Abstract

This paper summarises Virtual Power Plant (VPP) development within the European Seventh Framework Programme (FP7) project Intelligent URBAn eNergy tool (iURBAN).In the context of this work the VPP is considered as a high level design tool based upon load aggregation of near real-time metered energy demand and generation data at building/apartment levels. Selected data can be aggregated up to city level, or user defined and selected levels such as district, neighbourhood, low voltage electricity network, district heating network etc. Two types of analysis can be performed by the VPP: ‘as is’ model(s), representing the structures and consumption patterns currently in place (the status quo), and ‘what if’ (variant) model(s), representing possible alternatives such as adding photovoltaics (PV) at building and/or distribution levels. Target users, city planners and utility companies, will be able to use the VPP to gain an understanding of energy demand/generation at user defined and selected levels of interest ranging from high level city planning to the selection of individual buildings or user defined energy networks and so on. ‘What if’ scenarios aid in future development and planning of cities. The paper outlines an example VPP case study from the iURBAN project (grant agreement N° 608712).

Highlights

  • There a number of Virtual Power Plant (VPP) (Mostafa, 2017), (Othman, 2015) definitions

  • Navigant Research (Asmus, 2014) defines a VPP as a system that relies upon software and a smart grid to remotely and automatically dispatch and optimize Distributed Energy Resources (DER)s via an aggregation and optimization platform linking retail to wholesale markets

  • The VPP tool developed in Intelligent URBAn eNergy tool (iURBAN) is considered a prototype since there is a small set of available data from iURBAN demo cities, refer to case study description

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Summary

Introduction

There a number of Virtual Power Plant (VPP) (Mostafa, 2017), (Othman, 2015) definitions. That the modelling approach of the VPP is to be based upon load aggregation of near real-time metered energy demand and generation data and modelling of electricity and heat generation at building/apartment and district level. Demand and generation metered data from buildings within the iURBAN demonstrations cities is parsed to the SCDB-LDSS.

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