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Data Fusion Based Decentralized State Estimation in Nested Microgrid

IP.com Disclosure Number: IPCOM000247149D
Publication Date: 2016-Aug-10
Document File: 4 page(s) / 362K

Publishing Venue

The IP.com Prior Art Database

Related People

Ravindra Singh: AUTHOR [+2]

Abstract

The distribution grids of today were designed as passive networks in which the power flows from transmission grid to end customers. However due to large penetration of renewables and active loads such as electrical vehicles, the distribution grid is becoming more dynamic. The dynamic nature of distribution grid poses several challenges in terms of power flow and control. In addition to this, extreme weather conditions in recent past have exposed the vulnerability of the traditional distribution grid. Operating distribution circuits as a cluster of several distributed microgrids provides a unified elegant solution to the above problems.

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Data Fusion Based Decentralized State Estimation in Nested Microgrid

The distribution grids of today were designed as passive networks in which the power flows from transmission grid to end customers. However due to large penetration of renewables and active loads such as electrical vehicles, the distribution grid is becoming more dynamic. The dynamic nature of distribution grid poses several challenges in terms of power flow and control. In addition to this, extreme weather conditions in recent past have exposed the vulnerability of the traditional distribution grid. Operating distribution circuits as a cluster of several distributed microgrids provides a unified elegant solution to the above problems. The main idea is to partition the distribution network into several zones or clusters. Each zone has one microgrid controller (MGC) where the state estimation will be running. Alternatively, in a distributed decentralized microgrid control system one of the microgrid controllers can be allocated to perform the state estimation task. This controller can be installed, for instance at the point of common coupling. In addition to this, each zone can have one or two primary substations, several secondary substations, few DERs and all connected customers. A schematic of nested microgrid with decentralized MGC controllers is shown in Figure 1. The communication within a microgrid zone is local and called "intra-communication". The communication between different MGCs is "inter-communication"

Figure 1. Schematic of the nested microgrid

The measurement information within a cluster or zone (circle) will be treated as real measurement whereas the measurement information for the rest of the network outside the zone (circle) will be treated as pseudo measurements with high variance. For the purpose of state estimation, a MGC uses all the measurements in its 'intra-communication" range as real measurements and load values (obtained from load profiles) in other parts of


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the network as pseudo measurements. Thus each MGC has a good estimate of its own subsystem and poor estimate of the rest of the network. In order to have a good estimate of the entire network at each MGC location, the MGCs communicate their local measurements or state estimates amongst themselves to arrive at a global estimate, collaboratively. The communicated information will be processed locally at each MGC without any central processing site. The following two fusion methods can be applied based on whether the MGCs communicate their local measurements or the output of their local estimates.

Fusion Methods:


1) Measurement Fusion

 The measurements are communicated among the MGCs, so that the local measurements from both areas are available at each MGC.

 These measurements are concatenated into a single measurement vector and an estimate of the state is obtained using weighted least squares (WLS)

 MF is based on WLS estimation, it is the optimal method and...