Analysis of China Resources New Energy's Photovoltaic Curtailment Rate and Revision Research on Valuation Models for Wind Power Operators

China’s new energy power generation industry has long faced PV and wind curtailment issues, which directly affect the power generation utilization hours and actual revenue of wind power operators. The photovoltaic curtailment rate refers to the proportion of PV power plant generation that is restricted from grid connection, and is an important indicator to measure new energy absorption capacity. As a new energy power generation platform under China Resources Power, China Resources New Energy’s curtailment rate changes directly reflect the changes in regional power market supply and demand and grid absorption capacity.

When the photovoltaic curtailment rate rises from a low level to 12.9%, it means that nearly 13% of the generated electricity cannot be sold to the grid. For new energy operators whose revenue core is based on power generation and grid-connected electricity prices, this means a significant loss of revenue and profits. Against the backdrop of the full promotion of grid-parity policies, such losses are more difficult to offset through electricity price increases, creating double pressure on project收益率 (project returns).

With China’s new energy power generation fully entering the grid-parity era, subsidy-dependent projects are gradually退出历史舞台 (exiting the historical stage), and almost all new projects are grid-parity projects. This transformation has a profound impact on the valuation logic of wind power operators:

• Fixed grid-connected electricity prices or competitive grid-connected electricity prices have replaced the original “electricity price + subsidy” model
• Revenue predictability has decreased, relying more on electricity market transaction prices
• The proportion of market-oriented transactions has increased, and electricity price volatility risks have intensified

• Project construction costs have decreased, but the space for cost reduction is gradually narrowing
• Operation and maintenance costs show a clear trend of rigid growth
• Energy storage configuration requirements have increased, leading to additional costs

The traditional Discounted Cash Flow (DCF) model usually adopts the following core framework when evaluating wind power operators:

FCF = (Electricity Generation × Utilization Hours × Grid Connection Rate × Electricity Price) - Operating Costs - Capital Expenditure - Taxes and Fees

• Electricity Generation: Based on wind resource assessment and installed capacity
• Utilization Hours: Historical average or design value
• Grid Connection Rate: Assumed to be close to 100% or using historical average levels
• Electricity Price: Fixed price or considering moderate increases
• Operating Costs: Unit costs decrease with scale effects
• Discount Rate: Calculated based on WACC (Weighted Average Cost of Capital), considering industry beta

When the curtailment rate rises and the proportion of grid-parity projects increases, the core assumptions of traditional valuation models face severe challenges:

Traditional models usually assume a grid connection rate close to 100% or use relatively optimistic historical averages. However, the reality of a 12.9% curtailment rate indicates that this assumption may deviate significantly from the actual situation. Especially in regions with loose power supply and demand and limited grid channels, PV and wind curtailment issues may persist or even worsen for a long time.

Grid-parity projects mean that electricity prices are more determined by the market. With the advancement of power market reforms, electricity price volatility has increased significantly. The stable electricity price assumption in traditional DCF models is difficult to hold, requiring the introduction of more complex electricity price scenario analysis.

Operation and maintenance costs show rigid characteristics under the background of PV and wind curtailment—even if power generation decreases, fixed costs such as operation and maintenance personnel and equipment maintenance still need to be paid, leading to an increase in unit costs and a decrease in project returns.

Instead of simply assuming a fixed grid connection rate, a probability model based on the following factors is established:

• Regional power supply and demand balance
• Grid channel capacity and construction planning
• Local new energy installed capacity growth expectations
• Energy storage configuration ratio and scheduling strategy
• Power marketization process

For grid-parity projects, multiple scenario electricity price assumptions need to be established:

Scenario	Electricity Price Assumption	Probability Weight	Applicable Conditions
Optimistic Scenario	Base electricity price上浮10-15% (increased by 10-15%)	20%	Tight power supply and strong demand
Baseline Scenario	Base electricity price	50%	Normal market environment
Pessimistic Scenario	Base electricity price下浮10-15% (decreased by 10-15%)	30%	Excess power supply and fierce market competition

With the deepening of power market reforms, the revenue structure of new energy operators will shift from a single energy price to a diversified structure of “energy price + capacity price + auxiliary services”. These emerging revenue sources need to be included in the valuation model.

Split operating costs into fixed costs and variable costs:

• Fixed Costs
  : Personnel salaries, asset management fees, insurance fees, etc.—not changing with power generation
• Variable Costs
  : Consumables, maintenance spare parts, etc.—positively correlated with power generation
• Semi-Fixed Costs
  : Partial operation and maintenance services—with threshold effects

Establish cost elasticity coefficient model:

Actual Unit Cost = Fixed Costs/(Electricity Generation × Grid Connection Rate) + Variable Cost Coefficient

Curtailment is not only a revenue loss but also generates additional costs:

• Equipment idling loss
• Energy storage system operation cost
• Dispatch assessment fines

These costs should be fully considered in the valuation model.

Parameter	Traditional Assumption	Revised Recommendation	Adjustment Reason
Risk-Free Rate	3-4%	2.5-3%	Interest rate downward cycle
Market Risk Premium	5-6%	6-7%	Increased risk of power marketization
Beta Coefficient	0.8-1.0	1.0-1.2	Increased industry volatility
Specific Risk Premium	0-1%	2-3%	PV and wind curtailment risks, regional concentration

On the basis of the DCF model, extreme scenario analysis is added:

• Curtailment rate continues to deteriorate to more than 20%
• Electricity price drops significantly beyond expectations
• Policy changes (such as subsidy recovery)
• Equipment damage caused by natural disasters

Although these scenarios have low probability, they have a huge impact on valuation once they occur, and need to be fully reflected in the valuation range.

The design service life of wind and PV assets is usually 20-25 years, but the actual economic life may be longer. In the valuation model:

• Consider the reassessment value or residual value of assets at the end of their service life
• Consider the extension of asset life through technological transformation and upgrading
• Consider the renewal arrangement of land use rights

With the maturity of the carbon market and the rise of carbon prices, the carbon emission reduction value of new energy operators needs to be reflected in the valuation:

Implied Carbon Value = Annual Emission Reduction × Carbon Market Price × Discount Factor

FCF = (Σ Electricity Generation × Utilization Hours × (1-Curtailment Rate) × Electricity Price) 
      - Operating Costs - Maintenance Costs - Management Fees 
      - Tax Adjustments + Carbon Trading Income + Auxiliary Service Income

Revised WACC = Risk-Free Rate + β × Market Risk Premium + Curtailment Risk Premium + Regional Risk Premium

Given the complexity of grid-parity projects and PV/wind curtailment issues, the Monte Carlo simulation method is recommended for valuation:

• Curtailment Rate (Probability Distribution)
• Electricity Price (Scenario Tree)
• Utilization Hours (Historical Volatility Range)
• Operation and Maintenance Costs (Inflation + Technological Progress)
• Discount Rate (Interest Rate Scenarios)

• Valuation Probability Distribution
• Confidence Interval
• Sensitivity Analysis Matrix

Parameter	Change Range	Valuation Impact Direction	Impact Degree
Curtailment Rate	+1%	Negative	Medium
Electricity Price	-5%	Negative	Large
Utilization Hours	-10%	Negative	Large
Discount Rate	+0.5%	Negative	Medium
Operation and Maintenance Costs	+10%	Negative	Small

1. Valuation Center Downward:
   The rise of curtailment rate and the increase in the proportion of grid-parity projects mean that the intrinsic value center of wind power operators moves downward, and valuation multiples may decrease systematically.

2. Increased Valuation Differentiation:
   Operators in different regions with different absorption capacities will show significant valuation differentiation. High-quality assets with strong absorption capacity and low PV/wind curtailment rates will obtain valuation premiums.

3. Focus on Tail Risks:
   Extreme scenarios need to be fully considered in valuation analysis to avoid overly optimistic valuation assumptions.

4. Dynamic Adjustment Capability:
   The valuation model needs to have dynamic adjustment capabilities to update valuation judgments in a timely manner based on curtailment rate changes and electricity price trends.

For the investment analysis of wind power operators, it is recommended to focus on:

• Regional Selection:
  Prioritize regions with good absorption conditions and low PV/wind curtailment rates
• Asset Quality:
  Focus on high-quality assets with high availability and controllable operation and maintenance costs
• Growth Quality:
  Focus on the quality of installed capacity growth rather than simple scale expansion
• Cash Flow Capability:
  Attach importance to free cash flow and dividend capability rather than book profits

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China Resources New Energy’s photovoltaic curtailment rate rising to 12.9% reflects the systemic challenges faced by the industry, while the increase in the proportion of grid-parity projects has changed the profit model of wind power operators. In this context, the core assumptions of traditional valuation models need to be comprehensively revised, including introducing PV/wind curtailment probability models, establishing electricity price scenario analysis frameworks, adjusting discount rate parameters, and establishing elastic cost models. The revised valuation model will more accurately reflect the true intrinsic value of wind power operators and provide more reliable basis for investment decisions.

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