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Projects / Programmes source: ARIS

Energy management system for electric devices

Research activity

Code Science Field Subfield
2.12.00  Engineering sciences and technologies  Electric devices   

Code Science Field
T190  Technological sciences  Electrical engineering 

Code Science Field
2.02  Engineering and Technology  Electrical engineering, Electronic engineering, Information engineering 
Keywords
Electric devices; energy generation, storage, usage, energy management; efficiency, self learning models; market model; energy flexibility market
Evaluation (rules)
source: COBISS
Researchers (15)
no. Code Name and surname Research area Role Period No. of publicationsNo. of publications
1.  28428  PhD Miloš Beković  Electric devices  Researcher  2020 - 2022  138 
2.  37956  PhD Marko Bizjak  Computer science and informatics  Researcher  2019 - 2022  39 
3.  34581  Katarina Dežan  Energy engineering  Researcher  2019 - 2022  57 
4.  08919  PhD Drago Dolinar  Electric devices  Retired researcher  2019 - 2022  630 
5.  33709  PhD Niko Lukač  Computer science and informatics  Researcher  2019 - 2022  198 
6.  33248  PhD Martin Petrun  Electric devices  Researcher  2019 - 2022  125 
7.  09169  PhD Jože Pihler  Electric devices  Retired researcher  2019 - 2022  941 
8.  39651  Matej Pintarič  Energy engineering  Researcher  2019 - 2022  39 
9.  15671  PhD David Podgorelec  Computer science and informatics  Researcher  2019 - 2022  210 
10.  18698  PhD Boštjan Polajžer  Electric devices  Researcher  2019 - 2022  271 
11.  39978  Patricija Rijavec Simonič  Economics  Researcher  2021 - 2022  25 
12.  37449  PhD Nevena Srećković  Electric devices  Researcher  2019 - 2021  48 
13.  36449  PhD Primož Sukič  Electric devices  Researcher  2019 - 2022  72 
14.  10814  PhD Gorazd Štumberger  Electric devices  Head  2019 - 2022  973 
15.  56045  Marko Vodenik  Energy engineering  Researcher  2021 - 2022 
Organisations (1)
no. Code Research organisation City Registration number No. of publicationsNo. of publications
1.  0796  University of Maribor, Faculty of Electrical Engineering and Computer Science  Maribor  5089638003  27,274 
Abstract
The Winter package 2016 of the European Commission Energy efficiency directive represents a political frame for the introduction of the energy flexibility market. It complements the existing energy market with new market driven energy flexibility services. The aggregator coordinates and connects the flexibility service providers, in the form of energy generation, storage or consumption units, with the flexibility users in the form of electricity network operators and balancing group responsible parties. The project proposes a completely new concept of energy management system (EMS), that is installed at the side of flexibility service providers, and is crucial for the introduction of Market Driven Energy Flexibility Services (MDEFS).     The existing EMSs can be characterized as: Classical automation systems; Remote control systems.   They are incapable: Of providing off-grid (island) operation even when they contain power generation units like photovoltaic systems and energy storage systems, Of negotiating with the aggregator and articulating interests of their owner; Of asking for services or giving offers for services they can provide; Of operating when the main electricity network supply is disconnected or communication services are disabled.   The communication between the EMS owner and the aggregator is limited to: sending requests to the customers to switch their devices on or off; directly switching the customers’ devices on and off.   None of these two approaches is acceptable for customers!   The main objective of this project is to develop a new EMS concept and to confirm it. The developed EMS should eliminate most of the aforementioned drawbacks. In order to reach the given objective, the following tasks will be performed:   In order to provide the EMS with information, substantial for decision making, a machine learning based automated generation of models for individual units (energy generation, storage, consumption) will be developed. When developed, the models will be generated and updated automatically, based on the measurements performed during the normal operation of individual devices. The models will be implemented centrally on the EMS or locally on a switch or sensor device. When required, they will provide the EMS with the estimated status of observed units, before the particular actions will be performed. In this way, the models will be one of the most important support tools in the EMS’s decision logic.  A new EMS Autonomous Decision Logic (ADL), based on mimicking market behaviour, will be introduced. Its decisions will be based on estimations obtained from the models of individual units (energy generation, storage, consumption). Based on the estimated conditions provided by models, the EMS ADL will be able to accept offers from the aggregator and offer services to them. Thus, the existing request for the customers’ actions, regarding switching individual devices on and off, will be replaced by the exchange of requests and offers for services between the EMS and the aggregator. This will enable the introduction of MDEFS.   The developed EMS ADL will be further upgraded with off-gird operation functionalities, enabling utilization of all available resources and limited operation even when the electricity supply from the main grid is not available. This will be achieved by permanent monitoring, prediction and control of stored energy and energy flow among all energy generation, storage and consumption units connected to the EMS. In order to confirm the proposed concept, an experimental system for EMS testing will be set-up. It will include controllable electricity generation units (a PV system), a storage unit (LTO Battery with a converter) and energy consumption units (boiler, refrigerator, air conditioners). It will be applied to test the automatic generation of models and their adaption capabilities, the performances of the EMS ADL in on- grid and off-grid operation and its ability to be used in p
Significance for science
The project introduces a completely new concept of energy management systems (EMS). Its main advantage is the ability to negotiate with the aggregators on the energy flexibility market. The upcoming energy flexibility market complements the existing energy (electricity) market with the new, today not existing market driven flexibility services. On the energy flexibility market, the aggregator connects and coordinates the EMS equipped energy flexibility service providers (supply in the form of controllable energy generation, storage, and consumption units) on the one hand, and the energy service users (demand on the side of transmission system operators, distribution system operators, and balancing groups) on the other hand. The proposed EMS concept seems to be crucial for the successful introduction of market driven energy flexibility services. The existing EMS use measured data and regression based data analysis. However, they do not use models of individual devices in EMS decision logic. The proposed approach enables evaluation of different options before final decision is made. The algorithms for automated generation of devices’ models and their permanent adaptation based on permanent measurements are a novelty in the field of EMS. The use of algorithms that mimic market behaviour is a novelty in the field of EMS as well. The EMS ability to negotiate with the aggregators, in order to maximize benefits for its owner, is a completely new functionality of EMS. The utilization of all available and controllable energy sources, energy storage units and consumption units, in order to provide at least limited off-grid operation, achieved by a permanent energy and energy flow monitoring and control is a novelty as well. By implementing all these solutions inside building EMS and connecting it to a smart grid enables a variety of new services, not only inside smart grids but also inside smart cities, including all varieties of market driven energy flexibility services. Thus, based on the aforementioned statements, the expected relevance of the proposed project to the development of science and science fields related to energy flexibility services, smart homes, smart buildings, smart grid, smart cities and energy management is at least to say large, if not even huge. Consequently, the proposers expect significant interest for the project results from the scientific and industrial societies. Therefore, non-negligible resources will be allocated to the dissemination and replication of project results. Finally, the impact on the EMS end-users should not be neglected. During normal operation connected to the electricity network, the EMS should provide direct benefits for the owner, primarily in the form of reduced costs for energy supply. Secondarily, the proposed EMS should enable the owner its participation in marked driven energy flexibility services and additional incomes.
Significance for the country
The project introduces a completely new concept of energy management systems (EMS). Its main advantage is the ability to negotiate with the aggregators on the energy flexibility market. The upcoming energy flexibility market complements the existing energy (electricity) market with the new, today not existing market driven flexibility services. On the energy flexibility market, the aggregator connects and coordinates the EMS equipped energy flexibility service providers (supply in the form of controllable energy generation, storage, and consumption units) on the one hand, and the energy service users (demand on the side of transmission system operators, distribution system operators, and balancing groups) on the other hand. The proposed EMS concept seems to be crucial for the successful introduction of market driven energy flexibility services. The existing EMS use measured data and regression based data analysis. However, they do not use models of individual devices in EMS decision logic. The proposed approach enables evaluation of different options before final decision is made. The algorithms for automated generation of devices’ models and their permanent adaptation based on permanent measurements are a novelty in the field of EMS. The use of algorithms that mimic market behaviour is a novelty in the field of EMS as well. The EMS ability to negotiate with the aggregators, in order to maximize benefits for its owner, is a completely new functionality of EMS. The utilization of all available and controllable energy sources, energy storage units and consumption units, in order to provide at least limited off-grid operation, achieved by a permanent energy and energy flow monitoring and control is a novelty as well. By implementing all these solutions inside building EMS and connecting it to a smart grid enables a variety of new services, not only inside smart grids but also inside smart cities, including all varieties of market driven energy flexibility services. Thus, based on the aforementioned statements, the expected relevance of the proposed project to the development of science and science fields related to energy flexibility services, smart homes, smart buildings, smart grid, smart cities and energy management is at least to say large, if not even huge. Consequently, the proposers expect significant interest for the project results from the scientific and industrial societies. Therefore, non-negligible resources will be allocated to the dissemination and replication of project results. Finally, the impact on the EMS end-users should not be neglected. During normal operation connected to the electricity network, the EMS should provide direct benefits for the owner, primarily in the form of reduced costs for energy supply. Secondarily, the proposed EMS should enable the owner its participation in marked driven energy flexibility services and additional incomes.
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