Determining Optimal Alternative Energy Technology Investments

Dr. John Eddy*Sandia National

Laboratories

Environment, Energy Security, Sustainment SymposiumNDIA National Defense

Industrial Association

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Jack GauthierSandia National

Laboratories

June 17, 2010

* Presenter

Overview

• Problem Statement

• Approach — TMO

• Problem Structure

• Input Data

• Results

• Conclusion

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Problem Statement

• How does an organization decide which alternative energy sources to invest in? And how much should be invested in each one?

How should the military direct funding to support the future energy needs of installations (bases, forward areas, etc.)?

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Problem Statement

• How should conflicting objectives and constraints be included in the decision?

– Time to realization

– Total cost (investment, deployment, sustainment)?

– Energy requirements

– Technological interdependencies

– Risk

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Problem Statement

• Goal—to demonstrate a structure and a tool (TMO) that can address the problem of developing a defensible investment strategy– Build a roadmap indicating what investments should be

made and when the investments should be made

• This work is a Proof of Concept– Not all issues are addressed

– Not all possible alternative energy investments are addressed

– Data are notional

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Technology Management Optimization (TMO)

• TMO is produces optimal planning roadmaps– TMO performs time-based optimization – TMO considers time-based, user-defined

objectives and constraints (e.g., load-leveling of costs)

– TMO respects technology dependencies (e.g., power)

• TMO is used to address a range of difficult problems– Technology management– System design—e.g., power generation

selection and layout– Trade studies—e.g. Stryker modernization – Decision support—e.g., energy policy

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Technology Management Optimization (TMO)

• TMO runs on a PC• TMO advances the field

of optimization– Optimizes over time

• The technology behind TMO was a Sandia nominee for an R&D100 Award in 2009

• Can handle very large problem spaces.

TMO produces quantitative, optimal planning roadmaps

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TMO Advanced Features

In addition to a roadmap, TMO includes…• reliability analysis, • satisfaction of the objectives and constraints, • satisfaction of dependencies• multi-objective optimization• a visualization method that allows the user to interactively manipulate the multi-objective optimization results

Investment Problem Structure1. What issues are important to the organization?

– Budget – How soon can the technology be realized? – Investments must be made in both transportation and power generation technologies– Cost of investment, deployment, and sustainment – Other—low CO2, infrastructure, logistics footprint, energy density, etc. *

2. What are the energy options? – Transportation…H2 fuel cell, biodiesel, E2P– Power generation…wind, solar PV, small nuclear reactor– Storage…battery, capacitor, E2H

3. For each energy option, what are the investment alternatives? – Do not consider (do not use at all)– Use current technology (no investment—allows dependencies to be respected) – $/yr for the number of years until the technology is realized

4. How would each investment alternative affect the issues that are important?

5. What are the dependencies between the alternatives?

9* Not considered in this Proof of Concept

Input Data Note: Data are notional

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Generation Technologies Considered: Investment Levels

Wind Do Not Consider

No Investment

$5M/yr for 5 years

$10M/yr for 3 years

Solar PV Do Not Consider

No Investment

$8M/yr for 8 years

$15M/yr for 5 years

Small Nuclear Reactor Do Not Consider

$15M/yr for 12 years

$30M/yr for 8 years

H2 Fuel Cells …

Bio-Diesel …

Electricity – to – Petrol (E2P) …

Input Data Note: Data are notional

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Storage Technologies Considered: Investment Levels

Battery Do Not Consider

No Investment

$3M/yr for 10 years

$10M/yr for 5 years

Capacitor Do Not Consider

No Investment

$2M/yr for 12 years

$10M/yr for 5 years

Electricity - to – Hydrogen (E2H) Do Not Consider

$2M/yr for 9 years

$4M/yr for 5 years

Input Data

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Dependencies:

Technology Depends on:

Wind Battery or Capacitor for storage.

Solar PV Battery or Capacitor for storage.

H2 Fuel Cells Electricity – to – Hydrogen (E2H)

Results

• TMO was used to solve for yearly investments over a 20-year interval beginning in 2011

• TMO runtime < 1 min

– Solution space = ~10100 possible investment strategies

• Optimal solution respects all objectives and constraints

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Investment Roadmap

$3M/yr

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Constraint Satisfaction

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Also, investments in both transportation and power generation technologies were scheduled

Conclusions

• Proof of concept successful

– Spent our desired budget amount while minimizing other costs.

• Lessons learned

– Alternative formulations could solve for the $/yr directly

– Should add potential outcome & risk to each investment.

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