Abstract
This paper proposes a multi-agent system based microgrid energy management framework to balance the energy supply and demand by feasibly integrating the distributed energy storage and demand response (DR). The main contribution of this paper is an energy management system which schedules the operation of distributed energy storage systems (DESSs) and DR loads based on the day-ahead forecast data to minimise the energy mismatches in the system by taking the preferences set by the owners and life depletion costs of DESSs. The target schedule prepared based on the forecast information is adjusted in real-time to compromise the uncertainties and forecast errors. Besides scheduling the energy resources, the proposed management systems organises an energy spot market to settle the energy demand and supply quotes of end-users and distributed generators (DGs). The developed multi-agent systems is applied to a microgrid case study to verify its performance. The simulation results and their analysis suggest that the proposed microgrid energy management system is effective in managing the energy under uncertainties.
| Original language | English |
|---|---|
| Pages | 1-5 |
| Number of pages | 5 |
| DOIs | |
| Publication status | Published - Apr 27 2017 |
| Event | 2016 IEEE International Conference on Power Electronics, Drives and Energy Systems, PEDES 2016 - Trivandrum, Kerala, India Duration: Dec 14 2016 → Dec 17 2016 |
Conference
| Conference | 2016 IEEE International Conference on Power Electronics, Drives and Energy Systems, PEDES 2016 |
|---|---|
| Country | India |
| City | Trivandrum, Kerala |
| Period | 12/14/16 → 12/17/16 |
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ASJC Scopus subject areas
- Automotive Engineering
- Electrical and Electronic Engineering
- Energy Engineering and Power Technology
- Mechanical Engineering
Cite this
A Multi-Agent System for Energy Management in Smart Microgrids with Distributed Energy Storage and Demand Response. / Nunna, Kumar; Srinivasan, Dipti.
2017. 1-5 Paper presented at 2016 IEEE International Conference on Power Electronics, Drives and Energy Systems, PEDES 2016, Trivandrum, Kerala, India.Research output: Contribution to conference › Paper
}
TY - CONF
T1 - A Multi-Agent System for Energy Management in Smart Microgrids with Distributed Energy Storage and Demand Response
AU - Nunna, Kumar
AU - Srinivasan, Dipti
PY - 2017/4/27
Y1 - 2017/4/27
N2 - This paper proposes a multi-agent system based microgrid energy management framework to balance the energy supply and demand by feasibly integrating the distributed energy storage and demand response (DR). The main contribution of this paper is an energy management system which schedules the operation of distributed energy storage systems (DESSs) and DR loads based on the day-ahead forecast data to minimise the energy mismatches in the system by taking the preferences set by the owners and life depletion costs of DESSs. The target schedule prepared based on the forecast information is adjusted in real-time to compromise the uncertainties and forecast errors. Besides scheduling the energy resources, the proposed management systems organises an energy spot market to settle the energy demand and supply quotes of end-users and distributed generators (DGs). The developed multi-agent systems is applied to a microgrid case study to verify its performance. The simulation results and their analysis suggest that the proposed microgrid energy management system is effective in managing the energy under uncertainties.
AB - This paper proposes a multi-agent system based microgrid energy management framework to balance the energy supply and demand by feasibly integrating the distributed energy storage and demand response (DR). The main contribution of this paper is an energy management system which schedules the operation of distributed energy storage systems (DESSs) and DR loads based on the day-ahead forecast data to minimise the energy mismatches in the system by taking the preferences set by the owners and life depletion costs of DESSs. The target schedule prepared based on the forecast information is adjusted in real-time to compromise the uncertainties and forecast errors. Besides scheduling the energy resources, the proposed management systems organises an energy spot market to settle the energy demand and supply quotes of end-users and distributed generators (DGs). The developed multi-agent systems is applied to a microgrid case study to verify its performance. The simulation results and their analysis suggest that the proposed microgrid energy management system is effective in managing the energy under uncertainties.
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U2 - 10.1109/PEDES.2016.7914490
DO - 10.1109/PEDES.2016.7914490
M3 - Paper
SP - 1
EP - 5
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