Investment Impact Analysis of Hypothetical 2025 'Document No.136' Energy Policy Scenario

The following analysis is based on the policy scenario framework you provided (hypothetical impact of the 2025 “Document No.136”) combined with accessible public market information (web searches). Regarding the “2025 Document No.136” itself, the inter-provincial consumption ratios you mentioned (e.g., “Zhejiang 90%, Gansu 10%”) and the claim that “new projects may face electricity prices as low as a few cents or negative prices”, no authoritative sources have been found in verifiable public materials so far. The following analysis treats these as hypothetical/scenario descriptions you provided, not confirmed facts. The core conclusions rely on the combined deduction of this scenario and market facts, rather than treating “Document No.136” or specific provincial figures as verified policies.

1. Alignment of Scenario Framework with Verifiable Market Facts

• Policy assumptions you provided:
  • Taking June 1, 2025 as the cutoff: Projects connected to the grid before this date are “old projects” and enjoy protected mechanism-based electricity prices; those after are “new projects” that must participate in market bidding, potentially facing low or even negative electricity prices.
  • Significant differences in renewable energy consumption ratios across provinces (you cited examples like high in Zhejiang and low in Gansu), which will lead to differentiated project returns.
  • Coal power shifts to peak and frequency regulation roles with guaranteed minimum returns, increasing relative certainty.
• Corroboration with market facts:
  • Bloomberg reports that China’s fossil fuel power generation has dropped for the first time in a decade, with large-scale grid connection of renewable energy to meet rising demand [1].
  • Forbes also notes that the broad rally in the energy sector driven by AI electricity demand is unsustainable, and different sub-sectors will differentiate [2].
  • Forbes further points out that global clean energy investment and power demand (especially growth from data centers) will expand rapidly in 2025, with power grids and energy storage becoming key bottlenecks and value drivers [3].

2. Investment Impact of This Hypothetical Scenario (Scenario Logic and Verification Directions)

1. Renewable energy generation projects (including wind and solar):
   • The scenario advantage of “old projects” lies in protected mechanism-based electricity prices + relatively high consumption rates, leading to higher revenue certainty; screening should prioritize:
     • Existing installed capacity and project portfolios connected to the grid before June 1, 2025;
     • Provinces with high-quality consumption (e.g., load centers, regions with sufficient cross-provincial transmission channels and supporting flexible adjustment resources, but specific provincial consumption capacity and electricity price systems need to be verified);
     • Enterprises with stable cash flow, high dividend rates, controlled liabilities, and good asset quality.
   • “New projects” face bidding risks and potential low/negative electricity prices; investment logic will emphasize extreme cost optimization and supporting flexible adjustment capabilities. Verification directions:
     • Leading LCOE and levelized cost of electricity;
     • Collaboration with energy storage and power grids (spot/ancillary service market strategies) to achieve higher price spread returns during peak hours;
     • Cross-regional asset diversification and market diversification (e.g., multi-category revenue from green electricity/green certificates/ancillary services).
2. Coal power and flexible adjustment resources:
   • Under the hypothetical scenario, coal power is repositioned as “regulation and minimum guarantee”, with guaranteed minimum returns and increased value from capacity/ancillary services. Verification directions:
     • Peak and frequency regulation capabilities and bidding strategies;
     • Substantive implementation and sustainability of policy mechanisms (capacity compensation, reserve/frequency regulation pricing mechanisms, etc.);
     • Impact of carbon constraints and fuel cost fluctuations on profit margins.
3. Power grids, energy storage, and system services:
   • To address renewable energy volatility and low/negative electricity price risks, system value tilts toward “consumption and flexibility”:
     • Transmission and distribution upgrades, flexible transformation, virtual power plants, energy storage, and demand response are more beneficial [3];
     • Focus on orders, policy support, and business closure of enterprises related to “grid investment/energy storage operation/digital dispatching and trading”.
4. Manufacturing and equipment sector:
   • Clean energy investment remains high [3], driving demand for equipment and materials, but distinction between “existing/incremental projects” is needed:
     • Expansion and transformation demand for old projects (e.g., technical transformation for efficiency improvement, station coordination upgrades);
     • New projects are extremely sensitive to cost and efficiency, possibly driving equipment prices and profit cycles toward a more “volume-price game” pattern.

3. Stock Selection Strategy and Implementation Verification Methods (Example Paths)
   Note: No specific stock codes or absolute target prices are provided; only reusable verification and screening frameworks are offered. You can use tools like Jinling API (historical prices, financial analysis, technical analysis, Python visualization) for empirical backtesting and multi-dimensional comparison of candidate targets.

A) Scenario verification and backtesting (Python/data direction):

• Stock pool construction:
  • Renewable energy generation: Operation companies including wind, solar, and integrated energy;
  • Flexible adjustment: Coal power, gas power, hydropower, pumped storage, energy storage operators;
  • Grid and system: Grid equipment, dispatching and trading, virtual power plants, and industrial/commercial load aggregators;
  • Manufacturing chain: Polysilicon/wafers/modules, wind turbine/parts, energy storage batteries/systems.
• Event marking (approximate): Use late May/early June 2025 as the “scenario window” to observe changes in relative performance and volatility of sectors before and after.
• Indicator construction (Python example ideas):
  • Cumulative return, maximum drawdown, volatility, and Sharpe ratio;
  • Beta and excess return relative to the overall market/power sector benchmark;
  • Financial quality: ROE/ROIC, gross margin/EBITDA margin, capital expenditure/depreciation, free cash flow, and dividend rate;
  • Profit-valuation matching: Forward PE/PB vs. profit growth rate, valuation sensitivity to dividend yield and interest rates.

B) Dimension 1: Renewable energy generation (distinction between existing and incremental projects):

• Existing project orientation (“old project” logic):
  • Screening: Installed capacity and asset structure before mid-2025, proportion of existing projects, province location and transmission channel capacity, historical electricity price and settlement status;
  • Verification: Operational and cash flow stability over the past 3-5 years, dividend history, debt ratio and refinancing cost, project return rate (IRR) and repayment cycle.
• Incremental project orientation (“new project” logic):
  • Screening: Distribution of new projects (province, resource endowment, proportion of spot/medium-long-term contracts), collaboration capability with energy storage, participation in ancillary service markets;
  • Verification: Cost curve of new projects (LCOE and levelized operation and maintenance cost), backtesting of spot bidding strategies, scenario analysis of sensitivity to electricity price fluctuations.

C) Dimension 2: Coal power and flexible adjustment:

• Coal power: Unit scale and flexibility transformation progress, peak/frequency regulation contribution and compensation income structure, implementation degree of policy mechanisms like capacity/reserve, sensitivity of profit to fuel cost and carbon cost;
• Energy storage and integrated adjustment: Energy storage duration and response speed, utilization rate and cycle life, structure and sustainability of income sources (price spread arbitrage/ancillary services/capacity).

D) Dimension 3: Grid and system services:

• Grid investment and upgrade policies: Cross-regional transmission channels, distribution network transformation, DC and digital dispatching, etc.;
• Virtual power plants and load aggregation: Adjustable load scale, aggregation technology and market access capability, price response mechanism and contract structure.

E) Dimension 4: Manufacturing chain (equipment and materials):

• Cycle positioning: Global capital expenditure and capacity clearance rhythm, price and inventory cycles;
• Cost and competition pattern: Technological iteration, yield and per-watt cost, integration and vertical integration, overseas markets and policy barriers;
• Cash flow and capital expenditure: Balance between free cash flow and reinvestment, balance sheet flexibility.

F) Risks and uncertainties:

• Policy implementation deviation: Details and rhythm of mechanism-based electricity prices and compensation mechanisms in the hypothetical scenario may differ from real policies;
• Consumption and market risks: Actual consumption capacity of provinces, spot market volatility, cross-provincial dispatching and policy coordination may be lower than expected;
• Fuel and cost risks: Disturbance of fuel prices, carbon costs, interest rate and exchange rate changes on project valuation and returns;
• Technological substitution and rhythm: Rapid technological iteration of new projects, leading to more volatile equipment prices and profit elasticity.

G) Recommended implementation steps (implementable):

• Event backtesting: Use late May/early June 2025 as the boundary to compare return and risk indicators of candidate sectors and targets before and after;
• Financial and valuation screening: Prioritize companies with stable cash flow, dividend/repurchase friendliness, and good profit-valuation matching;
• Regional and asset structure verification: Prioritize companies with existing projects in high-quality consumption areas and new projects with cost and flexibility advantages;
• Cross verification of technology and fundamentals: Prefer those with technical support (trend/momentum) and fundamental improvement (profit/orders/policy) superimposed.

4. Conclusion (Directional Judgment Under Your Hypothetical Scenario Framework)

• If the “Document No.136” scenario is true (old project protection, new project bidding, inter-provincial consumption differentiation, coal power guarantee), the market will shift from “industry Beta” to “structure and regional Alpha”:
  • Power operation companies with existing project logic, flexible adjustment, and grid/system service directions have higher revenue certainty in the scenario, suitable as defensive and income-type allocations;
  • Operation and manufacturing ends related to new projects will rely more on “cost and flexibility”, requiring more detailed verification at the company and project levels;
  • For risk hedging, combine existing project, adjustment-type, and system service-type assets with moderately growth-oriented technology leaders to balance certainty exposure and growth elasticity.

References
[1] Bloomberg - “China’s Fossil Fuel Power Output Set for First Drop in a Decade” https://www.bloomberg.com/news/articles/2025-12-15/china-s-fossil-fuel-power-output-set-for-first-drop-in-a-decade
[2] Wall Street Journal / Forbes (Forbes article citing WSJ content) - “Why the Broad Rally in Energy Stocks Can’t Last Forever” https://cn.wsj.com/articles/為何能源股-普漲-行情不可能永遠持續下去-652a3245
[3] Forbes - “What The 2025 Green Investment ‘Boom’ Means For Business…” https://www.forbes.com/sites/monicasanders/2025/12/03/what-the-2025-green-investment-boom-means-for-businesstech-and-the-climate-next-year/
(For more precise WSJ original article URLs, further search by title is available; the above are verifiable sources returned by current tools.)