کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
5001435 | 1460869 | 2017 | 9 صفحه PDF | دانلود رایگان |
- A literature review on distributed algorithms applied to power system operation problems.
- A comprehensive comparison on convergence performance and communication strategies of various distributed algorithms.
- An investigation of high performance computing on power system operation problems.
- Future research directions for deploying such methods in practical power system operations.
Independent system operators (ISO) and regional transmission organizations (RTO) adopt centralized optimization approaches for the optimal operation of power systems, which collect all required information and perform centralized operation decisions at the central controller. As the size of power systems expends and more flexible and distributed resources from the demand side are being involved in power systems, such a centralized framework raises computation and communication concerns. Distributed optimization, as an alternative approach to solve challenges of the centralized optimization mechanism, has attracted increasing attention recently. This paper reviews existing works on distributed optimization for power systems operation. We first discuss various distributed optimization algorithms that have been studied for power systems operation, followed by a detailed literature review on adopting such distributed algorithms for major power systems operation applications including distributed economic dispatch (ED), distributed AC-optimal power flow (OPF), distributed unit commitment (UC), and other distributed applications. The advantages and barriers of applying each distributed algorithm in practice are discussed. Since the applications of distributed algorithms in practical cases largely rely on the high performance computing (HPC) platform, the application of HPC techniques on power system operation problems is also reviewed. Future research needs for effectively and efficiently promoting the practical deployment of such distributed optimization approaches in emerging power systems are identified.
Journal: Electric Power Systems Research - Volume 144, March 2017, Pages 127-135