Fast optimal power flow analysis for large-scale smart grid
Liang, Yi
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https://hdl.handle.net/2142/46937
Description
Title
Fast optimal power flow analysis for large-scale smart grid
Author(s)
Liang, Yi
Issue Date
2014-01-16T18:26:58Z
Director of Research (if dissertation) or Advisor (if thesis)
Chen, Deming
Department of Study
Electrical & Computer Eng
Discipline
Electrical & Computer Engr
Degree Granting Institution
University of Illinois at Urbana-Champaign
Degree Name
M.S.
Degree Level
Thesis
Keyword(s)
Smart Grid
Power System
Network Reduction
Optimal Power Flow
Abstract
Optimal power flow OPF plays an important role in power system operation. The emerging smart grid aims to create an automated energy delivery system that enables two-way flows of electricity and information. As a result, it will be desirable if OPF can be solved in real time in order to allow the implementation of time-sensitive applications, such as real-time pricing. We develop a novel algorithm to accelerate the computation of alternating current optimal power flow (ACOPF) through power system network reduction (NR). We formulate the OPF problem based on an equivalent reduced system and then compute its solution. The detailed optimal dispatch for the original power system is obtained afterwards using a distributed algorithm. Our results are compared with two widely used methods: full ACOPF and the linearized OPF with DC power flow and lossless network assumption, the so-called DCOPF. Experimental results show that for a large power system, our method achieves 7.01× speedup over ACOPF with only 1.72% error, and is 75.7% more accurate than the DCOPF solution. Our method is even 10% faster than DCOPF. Our experimental results demonstrate the unique strength of the proposed technique for fast, scalable, and accurate OPF computation. We also show that the proposed method is effective for smaller benchmarks.
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