| Title |
A Study of Autonomous Intelligent Load Management System Based on Queueing Model |
| Authors |
Seung-Chul Lee ; Chang-Ho Hong ; Kyung-Dong Kim ; In-Yong Lee ; Chan-Eom Park |
| Keywords |
Load Management ; Intelligent Load Management System ; Load Management Queue ; Peak Load ; Markov Birth and Death Process ; Airconditioner Load |
| Abstract |
This paper presents an innovative load management technique that can effectively lower the summer peak load by adjusting the aircondition loads through smoothe coordinations between utility companies and large customers. An intelligent hierarchical load management system composed of a Central Intelligent Load Management System(CIMS) and multiple Local Intelligent Managerrent Systems(LIMS) is also proposed to implement the proposed technique. Upon receiving a load curtailrrent request from the utilities, CIMS issues tokens, which can be used by each LIMS as a right to tum on the airconditioner. CIMS creates and maintains a queue for fair allocation of the tokens among the LIMS demanding tokens. By adjusting the number tokens and queue management policies, desired load factors can be achieved conveniently. The Markov Birth and Death Process and the Balance Equations are employed in estimating various queue performances. The proposed technique is tested using a summer load data of a large apartment complex and proved to be quite effective in load management while minimizing the customer inconveniences. |