Session: 16-01: Poster Presentations

Paper Number: 140757

140757 - Energy Management Optimization on the Basis of Energy Aggregators 

Abstract: 

In this work, a new MILP model for the day-ahead energy management of Energy Aggregators is developed. In order to fully exploit the inherent potential of decentralized and renewable energy systems, a holistic approach to the multi-faceted and complex decision problem of Energy Aggregators is necessary. Synergies between the different types of flexibility and energy trading options enable profit maximizing Energy Aggregators to provide economic benefits to participating households but require a detailed consideration of technological properties and constraints of the respective types of resources and their operation. Therefore, in the model developed in this work, in addition to photovoltaic systems, solar thermal systems, electric vehicles, household battery storages and time-shiftable loads, also power-to-heat systems consisting of heat pumps, heat storages and heater rods are integrated and modeled on a high level of detail.  This represents an important contribution to previous works on Energy Aggregators, as modeling the complex thermal relations of such a system is a challenging task that, however, comprises high potential for more efficient energy management. Multiple technical aspects of heat pumps that can be operated in either heating or cooling mode are taken into account. This includes a newly developed approach based on piecewise linearization to model the Coefficient of Performance (COP) and Energy Efficiency Ratio (EER) with an adaptable level of granularity dependent on operational power and supply temperature. Moreover, three different trading levels (wholesale, local markets and direct internal trading between aggregated households) are considered simultaneously. The model application to a case study with up to 111 individually modeled prosumer households in a summer and a winter scenario reveals high synergetic potential of Energy Aggregators resulting from the combined flexibility of the different system components, thus underlining the significance of holistically modeling the Energy Aggregator decision problem. A trade-off regarding the flexible usage of energy storages is identified between household battery storages and electric vehicle batteries, which can be explained by their different technical and practical restrictions. In addition to assessing the impact of the different types of energy resources, further analyses are deployed to develop operational strategies towards a foresighted use of energy storages. The results show that the concept of Energy Aggregators as energy managers of local prosumer household communities can provide the means for efficiently operating an energy system that is built on a large number of small-scale renewable energy sources and flexible distributed energy resources and hence has the potential for being an important element in future energy systems.

Presenting Author: Kai Hoth Hamburg University of Technology

Presenting Author Biography: Kai Hoth received the B. Sc. degree in 2015 and the M. Sc. degree in 2017 from Leibniz University Hannover in the field of Engineering and Business Administration. He is currently pursuing the Ph. D. degree at Hamburg University of Technology in the field of Operations Research. He has previously worked as Managing Director of Spenjoy GmbH, as Engineering Consultant for ALTEN Technology GmbH and as Research Assistant at the Institute for Operations Management at the University of Hamburg. His current research interests include the aggregator-based optimization of renewable energy systems with a focus on local energy markets.

Authors:

Kai Hoth Hamburg University of Technology
Béla Wiegel Institute of Electrical Power and Energy Technology
Tizian Schug Institute for Operations Research and Information Systems
Kathrin Fischer Institute for Operations Research and Information Systems