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Abstract The paper presents results developing an innovative power supply system on the basis of a modular, flexibly customizable and cost-effective lithium-ion battery and power converter unit for peak-shaving and load levelling applications in the industrial sector including advanced self-consumption optimization strategies for renewable energies. First, the paper describes a monitoring campaign with high resolution measurements on machine, plant and factory level. Second, technical and economic simulation models for the components (battery, power conversion system and energy management) and the integrated system (including total investment costs, conversion losses, state of charge estimation) are presented. The innovative features of the system are described, including a multi-criteria optimizing energy management based on an adaptive dynamic programming algorithm, battery condition monitoring and a hybrid battery storage approach. Third, results of the optimizing design process are presented. The optimal type and power rating of converters and switches and the optimal system topology are determined and discussed for an application example. Simulation results for three DC-DC and five DC-AC converter topologies and two different energy management concepts are discussed and compared. [ABSTRACT FROM AUTHOR]

Abstract This paper presents a model predictive control approach for a home energy system with a heat pump, a thermal storage, a photovoltaic system and a battery. The modeling of the system in the mixed-integer linear programming framework is demonstrated and results of a one-year simulation with real measured PV and electric load data are shown. Different solution strategies for the underlying optimization problem are presented. The strategies are compared with respect to their performance and reliability. In this rather complex case branch & cut-based algorithms performed best in solving the optimization problem. [ABSTRACT FROM AUTHOR]

The paper describes a new optimizing design concept for autonomous power supply systems employing an enhanced particle swarm algorithm taking into account both component sizing and energy management parameters. The structure of the overall optimization problem is investigated showing high complexity and nonlinearity particularly for switching energy management strategies. The specific features of the enhanced particle swarm optimization algorithm are discussed. The new optimizing design concept is investigated for two application examples, a private household and a small agricultural holding. The performance of the enhanced particle swarm algorithm is compared to two reference algorithms, a standard particle swarm and a genetic algorithm. The enhanced particle swarm algorithm shows the highest accuracy and fastest convergence speed for both applications and for both energy management strategies. [ABSTRACT FROM AUTHOR]

The paper presents an equivalent circuit based simulation model for the static and dynamic behavior of lithium-ion battery systems and explains the different steps of the theoretical and experimental modeling process. The equivalent circuit based model describes the voltage-current characteristic, the state of charge behavior and the occurring losses of the battery system. A parameter identification method based on three characteristic experiments, a cycle test, an open circuit voltage test and pulse tests, is introduced. The model parameters are estimated employing a nonlinear optimization method. Furthermore, the experimental test bed for investigation of lithium-ion battery systems is described. The battery model approach is demonstrated and validated for a commercial 5 kWh lithium-ion battery system, including the model validation for test profiles and emulated battery charging and discharging profiles of a real photovoltaic home storage application. The comparison of measured and simulated voltage profiles indicates an excellent performance of the battery model. [ABSTRACT FROM AUTHOR]

This paper presents an optimizing model-based energy management system for an AC-coupled grid connected photovoltaic battery system. The energy management consists of a prediction module, an optimization module, and a reactive management module. The main focus of this article is to present an innovative reactive management that can handle forecast uncertainties. The so called “SOC-bound method” will be described in detail. Main idea is to combine the outputs of the dynamic programming algorithm with a simple rule-based strategy. Furthermore, the results of a start-time and start-/end-SOC sensitivity analysis concerning the six performance criteria self-sufficiency, self-consumption, grid relief factor, economic parameter, battery full cycles, and specific battery stress value will be discussed. [ABSTRACT FROM AUTHOR]

Thepaper presents a new concept for the optimal design of autonomous energy supply systems based on a photovoltaic plant, a battery and a hydrogen storage path (PV-battery-H 2 -hybrid system) with the focus on the optimal sizing of therated power and the capacity of all system components. For this purpose a multi-criteria objective function (combining installation and operating costsas well as componentlifetime) and multiple constrains (e.g. security of supply) are considered. The basic characteristics and the complexity of the resulting solutionspace of the optimization problem are described as a function of the sizing and energy management parameters. For the minimization of the objective function a particle swarm algorithm was employed. The paper presents the implementation of the algorithm and simulation results for an example hybrid system configuration. The behaviour of the particle swarm is investigated for different scenarios. Results demonstrate excellent computational speed and accuracy compared to other optimization methods. [ABSTRACT FROM AUTHOR]

Abstract: The paper presents a new multi-storage hybrid system concept for the improvement of self-consumption rate, conversion efficiency and storage lifetime in photovoltaic (PV) hybrid systems. Main idea is the smart combination and control of short- and long-term storage technologies with supplementary operating characteristics. The paper discusses a typical application example of a PV-hybrid system with lithium-ion battery, hydrogen and heat storage path. A dynamic lithium-ion battery model is presented. The power electronic and control structure of the multi-storage experimental test-bed is explained. Investigation results for a typical application example demonstrate the functionality and benefits of the proposed concept. [Copyright &y& Elsevier]