Abstract
Renewable energy technologies are becoming increasingly important due to their cost-competitiveness, and because of enhanced climate concerns. We demonstrate the capabilities of an integer-programming optimization model that minimizes capital (investment) and operational costs, and utility charges, while adhering to system sizing constraints, demand requirements, and interoperability characteristics of the systems chosen. The model recommends an optimally sized mix of renewable energy, conventional generation, and energy storage technologies, while simultaneously optimizing the corresponding dispatch strategy. Our case studies explore several venues, i.e., a small campus and a local hospital, with complex utility rate tariffs, multi-technology integration opportunities, and incentives for renewable power production. Using an optimization model, versus applying rules of thumb, can produce millions of dollars in savings over a 25-year time horizon and result in thousands of kilowatts of installed renewable energy.
Original language | American English |
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Article number | 116527 |
Number of pages | 17 |
Journal | Applied Energy |
Volume | 287 |
DOIs | |
State | Published - 2021 |
Bibliographical note
Publisher Copyright:© 2021 Elsevier Ltd
NREL Publication Number
- NREL/JA-7A40-78610
Keywords
- Battery storage
- Dispatch optimization
- Grid integration
- Mixed-integer linear programming
- Renewable energy technologies
- Systems analysis