WESTERN ECOSYSTEMS TECHNOLOGY, INC. — Department of Agriculture SBIR Phase I: 8.119999999999999
WESTERN ECOSYSTEMS TECHNOLOGY, INC. — SBIR Phase I award from Department of Agriculture.
Phase I SBIR feasibility signal
- Phase I awards fund proof-of-concept work. For capture teams, they mark early interest from Department of Agriculture in a technical approach.
- Watch for Phase II follow-ons from the same firm/topic family — that conversion path is where budgets and transition pressure rise.
- Obligated amount $56,068. Cross-check similar awards in the same agency and technology tags for going-rate context.
- Topic code 8.119999999999999 links this award to a solicitation family — search the same topic stem for incumbents and recompete timing.
- Amount
- $56,068
- Agency
- Department of Agriculture
- Program / Phase
- SBIR · Phase I
- Topic
- 8.119999999999999
- Solicitation
- USDA-NIFA-SBIR-007726
- NAICS
- —
- Place of performance
- WY
- Period
- 2021-05-03 → 2022-02-28
Description
Revenue from wind energy is an important source of stable income for small and mid-size farms asthe agricultural sector becomes more volatile. One of the biggest challenges facing wind energydevelopment on small and mid-sized farms are the adverse effects of wind farms on bats. To reducecollision-related mortality of bats curtailment -- stopping wind turbines from spinning during timesof high bat activity -- is employed. While beneficial for bats curtailment results in lost renewableenergy and lost revenue which reduces the annual lease payment to small and mid-size farms. Thisproject aims to develop next-generation smart curtailment algorithms that save just as many bats ascurrent technologies for less lost renewable energy. Smart curtailment involves fitting an algorithmto environmental data to predict times that are risky for bats (times to curtail) or not (times to notcurtail). No current technologies acknowledge the dynamic cost of curtailment across wind speeds.The project team will design and implement a dynamic cost function for decision tree algorithms.The dynamic cost function will allow the algorithm to optimize a smart curtailment regime byexplicitly accounting for the cost of curtailment at different wind speeds (the cost of curtailment isproportional to a cubic function of wind speed). The new software will be applied to prototypicaldata to assess its efficacy. The proposed software solution will create a win-win-win for batconservation small and mid-size farms that receive a share of wind energy revenues and renewableenergy generation in the US.