Abstract
This paper proposes active and reactive power management based on distributed optimization method that is employed to minimize loss, voltage variation of buses, load shedding and variation of power generation. In this approach, energy efficiency is improved and voltage profile is kept in an acceptable range under different operating conditions of renewable energy resources and loads. Three various power control methods such as (1) active power control (APC), (2) reactive power control (RPC) and (3) simultaneous APC with RPC are implemented by proposed active and reactive power management unit (ARMU). Measurement units collect essential information and send them to ARMU in each bus. ARMU determines the active and reactive power set points of dispatchable DGs and loads and reactive set points of non-dispatchable DGs in each bus. Also ARMU updates set point in less than one second and all controllable units contribute to voltage and power control which is proper for online optimization. Simulation results show the superior performance of this control method to regulate dynamic active and reactive power set points in distribution network.
Highlights
The distribution networks were not active networks where the flow of both real and reactive power is always from main grid to distribution network
The proposed ARMU has been evaluated under different situations such as state A, B and C in distribution network
Optimal power management technique is an essential task in the future distribution networks according to the penetration level increment of intermittent DGs
Summary
The distribution networks were not active networks where the flow of both real and reactive power is always from main grid to distribution network. GMCM and LMCM units are internal controllers to regulate the generation of DG and consumption of load based on a set point These units measure voltage, transmitted active and reactive power and necessary parameters of all buses. GMCMs and LMCMs can use this framework to control optimal set points of active and reactive power of DGs and loads. To obtain the proposed framework, models of individual active and reactive power management units based on distribution subgradient optimization are derived. 3 and 4, an overview of active power control management and reactive power control management individually using distribution method is presented
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