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Low- and medium-voltage networks are facing new challenges due to the increased use of distributed energy generation and storage facilities, the integration of electric vehicles, the coupling of thermal and electrical energy systems (hybrid energy systems, heat pumps, HVAC) and also the increased use of information and communications technology (ICT) in networks and at the consumer/prosumer level.
Within the project “REsys - Regelungsstrategien zur Effizienzsteigerung komplexer hybrider Energiesysteme” – which was funded from the Austrian “Klima- und Energiefonds” as a part of the “Energieforschungsprogramm 2015” – models, simulations and analyses are built on measured and statistical data. By the use of ICT-methods and expert's knowledge, smart control strategies are developed and subsequently tested in simulations and on a real industrial hybrid energy system. Additionally, the transferability of the results to other hybrid energy systems is evaluated.
The objectives of the project were:
Improvement of the energy the efficiency of future and existing complex hybrid energy systems.
Generation of know-how regarding the interdependencies and interactions between components in such systems.
Open up innovative methods for the analysis of big data, generated by a multitude of measuring sensors.
Development of system-oriented simulation models with open system boundaries, validated by measured and statistical data.
This contribution presents the results of a developed optimizing hybrid energy management model consisting of a co-simulation between the thermal system modelled in TRNSYS and the electrical systems modelled in Matlab.
The industrial company consists of a thermal and, due to the historical expansion of the company, of two separate electrical subsystems as well as a further 50 km distant external industrial site, which are connected via the power grid.
The hybrid energy management model provides plausible results and the co-simulation between Matlab and TRNSYS implemented with a parallel interface works. However, since the thermal system in the hybrid energy management system in Matlab is only rudimentarily implemented for the optimization algorithm, uncertainties arise in the forecast for the thermal system.
The simulations have shown that the operation of the heat pumps, the solar thermal system and the electric cartridges of thermal energy storages is strongly dependent on the given thermal demand so that only a little freedom was available for the optimization algorithm. The biggest influence was the use of electrical energy storage with a capacity of at least 1000 kWh at the electrical system A (see Figure 1). This area with a large photovoltaic system and comparatively low demand is well suited as a location for such a system. By balancing all various locations of the company with the power grid achieve an increase in the degree of autonomy and a significant reduction in local CO2 emissions.
