SolarTech India: Sensitivity vs. Scenario Analysis Case Study – Prof. Nikhil Gangadhar

19th February

https://medium.com/@nikhil19india/solartech-india-sensitivity-vs-scenario-analysis-case-study-2dfec6abdcac

Course Relevance: 

 · Financial Management / Corporate Finance: Focuses on capital budgeting techniques like NPV, IRR, and payback periods under uncertainty.

· Risk Management: Demonstrates how to quantify project risks using sensitivity and scenario analysis.

· Project Finance & Infrastructure: Examines the financial structuring of long-term utility-scale energy projects.

· Renewable Energy Management: Provides context on the Indian energy market, including PPA rates, subsidies (GBI), and grid challenges.

Academic concepts and theories: Capital Budgeting Fundamentals, Sensitivity Analysis (Ceteris Paribus), Scenario Analysis, Probability Theory in Finance, Risk Metrics, Weighted Average Cost of Capital (WACC)

Case Narrative:

SolarTech India: Sensitivity vs. Scenario Analysis Case Study

Company Background

SolarTech India Private Limited is a renewable energy company headquartered in Bangalore, specializing in utility-scale solar power generation. The company has successfully developed three solar farms across Karnataka and Tamil Nadu over the past five years. Given India’s ambitious renewable energy targets and favorable policy environment, SolarTech is now evaluating a new 100 MW solar photovoltaic (PV) farm project in Rajasthan.

Project Overview: Rajasthan Solar Farm

Project Details:

• Capacity: 100 MW solar PV farm
• Location: Jodhpur district, Rajasthan (high solar irradiation area)
• Project Timeline: 18-month construction period, 25-year operational life
• Power Purchase Agreement (PPA): 25-year contract with Rajasthan State Electricity Board

Base Case Financial Projections

Initial Investment Requirements

• Land Acquisition: ₹50 crores
• Solar Panels & Equipment: ₹200 crores
• Civil & Electrical Works: ₹75 crores
• Grid Connection & Transmission: ₹25 crores
• Working Capital: ₹15 crores
• Pre-operative Expenses: ₹10 crores
• Total Initial Investment: ₹375 crores

Base Case Operating Assumptions

• Energy Price (PPA Rate): ₹3.25 per kWh (escalating at 3% annually)
• Capacity Utilization Factor (CUF): 22% (typical for Rajasthan)
• Annual Energy Generation: 192.72 million kWh (100 MW × 22% × 8760 hours)
• Government Subsidies:
  • Generation Based Incentive (GBI): ₹0.50 per kWh for first 10 years
  • Accelerated Depreciation: 40% in Year 1, 25% in Year 2
• Annual Operating Costs: ₹12 crores (increasing at 5% annually)
• Discount Rate (WACC): 12%

Base Case Financial Results

• Annual Revenue (Year 1): ₹722.34 crores (Energy + Subsidies)
• Annual Operating Profit (Year 1): ₹710.34 crores
• Net Present Value (NPV): ₹845 crores
• Internal Rate of Return (IRR): 28.4%
• Payback Period: 4.2 years

Part A: Sensitivity Analysis

You are required to conduct a comprehensive sensitivity analysis to understand how changes in key variables affect the project’s NPV. The volatile nature of the renewable energy sector makes this analysis crucial.

Key Variables to Analyze

1. Energy Price (PPA Rate)
   • Base case: ₹3.25 per kWh
   • Test range: -30% to +30% in 10% increments
2. Government Subsidies (GBI)
   • Base case: ₹0.50 per kWh for 10 years
   • Test range: ₹0.00 to ₹1.00 per kWh in ₹0.20 increments
3. Construction Costs
   • Base case: ₹300 crores (excluding land and working capital)
   • Test range: -20% to +40% in 10% increments
4. Capacity Utilization Factor (CUF)
   • Base case: 22%
   • Test range: 18% to 26% in 1% increments
5. Discount Rate (WACC)
   • Base case: 12%
   • Test range: 9% to 15% in 1% increments

Tasks for Sensitivity Analysis:

1. Create a sensitivity table showing NPV changes for each variable
2. Identify the most critical variable that has the highest impact on NPV
3. Determine break-even points for each variable where NPV = 0
4. Create a tornado diagram ranking variables by their impact on NPV
5. Calculate the range of NPV outcomes across all sensitivity tests

Part B: Scenario Analysis

The renewable energy sector in India faces significant uncertainties. The government’s policy stance, global commodity prices, and technological changes can create distinct operating environments. Conduct a scenario analysis using three comprehensive scenarios.

Scenario 1: Optimistic Scenario (Probability: 25%)

“Policy Support & Technology Boom”

Market Conditions:

• Government increases renewable energy targets to 500 GW by 2030
• Enhanced policy support with extended subsidies
• Technological improvements reduce maintenance costs
• Strong economic growth increases electricity demand

Key Assumptions:

• Energy Price: ₹3.80 per kWh (17% higher due to strong demand)
• Government Subsidies: ₹0.75 per kWh for 12 years (extended support)
• Construction Costs: ₹270 crores (10% lower due to technology improvements)
• CUF: 24% (improved panel efficiency and weather conditions)
• Operating Costs: ₹10 crores annually (technology reduces maintenance)
• Discount Rate: 11% (stable economic environment)

Scenario 2: Base Case Scenario (Probability: 50%)

“Steady Progress”

• Use the base case assumptions provided earlier
• Moderate policy support continues
• Technology improvements at expected pace
• Stable economic and regulatory environment

Scenario 3: Pessimistic Scenario (Probability: 25%)

“Policy Uncertainty & Market Stress”

Market Conditions:

• Political uncertainty affects renewable energy policies
• Global supply chain disruptions increase costs
• Grid stability issues limit capacity utilization
• Economic slowdown reduces electricity demand

Key Assumptions:

• Energy Price: ₹2.80 per kWh (14% lower due to competitive pressure)
• Government Subsidies: ₹0.25 per kWh for 8 years only (reduced support)
• Construction Costs: ₹350 crores (17% higher due to supply chain issues)
• CUF: 19% (grid curtailment and maintenance issues)
• Operating Costs: ₹15 crores annually (higher maintenance and regulatory costs)
• Discount Rate: 14% (increased risk premium)

Tasks for Scenario Analysis:

1. Calculate NPV and IRR for each scenario
2. Compute expected NPV using probability-weighted outcomes
3. Assess risk metrics:
   • Standard deviation of NPV across scenarios
   • Coefficient of variation
   • Probability of negative NPV
4. Compare worst-case scenario with sensitivity analysis results
5. Evaluate the risk-return profile of the project

Part C: Comparative Analysis & Decision Making

Analysis Questions:

1. Method Comparison:
   • Which method provides a more comprehensive view of project risk?
   • How do the risk insights from sensitivity analysis differ from scenario analysis?
   • Which method better captures the interconnected nature of variable changes?
2. Risk Assessment:
   • What is the probability of the project failing (NPV < 0) under each method?
   • How confident should management be in the base case projections?
   • Which variables/scenarios pose the greatest risk to project viability?
3. Strategic Implications:
   • Should SolarTech proceed with the investment?
   • What risk mitigation strategies should be considered?
   • How might the analysis influence the financing structure?
4. Limitations Analysis:
   • What are the key limitations of each analytical method?
   • What additional analysis might strengthen the decision-making process?

How might Monte Carlo simulation complement these approaches?

Deliverables

Required Outputs:

1. Sensitivity Analysis Summary:
   • Tornado diagram showing variable impact rankings
   • Break-even analysis table
   • Risk assessment based on sensitivity ranges
2. Scenario Analysis Report:
   • Detailed financial projections for each scenario
   • Expected value calculations with risk metrics
   • Probability distributions and risk indicators
3. Executive Summary:
   • Comparison of insights from both methods
   • Final investment recommendation with rationale
   • Risk mitigation strategy recommendations

Evaluation Criteria:

• Technical Accuracy: Correct application of financial formulas and concepts
• Analytical Depth: Thorough exploration of risk factors and their implications
• Business Insight: Understanding of renewable energy market dynamics
• Presentation Quality: Clear communication of complex analytical results
• Strategic Thinking: Practical recommendations for decision-making

Additional Context: Indian Renewable Energy Market

Current Market Dynamics:

• India has committed to 500 GW renewable capacity by 2030
• Solar tariffs have declined from ₹17/kWh in 2010 to ₹2-3/kWh in 2024
• Policy support includes Production Linked Incentives (PLI) and Green Energy Corridors
• Grid integration challenges persist in some states
• Land acquisition and financing remain key challenges

Key Risk Factors:

• Policy changes at central and state government levels
• Grid curtailment during peak generation periods
• Module price volatility due to global supply chain dynamics
• Interest rate fluctuations affecting project financing
• Transmission infrastructure development delays

This comprehensive case study will help students understand how different analytical approaches reveal various dimensions of investment risk in volatile markets, particularly in the rapidly evolving renewable energy sector.

5. Teaching Note:

1. Phase 1: The Base Case: Verify if the students understand the initial investment of ₹375 crores and the resulting NPV of ₹845 crores.
2. Phase 2: Variable Sensitivity: Discuss which variables are “volatile.” For instance, why are construction costs and CUF critical in the Rajasthan context?
3. Phase 3: Interconnectivity: Transition from sensitivity (one variable) to scenario analysis (multiple variables). Ask students: “In reality, if energy prices drop, do operating costs stay the same?”.
4. Phase 4: Strategic Decision: Move beyond the numbers. Should SolarTech proceed if the pessimistic scenario has a high probability of a negative NPV?

Key Insight: Sensitivity analysis identifies which variable is most dangerous, while scenario analysis shows the combined impact of a specific market environment.

6.  Suggested Activity:

“The Risk Committee Simulation”

Setup: Divide the class into three groups: Project Proponents, The Risk Management Team, and The Board of Directors.

• Step 1 (Technical): Have all groups calculate the Expected NPV using the formula. (Using probabilities: 25% Optimistic, 50% Base, 25% Pessimistic)
• Step 2 (Analysis): The Risk Management Team must create a “Tornado Diagram” concept (ranking variables like PPA Rate, CUF, and WACC by impact).
• Step 3 (Debate): The Project Proponents argue for the investment based on the 28.4% IRR. The Risk Team highlights the 14% WACC and supply chain risks in the pessimistic scenario.
• Step 4 (Decision): The Board of Directors makes a final “Go/No-Go” decision based on the Coefficient of Variation.

7. Sample Questions:

1. Based on the Base Case, calculate the total revenue for Year 1, considering both the energy generation and the GBI subsidy.
2. Calculate the Expected NPV of the project using the three scenarios provided in Part B.
3. If the Capacity Utilization Factor (CUF) drops from 22% to 18%, what is the percentage change in annual energy generation?
4. Which analysis is more useful for a project manager overseeing construction costs, and which is more useful for a CEO looking at national policy changes? Why?.
5. Identify the most critical variable for SolarTech India. How does the “high solar irradiation” of Jodhpur influence this variable?
6. Suggest two strategies SolarTech could use to mitigate the risks found in the “Pessimistic Scenario” (e.g., supply chain disruptions or grid curtailment).
   1. References:
7. Ministry of New and Renewable Energy (MNRE), Government of India (2024). Annual Report 2023-24. India’s renewable energy targets and policy framework
8. Central Electricity Authority (CEA) (2024). National Electricity Plan: Volume I – Generation. Solar capacity planning and utilization factors
9. International Renewable Energy Agency (IRENA) (2023). Renewable Power Generation Costs in 2023. Global solar PV cost trends and benchmarks
10. National Institute of Solar Energy (NISE) (2023). Solar Resource Assessment for India. Solar irradiation data and CUF benchmarks for different regions
11. Chandra, P. (2022). Projects: Planning, Analysis, Selection, Financing, Implementation, and Review. McGraw Hill India. (The standard text for Indian project finance).
12. Brealey, R. A., Myers, S. C., & Allen, F. Principles of Corporate Finance. McGraw-Hill Education. (Global reference for risk analysis techniques like Monte Carlo and Scenario analysis).
13. BRIDGE TO INDIA (2024). India Solar Market Outlook 2024. Current market trends and competitive landscape
14. Mercom India (2024). India Solar Market Update Q4 2023. Solar tariff trends and auction results
15. CRISIL Research (2024). Indian Renewable Energy Sector Report. Credit perspectives and risk factors