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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.
Cell lifetime diagnostics and system be-havior of stationary LFP/graphite lithium-ion batteries
(2018)
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.
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 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.
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.
In
this paper, a new method is demonstrated for onlin
e remote simulation of photovo
ltaic systems. The required
communication technology for the data exchange is introduced a
nd the methods of PV generato
r parameter extraction for the
simulation models are analysed. The method
shown for parameter extraction from the ma
nufacturer data is especially useful
for the commissioning procedure, where the measured installed pow
er is transferred to standard test conditions using the
simulation model and can then be easily compared with the de
sign power. At a simulation accuracy of 2% using the software
environment INSEL
®
any problems with the PV gene
rator 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 i
s
available. The method is implemented and
validated on several grid connected photovolta
ic power plants in Germany. It is
excellently suited to provide automatic and real time fault
detection and significantly impr
ove the commissioning procedure
for photovoltaic plants of all sizes.