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Die Hochschule Offenburg begleitet seit Juli 2006 in Zusammenarbeit mit dem Fraunhofer ISE in Freiburg, die solar unterstützte Klimatisierung der Festo AG & Co. KG in Esslingen im Rahmen des Forschungsvorhabens Solarthermie2000plus. Dabei wurde die bereits bestehende Adsorptionskälteanlage, die bisher mit Gaskesseln und Kompressorenabwärme betrieben wurde, durch eine Solaranlage als dritte Wärmequelle ergänzt.
Sustainable Aspects force a building manager to continuous observation of actual states and developments concerning building use, energy and media flows.In the presented approach a communication structure was built up to use different software applications and tools in order to optimize the operation of the building.
The PHOTOPUR project aims to develop a photocatalytic process as a type of AOPs (Advanced Oxidation Processes) for the elimination of plant protection products (PPP) of the cleaning water used to wash sprayers. At INES a PV based energy supply for the photocatalytic cleaning system was developed within the framework of two bachelor theses and assembled as a demonstration unit. Then the system was step by step extended with further process automation features and pushed to a remote operating device. The final system is now available as a mobile unit mounted on a lab table. The latest step was the photocatalytic reactor module which completed the first PHOTOPUR prototype. The system is actually undergoing an intensive testing phase with performance checks at the consortium partners. First results give an overview about the successful operation.
An energy oriented design concept was developed within the research project PHOTOPUR which has the development of a PV powered water cleaning system as main focus. During a wine season Plant Protection Products (PPP) are several times sprayed on plants to protect them of undesired insects and herbs or avoid hazardous fungus
types. A work package of the project partner INES in Offenburg led to a design introducing energy profiling already in the early beginning of a product design. The concept is based on three pillars respecting first the
requirements of the core process making up filtering and cleaning and secondary aspects which run, support, maintain and monitor the system to secure availability and product reliability.
The presented paper shows that the results of the design tools guided the developers to assemble a functional model of the water decontamination unit which was manually tested with its concatenated steps of the water cleaning process.
Three real-lab trigeneration microgrids are investigated in non-residential environments (educational, office/administrational, companies/production) with a special focus on domain-specific load characteristics. For accurate load forecasting on such a local level, à priori information on scheduled events have been combined with statistical insight from historical load data (capturing information on not explicitly-known consumer behavior). The load forecasts are then used as data input for (predictive) energy management systems that are implemented in the trigeneration microgrids. In real-world applications, these energy management systems must especially be able to carry out a number of safety and maintenance operations on components such as the battery (e.g. gassing) or CHP unit (e.g. regular test runs). Therefore, energy management systems should combine heuristics with advanced predictive optimization methods. Reducing the effort in IT infrastructure the main and safety relevant management process steps are done on site using a Smart & Local Energy Controller (SLEC) assisted by locally measured signals or operator given information as default and external inputs for any advanced optimization. Heuristic aspects for local fine adjustment of energy flows are presented.
The increase in households with grid connected Photovoltaic (PV) battery system poses challenge for the grid due to high PV feed-in as a result of mismatch in energy production and load demand. The purpose of this paper is to show how a Model Predictive Control (MPC) strategy could be applied to an existing grid connected household with PV battery system such that the use of battery is maximized and at the same time peaks in PV energy and load demand are reduced. The benefits of this strategy are to allow increase in PV hosting capacity and load hosting capacity of the grid without the need for external signals from the grid operator. The paper includes the optimal control problem formulation to achieve the peak shaving goals along with the experiment set up and preliminary experiment results. The goals of the experiment were to verify the hardware and software interface to implement the MPC and as well to verify the ability of the MPC to deal with the weather forecast deviation. A prediction correction has also been introduced for a short time horizon of one hour within this MPC strategy to estimate the PV output power behavior.
This paper presents the use of model predictive control (MPC) based approach for peak shaving application of a battery in a Photovoltaic (PV) battery system connected to a rural low voltage gird. The goals of the MPC are to shave the peaks in the PV feed-in and the grid power consumption and at the same time maximize the use of the battery. The benefit to the prosumer is from the maximum use of the self-produced electricity. The benefit to the grid is from the reduced peaks in the PV feed-in and the grid power consumption. This would allow an increase in the PV hosting and the load hosting capacity of the grid.
The paper presents the mathematical formulation of the optimal control problem
along with the cost benefit analysis. The MPC implementation scheme in the
laboratory and experiment results have also been presented. The results show
that the MPC is able to track the deviation in the weather forecast and operate
the battery by solving the optimal control problem to handle this deviation.
In this paper, a new method is demonstrated for online remote simulation of photovoltaic systems. The required communication technology for the data exchange is introduced and the methods of PV generator parameter extraction for the simulation models are analysed. The method shown for parameter extraction from the manufacturer data is especially useful for the commissioning procedure, where the measured installed power is transferred to standard test conditions using the simulation model and can then be easily compared with the design power. At a simulation accuracy of 2% using the software environment INSEL ® any problems with the PV generator can reliably be detected. Online simulation of a grid connected PV generator is then carried out during the operation of the photovoltaic plant. The visualisation includes both the monitored and the simulated online data sets, so that a very efficient fault detection scheme is available. The method is implemented and validated on several grid connected photovoltaic power plants in Germany. It is excellently suited to provide automatic and real time fault detection and significantly improve the commissioning procedure for photovoltaic plants of all sizes.
The uncertain and time-variant nature of renewable energy results in the need to deal with peaks in the production of energy. One approach is to achieve a load shift and thereby help balancing the grid by using thermally Activated Building Systems (TABS). Control systems currently in place do not exploit the full potential of TABS. This paper reviews how Model Predictive Control can possibly reduce the fluctuations of the demand and supply of (renewable) energy as it enables the TABS to react to the dynamics of weather and its impact on the grid at any time.
Für die solarunterstützte CO2-neutrale Nahwärmeversorgung des Neubaugebiets Hülben in Holzgerlingen wurden Holzpelletskessel mit einer 249m²-großen Solaranlage kombiniert. Im ersten Intensivmessjahr vom 01.03.2007 bis 29.02.2008 wurde eine Gesamt-Wärmeabgabe ins Nahwärmenetz von 920.606 kWh gemessen, wobei der solare Anteil bei 84.033 kWh lag. Es wurden ein Systemnutzungsgrad von 23,8 % und ein solarer Deckungsanteil von 9,5% gemessen. Die vom Lieferanten abgegebene Energiegarantie wurde in der ersten Intensivmessphase nicht erreicht.