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Load shifting of resistive domestic hot water heaters has been done in Europe since the 1930s, primarily to ease the power supply during peak times. However, the pursued and already commenced energy transition in Europe changes the requirements for the underlying logic. In this more general context, demand side management is considered a viable approach to utilize the flexibility of thermal and electrochemical storage systems for buffering energy generated from renewables. In this work, an autonomous approach for demand side management of energy storage systems is developed, which is based on unidirectional communication of an incentive. This concept is then applied to the specific problem of resistive domestic hot water heaters.
The basic algorithms for an optimized operation are developed and evaluated based on simulation studies. The optimization problem considered, maps the search for the optimal heating schedule, while ensuring the temperature limits defined: Firstly, a maximum, which is defined by the hysteresis set point temperature; Secondly, during hot water draw offs, the outlet temperature should not fall below a set minimum. To establish this, the time series of hot water usage has to be predicted.
Depending on the complexity of the hot water heater model used, the formulation of the problem ranges from a linear to non-linear optimization with discontinuous constraints. The simulation studies presented, comprise a formulation as binary linear optimization problem, as well as a solution based on a heuristic direct method to solve the non-linear version. In contrast to the first linear approach, the latter takes stratification inside the tank into account. One-year simulations based on realistic hot water draw profiles are used to investigate the potentials with respect to load shift and energy efficiency improvements. Additional to assuming perfect prediction of user behavior, this work also considers the k-nearest neighbors algorithm to predict the time series. If compared to usual night-tariff switched operation, assuming perfect prediction shows 30 % savings on the electricity market when stratification is taken into account. The user prediction proposed leads to 16 % cost savings, while 6 % of the electric energy is conserved.
Based on the linear approach, a prototype is developed and used in a field test. A micro computer processes the sensor information for local data acquisition, receives electricity spot market prices up to 34 hours in advance, solves the optimization problem for this time horizon, and switches the power supply of the resistive heating element accordingly. Beside the temperature of the environment, the inlet and outlet temperatures, the temperature inside the tank is measured at five points, as well as the water volume flow rate and the electric power recorded. Two test runs of 18 days each, compare the night-tariff switched operation to the price-based optimization in a real-world environment. Results show a significant increase of 6 % in thermal efficiency during the operation based on the algorithm developed, which can be contributed to the optimization accounting for the usage expected.
To facilitate the technical and economic feasibility for retrofit-able implementations of the method proposed for autonomous demand side management, the sensors used must be kept to a minimum. A sufficiently accurate state estimation of the storage has to be achieved, to facilitate a useful model predictive control. Therefore, the last part of this work focuses on the aspect of automated system identification and state estimation of resistive domestic hot water heaters. To that end, real hot water usage profiles and schedules gathered in a field test are used in a lab setup, to collect data on the temperature distribution inside the tank during realistic operating conditions. Four different thermal models, common in literature, are considered for state estimation and system identification. Based on the data collected in the lab, they are evaluated with respect to robustness, computational costs, and estimation accuracy. Based on the observations made in the experiments, an extension of the one-node model by a single additional parameter is proposed. By this adaption, a linear temperature distribution in the lower part of the tank can be modeled during heating. The resulting model exhibits improved robustness and lower computational costs, when compared to the original model. At the same time, the average temperature in the storage tank is estimated nearly as accurate (6 % mean average percentage error) as in the case of the about 50 times more computationally expensive multi-layer model (4 % mean average percentage error).
The master thesis concentrates on two different cases to generate energy from MSW. In the first case, the MSW is incinerated in an incineration plant. This approach represents the present situation in the waste treatment in large parts of the UK.
In the second case, the OFMSW is separated in a treatment facility and used in a fermentation plant. The remaining waste is again used as a feedstock in an incineration plant. The difference in the net energy yield between these two cases is investigated in this thesis.
To calculate the difference in the energy yield of case 1 and case 2, a research of the existing literature about comparisons of incineration and fermentation plants and their results are reflected and data about the MSW in the UK is collected. With the input of the literature and the researched data, a model is built which compares the two different cases of waste treatment. The results of the comparisons are then examined by varying different parameters. This step is repeated by using different input parameters. Afterwards, the results are compared and analysed.
In the next part of the thesis, an economic analysis of the incineration and fermentation combined technology plant is made. In this analysis, the investment costs, the annual profits and the annual costs of an additional fermentation plant are discussed and calculated. The result of the analysis is displayed as an amortization time calculation. The results are then analysed by varying the parameters in a sensitivity analysis.
Finally, the research question is answered and a forecast for possible plant designs with an incineration and a fermentation plant in combination are discussed.
In the residential construction industry, the focus on energy efficiency and cost effectiveness has been gaining importance. In order to achieve these contradicting objectives, a shift towards a reduced complexity in building practices can be observed.
Within the HVAC sector, the Tempering method for space heating has received particular attention as an alternative way to heat museums and buildings worthy of preservation.
In spite of the simplified design, this space heating system is claimed to offer significant advantages in its present field of application.
This study evaluates the implementation of Tempering in the residential context. So far, there is no scientific research on the implementation of Tempering in energy efficient-dwellings.
This master thesis provides initial results on achievable heat flux values, the impact on heat generation efficiency, the inherent installation costs as well as the particular
consequences in terms of end energy consumption of the building as a whole. The findings are compared to the individual performances of well-established heat emission approaches.
By means of a numerical analysis and a case study on a real-case single-family home, it is found that the heat flux values of Tempering systems suffice for the implementation within buildings, which comply with the low-energy building standard. Comparing radiant walls, radiant floors and radiators, the inherent installation costs are lowest for Tempering and radiant floors. The impact on the end energy consumption depends largely on the utilised heat generation system. With a gas-condensing boiler, Tempering performs equal to the radiant systems. When a ground source heat pump system is installed, however, Tempering performs poorly and accounts for a significantly increased energy consumption. Radiator systems are found to be the most energy-efficient method for space heating in both cases.
In times of global climate change, it is increasingly important to investigate emissions and resource consumption of all machines and, if possible, to improve them. This includes within the transport sector car ferries.
In order to reduce the environmental impacts of car ferries, the electrification has penetrated into this sector, which has led to the world's first fully electric car ferry. One of the most important components to operate this ferry is the energy storage. Not only the battery storage of the ferry itself is needed, but also an onshore battery storage system is needed to support the electrical grid.
The present study examines how storage technologies and concepts can impact the environment considering the world's first all-electric car ferry, MF Ampere, which operates in Norway.
To examine this, the current onshore battery storage system is compared to a concrete sphere storage system. For this purpose, data from the first test run of this new storage technology, which was successfully carried out by the Fraunhofer Institute in 2016, is considered. Subsequently, a life cycle assessment of the two storage systems is carried out to compare the environmental impacts.
The concrete sphere storage system performs better for 15 of 17 impact categories compared to the existing onshore battery storage system. Depending on the impact category the impact reduction is about 2% to 8%.
Nevertheless, it is difficult to estimate how long the useful life and how good the efficiency of the concrete ball storage will be, since no system of this size has been tested yet. Also, the costs of the concrete sphere storage system have not been considered.