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Since November 2011 the standard DIN 4709 stipulates performance tests for Micro-CHP units in Germany. In contrast to steady state measurements of the CHP unit itself, the test according to DIN 4709 includes the thermal storage tank as well as the internal control unit, and it is based on a 24 h test cycle following a specified thermal load profile. Hence, heat losses from the storage tank are as well taken into account as transient losses of the CHP unit. In addition, the control strategy for loading and unloading the storage tank affects the test results.
The DIN 4709 test cycle has been applied at the test stand for Micro-CHP units at Reutlingen University, and results for the Micro-CHP unit WhisperGen and the EC Power units XRGI 15® and XRGI 20® are available. During the analysis a method has been developed to evaluate the results in case the test cycle does not end in a time slot between 24 and 24.5 h after the starting as demanded by DIN 4709. Since this method has been successfully applied to the test of various CHP units of different size and technology so far, it is suggested to incorporate it to DIN 4709 during the next revision of the standard.
The performance numbers obtained reveal the differences in efficiencies measured at steady-state on the one hand and following the DIN 4709 test cycle on the other hand. While the deviations in electrical efficiencies are small, thermal efficiencies according to DIN 4709 fall below steady state data by 3–6 percentage points. This is attributed to transient thermal losses and heat losses from the storage tank, which are not included in steady state and separate testing of the CHP unit, only.
This paper covers test and verification of a forecast-based Monte Carlo algorithm for an optimized, demand-oriented operation of combined heat and power (CHP) units using the hardware-in-the-loop approach. For this purpose, the optimization algorithm was implemented at a test bench at Reutlingen University for controlling a CHP unit in combination with a thermal energy storage, both in real hardware. In detail, the hardware-in-the-loop tests are intended to reveal the effects of demand forecasting accuracy, the impact of thermal energy storage capacity and the influence of load profiles on demand-oriented operation of CHP units. In addition, the paper focuses on the evaluation of the content of energy in the thermal energy storage under practical conditions. It is shown that a 5-layer model allows to determine the energy stored quite accurately, which is verified by experimental results. The hardware-in-the-loop tests disclose that demand forecasting accuracies, especially electricity demand forecasting, as well as load profiles strongly impact the potential for CHP electricity utilization on-site in demand-oriented mode. Moreover, it is shown that a larger effective capacity of the thermal energy storage positively affects demand-oriented operation. In the hardware-in-the-loop tests, the fraction of electricity generated by the CHP unit utilized on-site could thus be increased by a maximum of 27% compared to heat-led operation, which is still the most common modus operandi of small-scale CHP plants. Hence, the hardware-in-the-loop tests were adequate to prove the significant impact of the proposed algorithm for optimization of demand-oriented operation of CHP units.
The paper illustrates the status quo of a research project for the development of a control system enabling CHP units for a demand-oriented electricity production by an intelligent management of the heat storage tank. Thereby the focus of the project is twofold. One is the compensation of the fluctuating power production by the renewable energies solar and wind. Secondly, a reduction of the load on the power grid is intended by a better match of local electricity demand and production. In detail, the general control strategy is outlined, the method utilized for forecasting heat and electricity demand is illustrated as well as a correlation method for the temperature distribution in the heat storage tank based on a Sigmoid function is proposed. Moreover, the simulation model for verification and optimization of the control system and the two field test sites for implementing and testing the system are introduced.
Coupling electricity and heat sector is one of the most necessary actions for the successful energy transition. Efficient electrification for space heating and domestic hot water generation is needed for buildings, which are not connected to any district heating network, as distributed heating demand momentarily is largely met by fossil fuels. Hence, hybrid energy systems will play a pivotal role for the energy transition in buildings. Heat pumps running on PV-electricity is one of the most widely discussed combination for this purpose. In this paper, a heuristic optimization method for the optimal operation of a heat pump driven by the objective for maximum onsite PV electricity utilization is presented. In this context, the thermal flexibility of the building and a thermal energy storage (TES) for generation of domestic hot water (DHW) are activated in order to shift the operation of the heat pump to times of PV-generation. Yearly simulations for a system consisting of heat pump, PV modules, building with floor heating installation and TES for DHW generation are carried out. Variation parameters for the simulation include room temperature amplitude (0.5, 1, 1.5 and 2 K) based on mean room temperature (21 °C), PV-capacity (4, 6, 8 and 10 kW) and type of heat pump (ground source and air source type). The yearly energy balances show that buildings offer significant thermal storage capacity avoiding an additional, large TES for space heating fulfillment and improving the share of onsite PV electricity utilization. With introduction of a battery, which has been analyzed as well for different sizes (1.9, 4.8, 7.7 and 10.6 kWh), the share of onsite PVelectricity utilization can even be improved. However, thermal flexibility supplemented by the varying room temperature amplitude for a bigger battery does not improve the share of onsite PV-electricity utilization. Nevertheless, even with a battery not more than 50% of the electrical load including operation of the heat pump can be covered by PV-electricity for the specific system under investigation. This is noteworthy on the one hand, since it indicates that a hybrid heating system consisting of heat pump and PV cannot solely cover the heat demand of residential buildings. One the other hand, this emphasizes the necessity to include further renewable sources like wind power, in order to draw the complete picture. This, however, is beyond the scope of this paper, which mainly focuses on introduction and verification of the novel control method with regard to a practical building.
Nowadays CHP units are discussed for the production of electricity on demand rather than for generation of heat providing electricity as a by-product. By this means, CHP units are capable of satisfying a higher share of the electricity demand on-site and in this new role, CHP units are able to reduce the load on the power grid and to compensate for high fluctuations of solar and wind power.
Evidently, a novel control strategy for CHP units is required in order to shift the operation oriented at the heat demand to an operation led by the electricity demand. Nevertheless, the heat generated by the CHP unit needs to be utilized completely in any case, for maintaining energy as well as economic efficiency. Such a strategy has been developed at Reutlingen University, and it will be presented in the paper. Part of the strategy is an intelligent management for the thermal energy storage (TES) ensuring that the storage is at low level in terms of its heat content just before an electricity demand is calling the CHP unit into operation. Moreover, a proper forecast of both, heat and electricity demand, is incorporated and the requirements of the CHP unit in terms of maintenance and lifetime are considered by limiting the number of starts and stops per unit time and by maintaining a certain minimum length of the operation intervals.
All aspects of this novel control strategy are revealed in the paper, which has been implemented on a controller for further testing at two sites in the field. Results from these tests are given as well as results from a simulation model, which is able to evaluate the performance of the control strategy for an entire year.
In the course of a more intensive energy generation from regenerative sources, an increased number of energy storages is required. In addition to the widespread means of storing electric energy, storing energy thermally can contribute significantly. However, limited research exists on the behaviour of thermal energy storages (TES) in practical operation. While the physical processes are well known, it is nevertheless often not possible to adequately evaluate its performance with respect to the quality of thermal stratification inside the tank, which is crucial for the thermodynamic effectiveness of the TES. The behaviour of a TES is experimentally investigated in cyclic charging and discharging operation in interaction with a cogeneration (CHP) unit at a test rig in the lab. From the measurements the quality of thermal stratification is evaluated under varying conditions using different metrics such as normalised stratification factor, modified MIX number, exergy number and exergy efficiency, which extends the state of art for CHP applications. The results show that the positioning of the temperature sensors for turning the CHP unit on and off has a significant influence on both the effective capacity of a TES and the quality of thermal stratification inside the tank. It is also revealed that the positioning of at least one of these sensors outside the storage tank, i.e. in the return line to the CHP unit, prevents deterioration of thermal stratification, thereby enhancing thermodynamic effectiveness. Furthermore, the effects of thermal load and thermal load profile on effective capacity and thermal stratification are discussed, even though these are much smaller compared to the effect of positioning the temperature sensors.