practices that mislead retail investors, often resulting in significant financial losses for those who follow their advice [12][20] - Another influencer, known as "Chen Xiaoqun," has been implicated in market manipulation, with reports of aggressive trading strategies that have led to substantial losses for retail investors [20][28] - The volatility of stocks promoted by these influencers has raised concerns about the integrity of the market, as evidenced by drastic price fluctuations following their recommendations [34]