Development of a Tool for Optimizing Solar and Battery Storage for Container Farming in a Remote Arctic Microgrid
High transportation costs make energy and food expensive in remote communities worldwide, especially in high-latitude Arctic climates. Past attempts to grow food indoors in these remote areas have proven uneconomical due to the need for expensive imported diesel for heating and electricity. This stu...
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| Format: | Article |
| Language: | English |
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MDPI AG
2020-10-01
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| Series: | Energies |
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| Online Access: | https://www.mdpi.com/1996-1073/13/19/5143 |
| _version_ | 1797551974781026304 |
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| author | Daniel J. Sambor Michelle Wilber Erin Whitney Mark Z. Jacobson |
| author_facet | Daniel J. Sambor Michelle Wilber Erin Whitney Mark Z. Jacobson |
| author_sort | Daniel J. Sambor |
| collection | DOAJ |
| description | High transportation costs make energy and food expensive in remote communities worldwide, especially in high-latitude Arctic climates. Past attempts to grow food indoors in these remote areas have proven uneconomical due to the need for expensive imported diesel for heating and electricity. This study aims to determine whether solar photovoltaic (PV) electricity can be used affordably to power container farms integrated with a remote Arctic community microgrid. A mixed-integer linear optimization model (FEWMORE: Food–Energy–Water Microgrid Optimization with Renewable Energy) has been developed to minimize the capital and maintenance costs of installing solar photovoltaics (PV) plus electricity storage and the operational costs of purchasing electricity from the community microgrid to power a container farm. FEWMORE expands upon previous models by simulating demand-side management of container farm loads. Its results are compared with those of another model (HOMER) for a test case. FEWMORE determined that 17 kW of solar PV was optimal to power the farm loads, resulting in a total annual cost decline of ~14% compared with a container farm currently operating in the Yukon. Managing specific loads appropriately can reduce total costs by ~18%. Thus, even in an Arctic climate, where the solar PV system supplies only ~7% of total load during the winter and ~25% of the load during the entire year, investing in solar PV reduces costs. |
| first_indexed | 2024-03-10T15:53:27Z |
| format | Article |
| id | doaj.art-f8994e8b194741c68bf354458ec2e45c |
| institution | Directory Open Access Journal |
| issn | 1996-1073 |
| language | English |
| last_indexed | 2024-03-10T15:53:27Z |
| publishDate | 2020-10-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Energies |
| spelling | doaj.art-f8994e8b194741c68bf354458ec2e45c2023-11-20T15:54:38ZengMDPI AGEnergies1996-10732020-10-011319514310.3390/en13195143Development of a Tool for Optimizing Solar and Battery Storage for Container Farming in a Remote Arctic MicrogridDaniel J. Sambor0Michelle Wilber1Erin Whitney2Mark Z. Jacobson3Department of Civil and Environmental Engineering, Stanford University, Stanford, CA 94305, USAAlaska Center for Energy and Power, University of Alaska Fairbanks, Fairbanks, AK 99775, USAAlaska Center for Energy and Power, University of Alaska Fairbanks, Fairbanks, AK 99775, USADepartment of Civil and Environmental Engineering, Stanford University, Stanford, CA 94305, USAHigh transportation costs make energy and food expensive in remote communities worldwide, especially in high-latitude Arctic climates. Past attempts to grow food indoors in these remote areas have proven uneconomical due to the need for expensive imported diesel for heating and electricity. This study aims to determine whether solar photovoltaic (PV) electricity can be used affordably to power container farms integrated with a remote Arctic community microgrid. A mixed-integer linear optimization model (FEWMORE: Food–Energy–Water Microgrid Optimization with Renewable Energy) has been developed to minimize the capital and maintenance costs of installing solar photovoltaics (PV) plus electricity storage and the operational costs of purchasing electricity from the community microgrid to power a container farm. FEWMORE expands upon previous models by simulating demand-side management of container farm loads. Its results are compared with those of another model (HOMER) for a test case. FEWMORE determined that 17 kW of solar PV was optimal to power the farm loads, resulting in a total annual cost decline of ~14% compared with a container farm currently operating in the Yukon. Managing specific loads appropriately can reduce total costs by ~18%. Thus, even in an Arctic climate, where the solar PV system supplies only ~7% of total load during the winter and ~25% of the load during the entire year, investing in solar PV reduces costs.https://www.mdpi.com/1996-1073/13/19/5143microgridcontainer farmsolar photovoltaics (PV)renewable energystorage |
| spellingShingle | Daniel J. Sambor Michelle Wilber Erin Whitney Mark Z. Jacobson Development of a Tool for Optimizing Solar and Battery Storage for Container Farming in a Remote Arctic Microgrid Energies microgrid container farm solar photovoltaics (PV) renewable energy storage |
| title | Development of a Tool for Optimizing Solar and Battery Storage for Container Farming in a Remote Arctic Microgrid |
| title_full | Development of a Tool for Optimizing Solar and Battery Storage for Container Farming in a Remote Arctic Microgrid |
| title_fullStr | Development of a Tool for Optimizing Solar and Battery Storage for Container Farming in a Remote Arctic Microgrid |
| title_full_unstemmed | Development of a Tool for Optimizing Solar and Battery Storage for Container Farming in a Remote Arctic Microgrid |
| title_short | Development of a Tool for Optimizing Solar and Battery Storage for Container Farming in a Remote Arctic Microgrid |
| title_sort | development of a tool for optimizing solar and battery storage for container farming in a remote arctic microgrid |
| topic | microgrid container farm solar photovoltaics (PV) renewable energy storage |
| url | https://www.mdpi.com/1996-1073/13/19/5143 |
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