DocumentCode
3605239
Title
Fully Distributed Social Welfare Optimization With Line Flow Constraint Consideration
Author
Ye Ma ; Wei Zhang ; Wenxin Liu ; Qinmin Yang
Author_Institution
Klipsch Sch. of Electr. & Comput. Eng., New Mexico State Univ., Las Cruces, NM, USA
Volume
11
Issue
6
fYear
2015
Firstpage
1532
Lastpage
1541
Abstract
This paper proposes a fully distributed social welfare optimization solution that solves the economic dispatch and demand response problems in an integrated way. Compared with sequentially implementing these two operations one after another, the integrated solution can efficiently maximize the benefits of customers and minimize the generation cost of generators simultaneously. By adjusting both generations and dispatchable loads, line flow constraints and generation bounds can be satisfied easier. The proposed solution has two layers of operations for consensus-based information discovery and gradient-based generation or demand adjustment, respectively. It is fully distributed in the sense that there is no need for a specialized/central controller to coordinate the operations of the autonomous local controllers (agents). Compared with centralized solutions, the multiagent system-based distributed solution is more reliable against single-point failures and can better accommodate customer participation. The proposed solution has been tested with a 5-bus system and the IEEE 30-bus system under light- and heavy-load conditions. Both static optimization and dynamic simulation results are provided to demonstrate the performance of the proposed solution.
Keywords
power generation dispatch; 5-bus system; IEEE 30-bus system; central controller; consensus-based information discovery; demand adjustment; demand response problems; dispatchable loads; distributed social welfare optimization; dynamic simulation; economic dispatch; generation cost; generators; gradient-based generation; line flow constraint consideration; line flow constraints; static optimization; Algorithm design and analysis; Communication networks; Convergence; Economics; Generators; Informatics; Optimization; Consensus; distributed gradient algorithm; line flow constraints; social welfare optimization; social welfare optimization (SWO);
fLanguage
English
Journal_Title
Industrial Informatics, IEEE Transactions on
Publisher
ieee
ISSN
1551-3203
Type
jour
DOI
10.1109/TII.2015.2475703
Filename
7234895
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