Intelligent Multi-Agent Based Multilayered Control System for Opportunistic Load Scheduling in Smart Buildings
Today’s power systems are subject to the high penetration of dynamic load. Volatility and intermittency of the dynamic load demand need to be compensated through optimization and scheduling without compromising user comfort. This paper proposes a multi-agent-based multi-layered hierarchic...
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| Format: | Article |
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IEEE
2019-01-01
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| Online Access: | https://ieeexplore.ieee.org/document/8643826/ |
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| author | Muhammad Babar Rasheed Nadeem Javaid Muhammad Sheraz Arshad Malik Muhammad Asif Muhammad Kashif Hanif Muhammad Hasanain Chaudary |
| author_facet | Muhammad Babar Rasheed Nadeem Javaid Muhammad Sheraz Arshad Malik Muhammad Asif Muhammad Kashif Hanif Muhammad Hasanain Chaudary |
| author_sort | Muhammad Babar Rasheed |
| collection | DOAJ |
| description | Today’s power systems are subject to the high penetration of dynamic load. Volatility and intermittency of the dynamic load demand need to be compensated through optimization and scheduling without compromising user comfort. This paper proposes a multi-agent-based multi-layered hierarchical control system for residential load management under real-time pricing environment. The major objectives are to reduce peak load demand, electricity cost, and user discomfort. In doing so, different types of agents, i.e., price agent <inline-formula> <tex-math notation="LaTeX">$p_{a}$ </tex-math></inline-formula>, sensor agent <inline-formula> <tex-math notation="LaTeX">$s_{a}$ </tex-math></inline-formula>, decision agent <inline-formula> <tex-math notation="LaTeX">$d_{a}$ </tex-math></inline-formula>, load agent <inline-formula> <tex-math notation="LaTeX">$l_{a}$ </tex-math></inline-formula>, and action agent <inline-formula> <tex-math notation="LaTeX">$a_{a}$ </tex-math></inline-formula>, are developed to control residential loads, such as normal load (<italic>nl</italic>) and heavy load (<italic>hl</italic>). To handle price uncertainty, dynamically, optimal stopping rule (OSR) theory has been used. Two variants of OSR are proposed: 1) priority inversion logic-based OSR to subsidize the responsive consumers and 2) maximum energy consumption limit <inline-formula> <tex-math notation="LaTeX">$Q$ </tex-math></inline-formula>-based OSR-Q to maximize the profit of energy retailers. Finally, the proposed mechanism is validated on a set of loads to show the applicability and proficiency under a dynamic environment. |
| format | Article |
| id | doaj-art-80afffd24a524de9822f82b72e502ecf |
| institution | Kabale University |
| issn | 2169-3536 |
| language | English |
| publishDate | 2019-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj-art-80afffd24a524de9822f82b72e502ecf2025-01-30T00:00:36ZengIEEEIEEE Access2169-35362019-01-017239902400610.1109/ACCESS.2019.29000498643826Intelligent Multi-Agent Based Multilayered Control System for Opportunistic Load Scheduling in Smart BuildingsMuhammad Babar Rasheed0https://orcid.org/0000-0002-9911-0693Nadeem Javaid1https://orcid.org/0000-0003-3777-8249Muhammad Sheraz Arshad Malik2Muhammad Asif3https://orcid.org/0000-0003-1839-2527Muhammad Kashif Hanif4Muhammad Hasanain Chaudary5Department of Electronics and Electrical Systems, The University of Lahore, Lahore, PakistanDepartment of Computer Science, COMSATS University Islamabad, Islamabad, PakistanDepartment of Information Technology, Government College University Faisalabad, Faisalabad, PakistanDepartment of Computer Science, National Textile University, Faisalabad, PakistanDepartment of Information Technology, Government College University Faisalabad, Faisalabad, PakistanDepartment of Computer Science, COMSATS University Islamabad, Lahore Campus, Lahore, PakistanToday’s power systems are subject to the high penetration of dynamic load. Volatility and intermittency of the dynamic load demand need to be compensated through optimization and scheduling without compromising user comfort. This paper proposes a multi-agent-based multi-layered hierarchical control system for residential load management under real-time pricing environment. The major objectives are to reduce peak load demand, electricity cost, and user discomfort. In doing so, different types of agents, i.e., price agent <inline-formula> <tex-math notation="LaTeX">$p_{a}$ </tex-math></inline-formula>, sensor agent <inline-formula> <tex-math notation="LaTeX">$s_{a}$ </tex-math></inline-formula>, decision agent <inline-formula> <tex-math notation="LaTeX">$d_{a}$ </tex-math></inline-formula>, load agent <inline-formula> <tex-math notation="LaTeX">$l_{a}$ </tex-math></inline-formula>, and action agent <inline-formula> <tex-math notation="LaTeX">$a_{a}$ </tex-math></inline-formula>, are developed to control residential loads, such as normal load (<italic>nl</italic>) and heavy load (<italic>hl</italic>). To handle price uncertainty, dynamically, optimal stopping rule (OSR) theory has been used. Two variants of OSR are proposed: 1) priority inversion logic-based OSR to subsidize the responsive consumers and 2) maximum energy consumption limit <inline-formula> <tex-math notation="LaTeX">$Q$ </tex-math></inline-formula>-based OSR-Q to maximize the profit of energy retailers. Finally, the proposed mechanism is validated on a set of loads to show the applicability and proficiency under a dynamic environment.https://ieeexplore.ieee.org/document/8643826/Optimizationreal time pricinguser comfortmulti-agent systemsdemand side managementdemand response |
| spellingShingle | Muhammad Babar Rasheed Nadeem Javaid Muhammad Sheraz Arshad Malik Muhammad Asif Muhammad Kashif Hanif Muhammad Hasanain Chaudary Intelligent Multi-Agent Based Multilayered Control System for Opportunistic Load Scheduling in Smart Buildings IEEE Access Optimization real time pricing user comfort multi-agent systems demand side management demand response |
| title | Intelligent Multi-Agent Based Multilayered Control System for Opportunistic Load Scheduling in Smart Buildings |
| title_full | Intelligent Multi-Agent Based Multilayered Control System for Opportunistic Load Scheduling in Smart Buildings |
| title_fullStr | Intelligent Multi-Agent Based Multilayered Control System for Opportunistic Load Scheduling in Smart Buildings |
| title_full_unstemmed | Intelligent Multi-Agent Based Multilayered Control System for Opportunistic Load Scheduling in Smart Buildings |
| title_short | Intelligent Multi-Agent Based Multilayered Control System for Opportunistic Load Scheduling in Smart Buildings |
| title_sort | intelligent multi agent based multilayered control system for opportunistic load scheduling in smart buildings |
| topic | Optimization real time pricing user comfort multi-agent systems demand side management demand response |
| url | https://ieeexplore.ieee.org/document/8643826/ |
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