Smart District Energy Management With Cooperative Microgrids
This paper faces the energy management problem of cooperative microgrids in a smart energy district. In particular, the aim of the research work is to propose an innovative optimization model to solve the problem of energy management in a district composed of several microgrids, taking into account...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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IEEE
2022-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/9745554/ |
| _version_ | 1818669115904098304 |
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| author | Michele Roccotelli Agostino Marcello Mangini Maria Pia Fanti |
| author_facet | Michele Roccotelli Agostino Marcello Mangini Maria Pia Fanti |
| author_sort | Michele Roccotelli |
| collection | DOAJ |
| description | This paper faces the energy management problem of cooperative microgrids in a smart energy district. In particular, the aim of the research work is to propose an innovative optimization model to solve the problem of energy management in a district composed of several microgrids, taking into account uncertainties of key parameters. In this context, the objective of the paper is threefold: i) maximize the use of energy purchased at the day-ahead market; ii) minimize the need of additional and expensive energy in real-time iii) optimize the integration of renewable energy sources (RES), energy storage systems (ESS) and electric vehicle (EV) batteries in the microgrid. To these goals, the District Energy Management System (DEMS), i.e. the central controller of the district, must balance the microgrids energy demand with the optimal integration of RES, ESS and the batteries of EVs that are seen as movable storage devices shared among buildings. Moreover, the energy surplus can be sold back to the main power grid. The DEMS problem is solved by two approaches. In the first approach, the energy demand, the RES production and the costs are known and a linear programming problem is formalized and solved by the DEMS. In addition, a second approach is proposed in order to address the parameters uncertainty and is formalized as a stochastic linear programming problem. The optimization problems solutions provide the optimal strategy to schedule the charging and discharging operations of the storage systems and the electric vehicle batteries. A simulated case study demonstrates the benefits of the proposed approaches for the smart district. |
| first_indexed | 2024-12-17T06:47:05Z |
| format | Article |
| id | doaj.art-8ce03e0815a640cdb45ed7f0619f2518 |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-17T06:47:05Z |
| publishDate | 2022-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-8ce03e0815a640cdb45ed7f0619f25182022-12-21T21:59:42ZengIEEEIEEE Access2169-35362022-01-0110363113632610.1109/ACCESS.2022.31637249745554Smart District Energy Management With Cooperative MicrogridsMichele Roccotelli0https://orcid.org/0000-0003-3045-8920Agostino Marcello Mangini1https://orcid.org/0000-0001-6850-6153Maria Pia Fanti2https://orcid.org/0000-0002-8612-1852Department of Electrical and Information Engineering, Polytechnic University of Bari, Bari, ItalyDepartment of Electrical and Information Engineering, Polytechnic University of Bari, Bari, ItalyDepartment of Electrical and Information Engineering, Polytechnic University of Bari, Bari, ItalyThis paper faces the energy management problem of cooperative microgrids in a smart energy district. In particular, the aim of the research work is to propose an innovative optimization model to solve the problem of energy management in a district composed of several microgrids, taking into account uncertainties of key parameters. In this context, the objective of the paper is threefold: i) maximize the use of energy purchased at the day-ahead market; ii) minimize the need of additional and expensive energy in real-time iii) optimize the integration of renewable energy sources (RES), energy storage systems (ESS) and electric vehicle (EV) batteries in the microgrid. To these goals, the District Energy Management System (DEMS), i.e. the central controller of the district, must balance the microgrids energy demand with the optimal integration of RES, ESS and the batteries of EVs that are seen as movable storage devices shared among buildings. Moreover, the energy surplus can be sold back to the main power grid. The DEMS problem is solved by two approaches. In the first approach, the energy demand, the RES production and the costs are known and a linear programming problem is formalized and solved by the DEMS. In addition, a second approach is proposed in order to address the parameters uncertainty and is formalized as a stochastic linear programming problem. The optimization problems solutions provide the optimal strategy to schedule the charging and discharging operations of the storage systems and the electric vehicle batteries. A simulated case study demonstrates the benefits of the proposed approaches for the smart district.https://ieeexplore.ieee.org/document/9745554/Electric vehicleenergy storagemicrogridoptimizationrenewable energysmart district |
| spellingShingle | Michele Roccotelli Agostino Marcello Mangini Maria Pia Fanti Smart District Energy Management With Cooperative Microgrids IEEE Access Electric vehicle energy storage microgrid optimization renewable energy smart district |
| title | Smart District Energy Management With Cooperative Microgrids |
| title_full | Smart District Energy Management With Cooperative Microgrids |
| title_fullStr | Smart District Energy Management With Cooperative Microgrids |
| title_full_unstemmed | Smart District Energy Management With Cooperative Microgrids |
| title_short | Smart District Energy Management With Cooperative Microgrids |
| title_sort | smart district energy management with cooperative microgrids |
| topic | Electric vehicle energy storage microgrid optimization renewable energy smart district |
| url | https://ieeexplore.ieee.org/document/9745554/ |
| work_keys_str_mv | AT micheleroccotelli smartdistrictenergymanagementwithcooperativemicrogrids AT agostinomarcellomangini smartdistrictenergymanagementwithcooperativemicrogrids AT mariapiafanti smartdistrictenergymanagementwithcooperativemicrogrids |