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Chapter 10 Dealing with Uncertainty. 10.1 Introduction ---exacerbated by regulatory & environmental uncertainty Restructuring of the electric industry,

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Presentation on theme: "Chapter 10 Dealing with Uncertainty. 10.1 Introduction ---exacerbated by regulatory & environmental uncertainty Restructuring of the electric industry,"— Presentation transcript:

1 Chapter 10 Dealing with Uncertainty

2 10.1 Introduction ---exacerbated by regulatory & environmental uncertainty Restructuring of the electric industry, is more complex than imagined. Dealing with uncertainty is crucial.

3 10.2 Key Issues 1.How can we make economic decisions in the face of market and nonmarket uncertainties? 2.How do we measure uncertainty, especially uncertainty about nonmarket issues like global climate change? 3.How do we determine the value of new information that might help reduce uncertainty?

4 Uncertainty has critical impacts. (price volatility, policy compromises) Development and failure of IRP (integrated resource planning).

5 10.3 Making Investment Decisions Under Uncertainty Sensitivity analysis &scenario analysis Sensitivity analysis: “base case” model, adjust inputs individually Scenario analysis: same “base case”, but constructs specific “scenarios” that can include multiple changes. Problem for both: Ignore the likelihood of different events or scenarios; fail to identify “least-cost” choices.

6 Table 10.1 Distribution Planning Costs

7 Table 10-2: Expected Costs of Alternative Investment Strategies

8  Real Options Let us consider discounted cash flow analysis & the impact of uncertainty. Suppose: consider whether to build a new electric generating plant; output will be sold in the wholesale market.

9 C=$500 million. Produce $1 million MWh per year P either $40 per MWh or $80 per MWh, then P=0.5*$40+0.5*$80=$60 C: cost; P: price; Q: quantity of electricity produced; r: discount rate

10 NPV is positive, but should also consider when P is $40: NPV of waiting for one year is: If P=$40, no investment ( first term 0); if P=$80, invest. Uncertainty resolved. ---This resembles a call option on a common stock. The cost of waiting is forgone R if the future turns out well.

11 Figure: The future Price of Electricity

12 First, calculate the Min. P next year for the investment to have a positive NPV if we wait: This means the initial price, P0, equals P1/1.5=$30. So if P0< $30, we will never wait to invest in the plant, coz there is no chance the investment will be profitable.

13 Next, determine when the expected NPV of investing today is greater than expected NPV if waiting: P0=$78. So the opportunity cost of waiting will be greater than the value of the option to wait.

14 Figure 10-2 :Value of Option to Invest.

15 Figure 10-3 Increased Price Uncertainty

16  Decision Trees and the Value of Information Decision trees: for making good decisions and determining the value of new info. Ex: deciding whether to walk to work tomorrow or ride the bus. Consider: weather walkRide Bus Rain06 No Rain 106

17 Two decision “branches” and two uncertainty branches off each decision branch. E(walk)=0.5*10+0.5*0=5.0 E(Bus)=0.5*6+0.5*6=6.0 So unless gamble on the weather, you should take a bus.

18  The Role of Emotions Traditional economics assumes rational decision-maker. Sometimes, the info needed to make a rational decision is not available; some decisions are emotional or political. But when it comes to major investment decisions and regulatory evaluations, role of emotions should be limited.

19  Applying Decision Analysis Techniques to the Electric Industry Ex: a coal-fired power plant, required to reduce carbon emissions by 50% starting 5 years from now. Choices: 1.Shut down the plant 2.Purchase emissions allowances at an unknown future P 3.Invest in a new experimental technology that is designed to capture 80% of the carbon emissions and inject it deep underground.

20  Regulatory Impacts This analysis is also crucial from a regulatory standpoint. To ensure prudent investment To scrutinize unregulated generators bidding into POLR auction

21 10.4 Measuring Price Volatility Forecast changes in demand and supply, to ensure that enough electricity is available to avoid blackouts; to evaluate whether market power concerns are likely to emerge. But still can not account for all. Volatility, similar to, but normalized to a specific time period.

22 Figure 10-7: Henry Hub Daily Average Closing Natural Gas Prices.

23 Measuring volatility is critical for : determining the value of hedging and the cost of reducing exposure to uncertain market prices; capital investment decision. Easiest way to calculate historic volatility: 1.Calculate the log of day-to-day P changes for entire y 2.Calculate the Of those P changes 3.Multiply the By the square root of the average number of trading days per y, usually defined as 252.

24 10.5 Nonmarket Uncertainties Ex: regulatory and political structures, etc. What can be done? 1.Ignore nonmarket uncertainties or addressing them crudely (Diff bw risk and uncertainty); determine event thresholds 2.Add uncertainty to the decision framework 3.Complications: Use judgment; decide how much risk is acceptable; weigh the risks of different investment strategies

25 Table 10-4 Critical Event Matrix

26 Figure 10-8 Comparing Multiple Projects

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