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			<titleStmt><title level='a'>A global algorithm for AC optimal power flow based on successive linear conic optimization</title></titleStmt>
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				<date>07/01/2017</date>
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				<bibl> 
					<idno type="par_id">10079395</idno>
					<idno type="doi">10.1109/PESGM.2017.8273957</idno>
					<title level='j'>2017 IEEE Power &amp; Energy Society General Meeting</title>
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					<author>Masoud Barati</author><author>Amin Kargarian</author>
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			<abstract><ab><![CDATA[Newly, there has been significant research interest in the exact solution of the AC optimal power flow (AC-OPF) problem. A semideflnite relaxation solves many OPF problems globally. However, the real problem exists in which the semidefinite relaxation fails to yield the global solution. The appropriation of relaxation for AC-OPF depends on the success or unfulflllment of the SDP relaxation. This paper demonstrates a quadratic AC-OPF problem with a single negative eigenvalue in objective function subject to linear and conic constraints. The proposed solution method for AC-OPF model covers the classical AC economic dispatch problem that is known to be NP-hard. In this paper, by combining successive linear conic optimization (SLCO), convex relaxation and line search technique, we present a global algorithm for AC-OPF which can locate a globally optimal solution to the underlying AC-OPF within given tolerance of global optimum solution via solving linear conic optimization problems. The proposed algorithm is examined on modified IEEE 6-bus test system. The promising numerical results are described.]]></ab></abstract>
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