Study on Behavioral Decision Making by Power Generation Companies Regarding Energy Transitions under Uncertainty
Abstract
:1. Introduction
1.1. Background
1.2. Literature Review
2. Materials and Methods
2.1. Design of the Framework
2.2. Development of the Behavioral Decision Model in the Energy Market
2.3. Application to Kansai Region, Japan
2.3.1. Overview of Electric Utility System in Japan
2.3.2. Private Information of Company 2 (STEP I-a)
- (i.)
- Existing VRE Capacity
- (ii.)
- Strategies of Company 2
2.3.3. Exogenous Information: Scenario Development (STEP I-b)
- (i.)
- Strategies of Company 1 Regarding Existing Power Plant Replacement
- (ii.)
- Future Policies
2.3.4. Exogenous Information: Probability Distribution (STEP I-b)
- (i.)
- Fuel Price
- (ii.)
- Electricity Demand
- (iii.)
- Ambient Conditions
2.4. Study Cases
3. Results and Discussion
3.1. Effect of FIP Price (Cases 1 and 2)
3.2. Effect of the Strategy of Company 1 (Cases 3 and 4)
3.3. Effect of VRE Mixture (Cases 5 and 6)
3.4. Effect of Option to Expand in Cases 7, 8, 9, and 10
4. Conclusions
- This study assumed that the energy market was competitive, even though there were only two players (Company 1 and 2) in the market, in order to examine the novel decision-making model. Although renewable power generation companies were consolidated into Company 2 for simplicity, each renewable power generation company in the region may interact in reality. Moreover, although the strategies of Company 1 were provided by some scenarios in this study, the interactions between the decisions of Company 1 and the RE companies need to be considered in future work.
- In this study, only two types of RFPs were defined as the influence of the suggestions of the middle management for simplicity: Ref_EXP (higher RFP) and Ref_CVaR (lower RFP) for simplicity. However, as mentioned in the framework of Section 2.1, several factors will influence the RFP of the top management other than suggestions from the middle management, such as personal and exogenous influences. We should examine how the other non-normative perspectives affect the decisions made by the RE company.
- Although the NPV method was applied to the normative perspective of RE companies in the decision-making model, other methods such as IRR or Real Options approaches may be applicable. The Kahneman and Tversky approach [29,30] was used here to quantitatively express the non-normative perspective of RE companies; however, other approaches, such as the Regret theory, could be used for the non-normative perspective. Alternative methods should be further investigated in future studies.
- Energy storage was not applied as an option for technology. As the timeframe of decision making in this study was 2020–2030, we expected the effect of energy storage to be limited. However, energy storage should be considered in further studies of VRE introduction, such as the energy transition in the 2050s, on a larger scale.
- The electricity trade spot price and feed-in premium were the only financial supports considered for VRE to simplify the spot price market model. As emerging electricity markets and financial supports, such as the capacity market, are still being discussed in Japan, the effects of such new systems need to be examined.
Author Contributions
Funding
Conflicts of Interest
Appendix A. Application of Reference Point, Value Function, and the Weighting Function
- Reference Point (RFP)
- 2.
- The Value Function
- 3.
- The Weighting Function
Appendix B. Definition of NPV and the Other Outputs
- 1.
- Net Present Value (NPV)
- 2.
- Value at Risk (VaR) and Conditional Value at Risk (CVaR)
Appendix C. Properties of Technology
Item | Unit | Technology | Value | Remarks |
---|---|---|---|---|
Construction Cost | [yen/kW] | GTCC (Natural Gas) | 120,000 | [58] |
PV | 273,500 | |||
Wind (On-shore) | 287,000 | |||
Operation & Maintenance | [%/Year] | GTCC (Natural Gas) | 3.0 | [58] |
Steam Power (Oil) | 3.2 | |||
Steam Power (Coal) | 4.0 | |||
Nuclear | 5.2 | |||
PV | 1.2 | |||
Wind (On-shore) | 2.1 | |||
Gross Plant Efficiency (LHV) | [%-LHV] | GTCC (Natural Gas, Existing) | 51.5 | Based on [58] |
GTCC (Natural Gas, Replaced) | 58.6 | |||
Steam Power (Oil) | 37.5 | |||
Steam Power (Coal) | 40.8 | |||
Payback Period | [Year] | GTCC | 15 | [58] |
PV | 10 | |||
Wind (On-shore) | 10 | |||
Lifetime | [Year] | GTCC | 40 | [58] |
PV | 20 | |||
Wind (On-shore) | 20 | |||
CO2 Emission Coefficient | [t-CO2/t] | GTCC (Natural Gas) | 2.7 | [59] |
Steam Power (Oil) | 3.4 | |||
Steam Power (Coal) | 2.3 |
Appendix D. Calculation Results of Each Case
Scenario | Case | 1 (Investments in PV) | 2 (Investments in Wind) | |||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|
Total Capacity | Unit | 0 | 1000 | 3000 | 5000 | 7000 | 0 | 1000 | 3000 | 5000 | 7000 | |
FIP- Low | Exp. NPV | Billion yen | 372.9 | 335.8 | 221.1 | 67.7 | −129.6 | 372.9 | 339.2 | 212.3 | −15.5 | −316.1 |
Exp.Value (Ref_EXP) | - | 0.0 | −37.7 | −123.6 | −225.9 | −346.1 | 0.0 | −37.0 | −126.7 | −270.2 | −461.6 | |
Exp.Value (Ref_CVa) | - | 0.0 | 0.3 | −84.1 | −188.6 | −312.2 | 0.0 | 0.6 | −87.9 | −232.5 | −426.0 | |
SD of NPV | Billion yen | 26.0 | 40.0 | 65.7 | 91.7 | 105.8 | 26.0 | 48.1 | 97.7 | 141.0 | 167.7 | |
CVaR of NPV | Billion yen | 319.0 | 253.7 | 88.6 | −123.1 | −342.8 | 319.0 | 243.0 | 9.7 | −290.1 | −642.1 | |
FIP- Mid | Exp.NPV | Billion yen | 372.9 | 363.3 | 308.4 | 217.0 | 69.2 | 372.9 | 415.0 | 428.9 | 357.3 | 188.9 |
Exp.Value (Ref_EXP) | - | 0.0 | −19.2 | −61.7 | −129.9 | −209.2 | 0.0 | 9.9 | −0.4 | −38.4 | −135.9 | |
Exp.Value (Ref_CVa) | - | 0.0 | 14.2 | −24.1 | −90.5 | −173.4 | 0.0 | 36.7 | 29.0 | −8.6 | −104.0 | |
SD of NPV | Billion yen | 26.0 | 41.3 | 69.1 | 95.8 | 117.6 | 26.0 | 53.3 | 128.7 | 189.6 | 217.7 | |
CVaR of NPV | Billion yen | 319.0 | 277.2 | 172 | 18.7 | −174.9 | 319.0 | 305.4 | 163.3 | −3.6 | −230.5 | |
FIP- High | Exp.NPV | Billion yen | 372.9 | 407.8 | 440.9 | 441.7 | 367.8 | 372.9 | 466.2 | 580.2 | 604.4 | 520.4 |
Exp.Value (Ref_EXP) | - | 0.0 | 9.0 | 17.5 | 0.7 | −38.1 | 0.0 | 35.4 | 62.8 | 65.6 | 22.4 | |
Exp.Value (Ref_CVa) | - | 0.0 | 34.7 | 43.7 | 29.1 | −8.6 | 0.0 | 57.9 | 85.7 | 90.2 | 49.1 | |
SD of NPV | Billion yen | 26.0 | 41.8 | 74.4 | 107.9 | 134.3 | 26.0 | 62.8 | 148.7 | 221.3 | 269.9 | |
CVaR of NPV | Billion yen | 319.0 | 324.7 | 294.4 | 201.4 | 89.5 | 319.0 | 346.0 | 282.6 | 164.6 | −21.0 |
Scenario | Case | 3 (Investments in PV with FIP-Low) | 4 (Investments in Wind with FIP-Low) | |||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|
Total Capacity | Unit | 0 | 1000 | 3000 | 5000 | 7000 | 0 | 1000 | 3000 | 5000 | 7000 | |
wRP _NC60 | Exp. NPV | Billion yen | 372.9 | 335.8 | 221.1 | 67.7 | −129.6 | 372.9 | 339.2 | 212.3 | −15.5 | −316.1 |
Exp. Value (Ref_EXP) | - | 0.0 | −37.7 | −123.6 | −225.9 | −346.1 | 0.0 | −37.0 | −126.7 | −270.2 | −461.6 | |
Exp. Value (Ref_CVa) | - | 0.0 | 0.3 | −84.1 | −188.6 | −312.2 | 0.0 | 0.6 | −87.9 | −232.5 | −426.0 | |
SD of NPV | Billion yen | 26.0 | 40.0 | 65.7 | 91.7 | 105.8 | 26.0 | 48.1 | 97.7 | 141.0 | 167.7 | |
CVaR of NPV | Billion yen | 319.0 | 253.7 | 88.6 | −123.1 | −342.8 | 319.0 | 243.0 | 9.7 | −290.1 | −642.1 | |
wRP _NC40 | Exp. NPV | Billion yen | 464.6 | 451.3 | 413.2 | 354.3 | 255.5 | 464.6 | 483.3 | 475.5 | 413.6 | 258.7 |
Exp. Value (Ref_EXP) | - | 0.0 | −21.6 | −52.2 | −100.6 | −154.2 | 0.0 | −1.9 | −15.9 | −63.5 | −151.0 | |
Exp. Value (Ref_CVa) | - | 0.0 | 16.9 | −10.6 | −53.7 | −112.7 | 0.0 | 30.7 | 19.7 | −23.6 | −112.0 | |
SD of NPV | Billion yen | 32.1 | 45.6 | 78.8 | 96.7 | 122.5 | 32.1 | 56.1 | 119.1 | 186.9 | 219.9 | |
CVaR of NPV | Billion yen | 400 | 360 | 255 | 159 | 17 | 400 | 377 | 254 | 54 | −174 | |
woRP _NC60 | Exp. NPV | Billion yen | 335.1 | 285.8 | 154.1 | 1.3 | −193.1 | 335.1 | 284.3 | 124.1 | −111.3 | −415.4 |
Exp. Value (Ref_EXP) | - | 0.0 | −47.1 | −148.3 | −241.6 | −358.6 | 0.0 | −50.6 | −150.1 | −310.9 | −501.0 | |
Exp. Value (Ref_CVa) | - | 0.0 | −5.8 | −105.4 | −204.1 | −323.9 | 0.0 | −12.2 | −115.8 | −277.0 | −469.8 | |
SD of NPV | Billion yen | 27.9 | 37.3 | 59.9 | 82.7 | 101.3 | 27.9 | 45.0 | 96.4 | 135.9 | 160.6 | |
CVaR of NPV | Billion yen | 278.7 | 211.4 | 31.7 | −163.0 | −402.4 | 278.7 | 196.6 | −64.5 | −372.5 | −730.2 |
Scenario | Case | 5 (with FIP-Low) | 6 (with FIP-High) | |||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|
Total Capacity | Unit | 0 | 1000 | 3000 | 5000 | 7000 | 0 | 1000 | 3000 | 5000 | 7000 | |
PV _ONLY | Exp. NPV | Billion yen | 372.9 | 335.8 | 221.1 | 67.7 | −129.6 | 372.9 | 407.8 | 440.9 | 441.7 | 367.8 |
Exp. Value (Ref_EXP) | - | 0.0 | −37.7 | −123.6 | −225.9 | −346.1 | 0.0 | 9.0 | 17.5 | 0.7 | −38.1 | |
Exp. Value (Ref_CVaR) | - | 0.0 | 0.3 | −84.1 | −188.6 | −312.2 | 0.0 | 34.7 | 43.7 | 29.1 | −8.6 | |
SD of NPV | Billion yen | 26.0 | 40.0 | 65.7 | 91.7 | 105.8 | 26.0 | 41.8 | 74.4 | 107.9 | 134.3 | |
CVaR of NPV | Billion yen | 319.0 | 253.7 | 88.6 | −123.1 | −342.8 | 319.0 | 324.7 | 294.4 | 201.4 | 89.5 | |
WIND _ONLY | Exp. NPV | Billion yen | 372.9 | 339.2 | 212.3 | −15.5 | −316.1 | 372.9 | 466.2 | 580.2 | 604.4 | 520.4 |
Exp. Value (Ref_EXP) | - | 0.0 | −37.0 | −126.7 | −270.2 | −461.6 | 0.0 | 35.4 | 62.8 | 65.6 | 22.4 | |
Exp. Value (Ref_CVaR) | - | 0.0 | 0.6 | −87.9 | −232.5 | −426.0 | 0.0 | 57.9 | 85.7 | 90.2 | 49.1 | |
SD of NPV | Billion yen | 26.0 | 48.1 | 97.7 | 141.0 | 167.7 | 26.0 | 62.8 | 148.7 | 221.3 | 269.9 | |
CVaR of NPV | Billion yen | 319.0 | 243.0 | 9.7 | −290.1 | −642.1 | 319.0 | 346.0 | 282.6 | 164.6 | −21.0 | |
MIX1 (PV:Wind =1:1) | Exp. NPV | Billion yen | 372.9 | 340.4 | 240.3 | 93.0 | −84.7 | 372.9 | 443.3 | 542.0 | 593.5 | 601.0 |
Exp. Value (Ref_EXP) | - | 0.0 | −35.3 | −116.8 | −221.1 | −312.7 | 0.0 | 26.6 | 60.5 | 73.7 | 63.9 | |
Exp. Value (Ref_CVaR) | - | 0.0 | 3.6 | −72.1 | −178.6 | −276.2 | 0.0 | 49.4 | 81.1 | 95.5 | 85.9 | |
SD of NPV | Billion yen | 26.0 | 40.7 | 69.9 | 97.9 | 121.4 | 26.0 | 46.0 | 92.9 | 144.5 | 180.7 | |
CVaR of NPV | Billion yen | 319.0 | 257.5 | 99.8 | −106.1 | −330.0 | 319.0 | 350.6 | 356.0 | 305.5 | 228.7 | |
MIX2 (PV:Wind =7:3) | Exp. NPV | Billion yen | 372.9 | 339.1 | 237.0 | 106.4 | −70.5 | 372.9 | 426.6 | 512.1 | 550.3 | 563.6 |
Exp. Value (Ref_EXP) | - | 0.0 | −36.5 | −114.6 | −197.0 | −320.3 | 0.0 | 18.9 | 49.1 | 63.9 | 58.6 | |
Exp. Value (Ref_CVaR) | - | 0.0 | 1.1 | −75.0 | −160.9 | −285.3 | 0.0 | 43.1 | 70.0 | 86.5 | 80.7 | |
SD of NPV | Billion yen | 26.0 | 40.1 | 67.5 | 89.2 | 116.5 | 26.0 | 43.0 | 78.6 | 111.7 | 155.9 | |
CVaR of NPV | Billion yen | 319.0 | 258.8 | 102.5 | −79.5 | −305.3 | 319.0 | 339.4 | 350.4 | 330.3 | 262.1 | |
MIX3 (PV:Wind =3:7) | Exp. NPV | Billion yen | 372.9 | 338.0 | 231.6 | 60.2 | −126.4 | 372.9 | 451.4 | 550.3 | 610.7 | 611.0 |
Exp. Value (Ref_EXP) | - | 0.0 | −37.8 | −115.0 | −211.3 | −345.6 | 0.0 | 29.3 | 64.5 | 78.0 | 79.1 | |
Exp. Value (Ref_CVaR) | - | 0.0 | −1.2 | −77.3 | −177.2 | −311.3 | 0.0 | 50.6 | 84.0 | 97.1 | 100.4 | |
SD of NPV | Billion yen | 26.0 | 42.8 | 82.2 | 114.4 | 134.2 | 26.0 | 50.4 | 106.1 | 166.8 | 198.0 | |
CVaR of NPV | Billion yen | 319.0 | 251 | 69 | −167 | −379 | 319.0 | 353 | 338 | 283 | 227 |
Scenario | Case | 7 (Investments in PV with FIP-Low) | 8 (Investments in Wind with FIP-Low) | |||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|
Total Capacity | Unit | 0 | 1000 | 3000 | 5000 | 7000 | 0 | 1000 | 3000 | 5000 | 7000 | |
PV (Case 7) WIND _OE (Case 8) | Exp NPV | Billion yen | 372.9 | 335.8 | 221.1 | 67.7 | −129.6 | 372.9 | 339.2 | 212.3 | −15.5 | −316.1 |
Exp Value (Ref_EXP | - | 0.0 | −37.7 | −123.6 | −225.9 | −346.1 | 0.0 | −37.0 | −126.7 | −270.2 | −461.6 | |
Exp Value (Ref_CVaR) | - | 0.0 | 0.3 | −84.1 | −188.6 | −312.2 | 0.0 | 0.6 | −87.9 | −232.5 | −426.0 | |
SD of NPV | Billion yen | 26.0 | 40.0 | 65.7 | 91.7 | 105.8 | 26.0 | 48.1 | 97.7 | 141.0 | 167.7 | |
CVaR of NPV | Billion yen | 319.0 | 253.7 | 88.6 | −123.1 | −342.8 | 319.0 | 243.0 | 9.7 | −290.1 | −642.1 | |
PV (Case 7) WIND _OE (Case 8) | Exp NPV | Billion yen | 372.9 | 345.0 | 279.7 | 224.6 | 157.8 | 372.9 | 341.2 | 261.2 | 168.0 | 65.7 |
Exp Value (Ref_EX) | - | 0.0 | −32.5 | −92.9 | −138.4 | −170.8 | 0.0 | −36.5 | −113.5 | −179.0 | −249.4 | |
Exp. Value (Ref_CVaR) | - | 0.0 | 6.8 | −51.8 | −98.4 | −135.5 | 0.0 | −1.5 | −74.6 | −143.8 | −215.5 | |
SD of NPV | Billion yen | 26.0 | 32.8 | 65.9 | 92.9 | 122.7 | 26.0 | 40.0 | 93.2 | 150.3 | 201.0 | |
CVaR of NPV | Billion yen | 319.0 | 276.1 | 106.5 | −70.7 | −259.5 | 319.0 | 250.8 | 35.9 | −227.1 | −493.7 |
Scenario | Case | 9 (Investments in PV with FIP-Low) | 10 (Investments in PV with FIP-High) | |||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|
Total Capacity | Unit | 0 | 1000 | 3000 | 5000 | 7000 | 0 | 1000 | 3000 | 5000 | 7000 | |
PV (Case 9) WIND _OE (Case 10) | Exp. NPV | Billion yen | 372.9 | 407.8 | 440.9 | 441.7 | 367.8 | 372.9 | 466.2 | 580.2 | 604.4 | 520.4 |
Exp. Value (Ref_EXP) | - | 0.0 | 9.0 | 17.5 | 0.7 | −38.1 | 0.0 | 35.4 | 62.8 | 65.6 | 22.4 | |
Exp. Value (Ref_CVaR) | - | 0.0 | 34.7 | 43.7 | 29.1 | −8.6 | 0.0 | 57.9 | 85.7 | 90.2 | 49.1 | |
SD of NPV | Billion yen | 26.0 | 41.8 | 74.4 | 107.9 | 134.3 | 26.0 | 62.8 | 148.7 | 221.3 | 269.9 | |
CVaR of NPV | Billion yen | 319.0 | 324.7 | 294.4 | 201.4 | 89.5 | 319.0 | 346.0 | 282.6 | 164.6 | −21.0 | |
PV (Case 9) WIND _OE (Case 10) | Exp. NPV | Billion yen | 372.9 | 360.9 | 313.3 | 238.4 | 142.3 | 372.9 | 409.0 | 430.6 | 394.4 | 327.7 |
Exp. Value (Ref_EXP) | - | 0.0 | −19.7 | −62.1 | −115.5 | −173.7 | 0.0 | 10.2 | 8.7 | −22.1 | −72.5 | |
Exp. Value (Ref_CVaR) | - | 0.0 | 14.0 | −24.1 | −77.4 | −136.6 | 0.0 | 35.1 | 31.9 | 6.4 | −42.4 | |
SD of NPV | Billion yen | 26.0 | 37.9 | 67.8 | 96.2 | 141.4 | 26.0 | 49.3 | 116.7 | 174.5 | 216.9 | |
CVaR of NPV | Billion yen | 319.0 | 285.7 | 178.0 | 41.9 | −105.4 | 319.0 | 315.1 | 204.8 | 43.8 | −126.6 |
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Item | Normative | Prescriptive | Descriptive |
---|---|---|---|
Perspective [1] | How “rational” people should make decisions. | How less rational people, who aspire to rationality, might do better. | How people make decisions. |
Focused disciplines | Economics (Microeconomics, Game theory) | Business administration, Engineering | Psychology, Behavioral economics |
Typical theories/methods | NPV method, IRR method, Expected utility theory, Real options | Operations research (Multi-criteria Decision Making (MCDM), etc.) Management science | Prospect theory Regret theory Questionnaire surveys |
Application to decision making for energy investment | Real options [11,12,13,14] | Analytic hierarchy process (AHP) [18,19,20,21] Multi-attribute Utility Theory (MAUT) [23] | Qualitative questionnaire surveys and qualitative analysis [25,26,27,28] Quantitative PV investments of households [31] Energy saving investments of individuals [32] |
System Characteristic | Currently (as of 2020) | Future Expectation According to This Study |
---|---|---|
Electricity trade | Bilaterally over the counter | Spot price market (*) |
Electricity supply responsibility | Power generation companies | Transmission operators |
Financial support for renewables | Feed-in tariff | Feed-in premium |
Fuel price uncertainty risk | Passed on retail electricity price | Mainly covered by the income of the spot price market |
VRE Infrastructure | Period | |
---|---|---|
2025–2034 | 2035–2044 | |
PV | 4200 MW | 2100 MW |
Wind (onshore) | 150 MW | 75 MW |
Strategy | VRE | Capacity to be Invested [MW] | ||||||||
---|---|---|---|---|---|---|---|---|---|---|
0 MW | 1000 MW | 3000 MW | 5000 MW | 7000 MW | ||||||
PV_ONLY | PV | 0 | 1000 | 3000 | 5000 | 7000 | ||||
Wind | 0 | 0 | 0 | 0 | 0 | |||||
WIND_ONLY | PV | 0 | 0 | 0 | 0 | 0 | ||||
Wind | 0 | 1000 | 3000 | 5000 | 7000 | |||||
MIX1 (PV:Wind = 1:1) | PV | 0 | 500 | 1500 | 2500 | 3500 | ||||
Wind | 0 | 500 | 1500 | 2500 | 3500 | |||||
MIX2 (PV:Wind = 7:3) | PV | 0 | 700 | 2000 | 3500 | 4500 | ||||
Wind | 0 | 300 | 1000 | 1500 | 2500 | |||||
MIX3 (PV:Wind = 3:7) | PV | 0 | 300 | 1000 | 1500 | 2500 | ||||
Wind | 0 | 700 | 2000 | 3500 | 4500 | |||||
Option to Expand (OE) | 2025 | 2030 | 2025 | 2030 | 2025 | 2030 | 2025 | 2030 | ||
PV_OE | PV | 0 | 500 | 500 | 1500 | 1500 | 2500 | 2500 | 3500 | 3500 |
Wind | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | |
WIND_OE | PV | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
Wind | 0 | 500 | 500 | 1500 | 1500 | 2500 | 2500 | 3500 | 3500 |
Scenario Name | Thermal Power | Nuclear Power |
---|---|---|
wRP_NC60 (Base) | T-1 | N-1 |
wRP_NC40 | T-1 | N-2 |
woRP_NC60 | T-2 | N-1 |
Scenario Name | FIP [yen/kWh] | |
---|---|---|
PV | Wind (Offshore) | |
FIP-Low | 10 | 5 |
FIP-Mid | 12 | 8 |
FIP-High | 15 | 10 |
Fuel | Fuel Price | ||
---|---|---|---|
Low | Mode | High | |
Natural gas [$/Mbtu] | 8.8 | 9.7 | 11.0 |
Coal [$/ton] | 65 | 86 | 94 |
Oil [$/Barrel] | 62 | 88 | 111 |
Case No. | Strategy of Company 2 (Table 4) | Combination of Scenarios | |
---|---|---|---|
Company 1 (Table 5) | FIP Price (Table 6) | ||
1 | PV_ONLY | wRP_NC60 | FIP-Low FIP-Mid FIP-High |
2 | WIND_ONLY | wRP_NC60 | FIP-Low FIP-Mid FIP-High |
3 | PV_ONLY | wRP_NC60 wRP_NC40 woRP_NC60 | FIP-Low |
4 | WIND_ONLY | wRP_NC60 wRP_NC40 woRP_NC60 | FIP-Low |
5 | PV_ONLY_ MIX1(PV:Wind = 1:1) MIX2(PV:Wind = 7:3) MIX3(PV:Wind = 3:7) WIND_ONLY_ | wRP_NC60 | FIP-Low |
6 | PV_ONLY_ MIX1(PV:Wind = 1:1) MIX2(PV:Wind = 7:3) MIX3(PV:Wind = 3:7) WIND_ONLY_ | wRP_NC60 | FIP-High |
7 | PV_ONLY_ PV_OE | wRP_NC60 | FIP-Low |
8 | WIND_ONLY_ WIND_OE | wRP_NC60 | FIP-Low |
9 | PV_ONLY_ PV_OE | wRP_NC60 | FIP- High |
10 | WIND_ONLY_ WIND_OE | wRP_NC60 | FIP- High |
Reference Point Name | Remark |
---|---|
Ref_EXP | Expected value of NPV in the option of-0MW of each case (Higher RFP) |
Ref_CVaR | CVaR of NPV in the option of -0MW of each case (Lower RFP) |
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Gotoh, R.; Tezuka, T.; McLellan, B.C. Study on Behavioral Decision Making by Power Generation Companies Regarding Energy Transitions under Uncertainty. Energies 2022, 15, 654. https://doi.org/10.3390/en15020654
Gotoh R, Tezuka T, McLellan BC. Study on Behavioral Decision Making by Power Generation Companies Regarding Energy Transitions under Uncertainty. Energies. 2022; 15(2):654. https://doi.org/10.3390/en15020654
Chicago/Turabian StyleGotoh, Ryosuke, Tetsuo Tezuka, and Benjamin C. McLellan. 2022. "Study on Behavioral Decision Making by Power Generation Companies Regarding Energy Transitions under Uncertainty" Energies 15, no. 2: 654. https://doi.org/10.3390/en15020654