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Authors: Sandford Bessler 1 ; Domagoj Drenjanac 1 ; Eduard Hasenleithner 1 ; Suhail Ahmed-Khan 1 and Nuno Silva 2

Affiliations: 1 FTW Telecommunications Research Center, Austria ; 2 EFACEC Energia M´aquinas e Equipamentos El´ectricos and S.A, Portugal

ISBN: 978-989-758-105-2

Keyword(s): Flexibility Models, Load Predictive Models, Optimization Models, Energy Scheduling, EV Charging, HVAC, PV Generation, Aggregated Energy Controller, Day-Ahead Pricing, Setpoint Following.

Related Ontology Subjects/Areas/Topics: Energy and Economy ; Energy Management Systems (EMS) ; Energy-Aware Systems and Technologies ; Integration of Smart Appliances ; Load Balancing in Smart Grids ; Optimization Techniques for Efficient Energy Consumption ; Smart Grids ; Smart Homes (Domotics)

Abstract: Flexibility information that characterizes the energy consumption of certain loads with electric or thermal storage has been recently proposed as a means for energy management in the electric grid. In this paper we propose an energy management architecture that allows the grid operator to learn and use the consumption flexibility of its users. Starting on the home asset level, we describe flexibility models for EV charging and HVAC and their aggregation at the household and low voltage grid level. Here, the aggregated energy controller determines power references (set points) for each household controller. Since voltage limits might be violated by the energy balancing actions, we include a power flow calculation in the optimization model to keep the voltages and currents within the limits. In simulation experiments with a 42 bus radial grid, we are able to support higher household loads by individual scheduling, without falling below voltage limits.

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Paper citation in several formats:
Bessler, S.; Drenjanac, D.; Hasenleithner, E.; Ahmed-Khan, S. and Silva, N. (2015). Using Flexibility Information for Energy Demand Optimization in the Low Voltage Grid.In Proceedings of the 4th International Conference on Smart Cities and Green ICT Systems - Volume 1: SMARTGREENS, ISBN 978-989-758-105-2, pages 324-332. DOI: 10.5220/0005448903240332

@conference{smartgreens15,
author={Sandford Bessler. and Domagoj Drenjanac. and Eduard Hasenleithner. and Suhail Ahmed{-}Khan. and Nuno Silva.},
title={Using Flexibility Information for Energy Demand Optimization in the Low Voltage Grid},
booktitle={Proceedings of the 4th International Conference on Smart Cities and Green ICT Systems - Volume 1: SMARTGREENS,},
year={2015},
pages={324-332},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005448903240332},
isbn={978-989-758-105-2},
}

TY - CONF

JO - Proceedings of the 4th International Conference on Smart Cities and Green ICT Systems - Volume 1: SMARTGREENS,
TI - Using Flexibility Information for Energy Demand Optimization in the Low Voltage Grid
SN - 978-989-758-105-2
AU - Bessler, S.
AU - Drenjanac, D.
AU - Hasenleithner, E.
AU - Ahmed-Khan, S.
AU - Silva, N.
PY - 2015
SP - 324
EP - 332
DO - 10.5220/0005448903240332

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