Multi-Agent Based Optimal Operation of Hybrid Energy Sources Coupled with Demand Response Programs
Electricity is an indispensable commodity on which both urban and rural regions heavily rely. Rural areas where the main grid cannot reach make use of distributed energy resources (DER), especially renewable energy sources (RES), in an islanded microgrid. Therefore, it is necessary to make sure ther...
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doaj-b5630308d8bc4807aa7c22f2da23464f2021-07-23T14:07:37ZengMDPI AGSustainability2071-10502021-07-01137756775610.3390/su13147756Multi-Agent Based Optimal Operation of Hybrid Energy Sources Coupled with Demand Response ProgramsTope Roseline Olorunfemi0Nnamdi I. Nwulu1Department of Electrical and Electronic Engineering Science, University of Johannesburg, Johannesburg 2006, South AfricaDepartment of Electrical and Electronic Engineering Science, University of Johannesburg, Johannesburg 2006, South AfricaElectricity is an indispensable commodity on which both urban and rural regions heavily rely. Rural areas where the main grid cannot reach make use of distributed energy resources (DER), especially renewable energy sources (RES), in an islanded microgrid. Therefore, it is necessary to make sure there is a sufficient power supply to balance the demand and supply curve and meet people’s demands. The work done in this paper aims to minimize the daily operating cost of the hybrid microgrid while incorporating a demand response strategy built on an incentive-based demand response (IBDR) model. Three case studies were constructed and analyzed to derive the best, most reduced daily operational cost. This was achieved using the CPLEX solver embedded in algebraic modeling language in the Advanced Interactive Multidimensional Modeling Systems (AIMMS) software with multi-agent system (MAS); the MAS was used to make sure that the developed intelligent-based agents work independently to achieve an optimal microgrid system. The sensitivity analysis employed established that case study 2 gave the most reduced daily operation cost (USD 119), which represents an 8% reduction in the daily operational cost from case study 1 and a 9% reduction from case study 3. Then, we achieved 17% and 25% reductions, as compared to specific other approaches.https://www.mdpi.com/2071-1050/13/14/7756demand responsedistributed energy resourcesincentive-based DRmulti-agent systemrenewable energy sources |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Tope Roseline Olorunfemi Nnamdi I. Nwulu |
spellingShingle |
Tope Roseline Olorunfemi Nnamdi I. Nwulu Multi-Agent Based Optimal Operation of Hybrid Energy Sources Coupled with Demand Response Programs Sustainability demand response distributed energy resources incentive-based DR multi-agent system renewable energy sources |
author_facet |
Tope Roseline Olorunfemi Nnamdi I. Nwulu |
author_sort |
Tope Roseline Olorunfemi |
title |
Multi-Agent Based Optimal Operation of Hybrid Energy Sources Coupled with Demand Response Programs |
title_short |
Multi-Agent Based Optimal Operation of Hybrid Energy Sources Coupled with Demand Response Programs |
title_full |
Multi-Agent Based Optimal Operation of Hybrid Energy Sources Coupled with Demand Response Programs |
title_fullStr |
Multi-Agent Based Optimal Operation of Hybrid Energy Sources Coupled with Demand Response Programs |
title_full_unstemmed |
Multi-Agent Based Optimal Operation of Hybrid Energy Sources Coupled with Demand Response Programs |
title_sort |
multi-agent based optimal operation of hybrid energy sources coupled with demand response programs |
publisher |
MDPI AG |
series |
Sustainability |
issn |
2071-1050 |
publishDate |
2021-07-01 |
description |
Electricity is an indispensable commodity on which both urban and rural regions heavily rely. Rural areas where the main grid cannot reach make use of distributed energy resources (DER), especially renewable energy sources (RES), in an islanded microgrid. Therefore, it is necessary to make sure there is a sufficient power supply to balance the demand and supply curve and meet people’s demands. The work done in this paper aims to minimize the daily operating cost of the hybrid microgrid while incorporating a demand response strategy built on an incentive-based demand response (IBDR) model. Three case studies were constructed and analyzed to derive the best, most reduced daily operational cost. This was achieved using the CPLEX solver embedded in algebraic modeling language in the Advanced Interactive Multidimensional Modeling Systems (AIMMS) software with multi-agent system (MAS); the MAS was used to make sure that the developed intelligent-based agents work independently to achieve an optimal microgrid system. The sensitivity analysis employed established that case study 2 gave the most reduced daily operation cost (USD 119), which represents an 8% reduction in the daily operational cost from case study 1 and a 9% reduction from case study 3. Then, we achieved 17% and 25% reductions, as compared to specific other approaches. |
topic |
demand response distributed energy resources incentive-based DR multi-agent system renewable energy sources |
url |
https://www.mdpi.com/2071-1050/13/14/7756 |
work_keys_str_mv |
AT toperoselineolorunfemi multiagentbasedoptimaloperationofhybridenergysourcescoupledwithdemandresponseprograms AT nnamdiinwulu multiagentbasedoptimaloperationofhybridenergysourcescoupledwithdemandresponseprograms |
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