Multi-class energy management for peer-to-peer energy trading driven by prosumer preferences
This paper proposes a peer-to-peer energy market platform based on the new concept of multiclass energy management, to coordinate trading between prosumers with heterogeneous (i.e., beyond purely financial) preferences. Power networks are undergoing a fundamental transition, with traditionally passi...
| Hauptverfasser: | , |
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| Format: | Journal article |
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IEEE
2018
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| _version_ | 1826297456877371392 |
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| author | Morstyn, T McCulloch, M |
| author_facet | Morstyn, T McCulloch, M |
| author_sort | Morstyn, T |
| collection | OXFORD |
| description | This paper proposes a peer-to-peer energy market platform based on the new concept of multiclass energy management, to coordinate trading between prosumers with heterogeneous (i.e., beyond purely financial) preferences. Power networks are undergoing a fundamental transition, with traditionally passive distribution network consumers becoming “prosumers”; proactive consumers that actively manage their production and consumption of energy. The paper introduces the new concept of energy classes, allowing energy to be treated as a heterogeneous product, based on attributes of its source, which are perceived by prosumers to have value. Examples include generation technology, location in the network and owner's reputation. The proposed peer-to-peer energy market platform coordinates trading between subscribed prosumers and the wholesale electricity market, to minimize costs associated with losses and battery depreciation, while providing added value by accounting for the prosumers’ individual preferences for the source/destination of the energy they consume/produce. The decomposable structure of the multiclass energy management problem is exploited to devise a distributed price-directed optimization mechanism, providing scalability and prosumer data privacy. Receding horizon model predictive control allows the prosumers to adjust their planned power flows based on the wholesale energy price, and up-to-date renewable generation and load predictions. |
| first_indexed | 2024-03-07T04:31:54Z |
| format | Journal article |
| id | oxford-uuid:ce9d9f41-bc1b-481c-b781-8bf1b3f76f27 |
| institution | University of Oxford |
| last_indexed | 2024-03-07T04:31:54Z |
| publishDate | 2018 |
| publisher | IEEE |
| record_format | dspace |
| spelling | oxford-uuid:ce9d9f41-bc1b-481c-b781-8bf1b3f76f272022-03-27T07:36:48ZMulti-class energy management for peer-to-peer energy trading driven by prosumer preferencesJournal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:ce9d9f41-bc1b-481c-b781-8bf1b3f76f27Symplectic Elements at OxfordIEEE2018Morstyn, TMcCulloch, MThis paper proposes a peer-to-peer energy market platform based on the new concept of multiclass energy management, to coordinate trading between prosumers with heterogeneous (i.e., beyond purely financial) preferences. Power networks are undergoing a fundamental transition, with traditionally passive distribution network consumers becoming “prosumers”; proactive consumers that actively manage their production and consumption of energy. The paper introduces the new concept of energy classes, allowing energy to be treated as a heterogeneous product, based on attributes of its source, which are perceived by prosumers to have value. Examples include generation technology, location in the network and owner's reputation. The proposed peer-to-peer energy market platform coordinates trading between subscribed prosumers and the wholesale electricity market, to minimize costs associated with losses and battery depreciation, while providing added value by accounting for the prosumers’ individual preferences for the source/destination of the energy they consume/produce. The decomposable structure of the multiclass energy management problem is exploited to devise a distributed price-directed optimization mechanism, providing scalability and prosumer data privacy. Receding horizon model predictive control allows the prosumers to adjust their planned power flows based on the wholesale energy price, and up-to-date renewable generation and load predictions. |
| spellingShingle | Morstyn, T McCulloch, M Multi-class energy management for peer-to-peer energy trading driven by prosumer preferences |
| title | Multi-class energy management for peer-to-peer energy trading driven by prosumer preferences |
| title_full | Multi-class energy management for peer-to-peer energy trading driven by prosumer preferences |
| title_fullStr | Multi-class energy management for peer-to-peer energy trading driven by prosumer preferences |
| title_full_unstemmed | Multi-class energy management for peer-to-peer energy trading driven by prosumer preferences |
| title_short | Multi-class energy management for peer-to-peer energy trading driven by prosumer preferences |
| title_sort | multi class energy management for peer to peer energy trading driven by prosumer preferences |
| work_keys_str_mv | AT morstynt multiclassenergymanagementforpeertopeerenergytradingdrivenbyprosumerpreferences AT mccullochm multiclassenergymanagementforpeertopeerenergytradingdrivenbyprosumerpreferences |