01/08/2009 Using Wind Energy to Offset Irrigation Costs: A Systems-Modeling Case Study Dustin Shively Todd Haynes Dr. John Gardner Department of Mechanical and Biomedical Engineering Boise State University

01/08/2009 Introduction Farm in Southern Idaho (SWI) Water is pumped from a stream 300 feet up a plateau During the most intensive pumping months, over $100,000 per month for electricity Total spent in 2006 for electricity: $431,192 17% from demand charge Anemometer data for over three years 3 – GE 1.5MW turbines

01/08/2009 Introduction

01/08/2009 Analysis PURPA HOMER analysis indicated economically infeasible at current rates Net-Metering 2 MW power capacity (Idaho currently only allows 100 kW) Under a net-metering contract, SWI Farm would pay ~25% less than 2006 Storage Options may exist using wind energy to: 1.Pump and store water 2.Store energy 3.both

01/08/2009 Analysis Store Water Volume of water needed ? Store Energy Amount of energy needed Energy → Power avg → Flowrate avg → Volume

01/08/2009 Modeling Store Water GE 1.5MW wind turbine power curves used Water cannot be pumped during winter months Five turbines required to cover demand Irrigation Season Begins

01/08/2009 Results Store Water

01/08/2009 Modeling Store Energy Compressed Air Energy Storage, CAES Bulk energy storage system Site specific Requires combustion of natural gas CAES Development Company Princeton Environmental Institute ~75% of the US has geology suitable for CAES

01/08/2009 Modeling Store Energy GE 1.5MW wind turbine power curves used Seven turbines required to cover demand CAES system ~50% efficient Irrigation Season Begins

01/08/2009 Results Store Energy

01/08/2009 Economics Amount paid to utility Store Energy$0 Store Water$0 Net Metering$330,000 Amount avoided to utility Store Energy$431,192 Store Water$431,192 Net Metering$101,192 Number of turbines decided such that all payments to the utility could be avoided. Net metering still has a 2MW capacity, which only allows a single 1.5MW turbine to be used

01/08/2009 Economics Capital Costs Storing Energy Turbines (7)$14,000,000 CAES System$135,000,000 Total$149,000,000 Storing Water Turbines (5)$10,000,000 Additional Reservoirs$30,000 Total$10,030,000 Net Metering Turbines (1)$2,000,000 Simple Payback (years) Store Energy346 Store Water23 Net Metering20

01/08/2009 Re-Configure $$ paid to utility Number of turbines Capital Costs Payback?

01/08/2009 Analysis If fewer turbines are used in both configurations (storing energy/water), the storage in either case will not be sufficient to cover demand. Most effective way to use stored energy/water: 1.Neglect running pumps as long as possible, use stored energy/water early in the season 2.Run pumps from grid in the beginning of the season, use stored energy/water late in the season during high cost months

01/08/2009 Results Store Water Scenario 1: Use stored water early in season Scenario 2: Use stored water late in season

01/08/2009 Results Store Energy Scenario 1: Use stored energy early in season Scenario 2: Use stored energy late in season

01/08/2009 Economics Status Quo Time of use pricing Store Energy Use storage early$257,342$275,818 Use storage late$239,276$237,879 Distribute storage evenly$299,881$291,644 Store Water Use storage early$173,354$170,462 Use storage late$158,532$158,057 Distribute storage evenly$197,532$201,181 Net Metering $330,000 Original$431,192 Two economic scenarios : 1.Status Quo: cost of electricity and demand charges equal to those from Time of Use Pricing: variation in cost of electricity over the course of the year. Base rate for nine months and a graduated rate for the three summer months. Amount paid to utility

01/08/2009 Economics Capital Costs Storing Energy Turbines (3)$6,000,000 CAES System$135,000,000 Storing Water Turbines (3)$6,000,000 Additional Reservoirs$30,000 Net Metering Turbines (1)$2,000,000

01/08/2009 Economics Status Quo Time of use pricing Store Energy Use storage early Use storage late Distribute storage evenly1,0741,010 Store Water Use storage early23 Use storage late22 Distribute storage evenly26 Net Metering 20 Simple Payback (years)

01/08/2009 Conclusion None of the scenarios analyzed appear to be economically feasible. The system-modeling method does allow the freedom to examine the interaction of the wind with the pumps and storage facilities. By inputting actual anemometer data and detailed pumping costs, this technique can accurately reflect the individual sites performance of such a system.

01/08/2009 Acknowledgements National Renewable Energy Laboratory Wind Powering America Todd Haynes, Boise State University John Gardner, Boise State University Idaho National Laboratory Gerald Fleischman, Idaho Office of Energy Resources