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Energies 2018, 11(1), 244; https://doi.org/10.3390/en11010244

A Distributed Randomized Gradient-Free Algorithm for the Non-Convex Economic Dispatch Problem

1,* , 1
and
2
1
College of Energy and Electrical Engineering, Hohai University, Nanjing 211100, China
2
College of Automation, Nanjing University of Posts and Telecommunications, Nanjing 210023, China
*
Author to whom correspondence should be addressed.
Received: 25 November 2017 / Revised: 6 January 2018 / Accepted: 17 January 2018 / Published: 19 January 2018
(This article belongs to the Section Electrical Power and Energy System)
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Abstract

In this paper, a distributed randomized gradient-free algorithm (DRGF) is employed to solve the complex non-convex economic dispatch problem whose non-convex constraints include valve-point loading effects, prohibited operating zones, and multiple fuel options. The DRGF uses the Gauss approximation, smoothing parameters, and a random sequence to construct distributed randomized gradient-free oracles. By employing a consensus procedure, generation units can gather local information through local communication links and then process the economic dispatch data in a distributed iteration format. Based on the principle of projection optimization, a projection operator is adopted in the DRGF to deal with the discontinuous solution space. The effectiveness of the proposed approach in addressing the non-convex economic dispatch problem is demonstrated by simulations implemented on three standard test systems. View Full-Text
Keywords: distributed randomized gradient-free algorithm; non-convex economic dispatch; randomized gradient-free oracles distributed randomized gradient-free algorithm; non-convex economic dispatch; randomized gradient-free oracles
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Xie, J.; Yu, Q.; Cao, C. A Distributed Randomized Gradient-Free Algorithm for the Non-Convex Economic Dispatch Problem. Energies 2018, 11, 244.

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