Optimal Operation and Management of Smart Grid System with LPC and BESS in Fault Conditions

Ryuto Shigenobu, Ahmad Samim Noorzad, Cirio Muarapaz, Atsushi Yona and Tomonobu Senjyu
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Ryuto Shigenobu: Faculty of Engineering, University of the Ryukyus, 1 Senbaru Nishihara-cho Nakagami, Okinawa 903-0213, Japan
Ahmad Samim Noorzad: Faculty of Engineering, University of the Ryukyus, 1 Senbaru Nishihara-cho Nakagami, Okinawa 903-0213, Japan
Cirio Muarapaz: Faculty of Engineering, University of the Ryukyus, 1 Senbaru Nishihara-cho Nakagami, Okinawa 903-0213, Japan
Atsushi Yona: Faculty of Engineering, University of the Ryukyus, 1 Senbaru Nishihara-cho Nakagami, Okinawa 903-0213, Japan
Tomonobu Senjyu: Faculty of Engineering, University of the Ryukyus, 1 Senbaru Nishihara-cho Nakagami, Okinawa 903-0213, Japan

Sustainability, 2016, vol. 8, issue 12, 1-19

Abstract: Distributed generators (DG) using renewable energy sources (RESs) have been attracting special attention within distribution systems. However, a large amount of DG penetration causes voltage deviation and reverse power flow in the smart grid. Therefore, the smart grid needs a solution for voltage control, power flow control and power outage prevention. This paper proposes a decision technique of optimal reference scheduling for a battery energy storage system (BESS), inverters interfacing with a DG and voltage control devices for optimal operation. Moreover, the reconfiguration of the distribution system is made possible by the installation of a loop power flow controller (LPC). Two separate simulations are provided to maintain the reliability in the stable power supply and economical aspects. First, the effectiveness of the smart grid with installed BESS or LPC devices is demonstrated in fault situations. Second, the active smart grid using LCPs is proposed. Real-time techniques of the dual scheduling algorithm are applied to the system. The aforementioned control objective is formulated and solved using the particle swarm optimization (PSO) algorithm with an adaptive inertia weight (AIW) function. The effectiveness of the optimal operation in ordinal and fault situations is verified by numerical simulations.

Keywords: voltage control; distributed generator; battery energy storage system; reverse power flow; loop power flow controller; fault analysis; renewable energy source; active smart grid; adaptive inertia weight particle swarm optimization (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2016
References: View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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