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Photovoltaics Energy Prediction Under Complex Conditions for a Predictive Energy Management System
(2015)
Passive solar elements for both direct and indirect gains, are systems used to maintain a comfortable living environment while saving energy, especially in the building energy retrofit and adaptation process. Sunspaces, thermal mass and glazing area and orientation have been often used in the past to guarantee adequate indoor conditions when mechanical devices were not available. After a period of neglect, nowadays they are again considered as appropriate systems to help face environmental issues in the building sector, and both international and national legislation takes into consideration the possibility of including them in the building planning tools, also providing economic incentives. Their proper design needs dynamic simulation, often difficult to perform and time consuming. Moreover, results generally suffer from several uncertainties, so quasi steady-state procedures are often used in everyday practice with good results, but some corrections are still needed. In this paper, a comparative analysis of different solutions for the construction of verandas in an existing building is presented, following the procedure provided by the slightly modified and improved Standard EN ISO 13790:2008. Advantages and disadvantages of different configurations considering thermal insulation, windows typology and mechanical ventilation systems are discussed and a general intervention strategy is proposed. The aim is to highlight the possibility of using sunspaces in order to increase the efficiency of the existing building stock, considering ease of construction and economic viability.
Energy Performance of Verandas in the Building Retrofit Process (PDF Download Available). Available from: https://www.researchgate.net/publication/303093420_Energy_Performance_of_Verandas_in_the_Building_Retrofit_Process [accessed Jul 5, 2017].
Optimal microgrid scheduling with peak load reduction involving an electrolyzer and flexible loads
(2016)
This work consists of a multi-objective mixed-integer linear programming model for defining optimized schedules of components in a grid-connected microgrid. The microgrid includes a hydrogen energy system consisting of an alkaline electrolyzer, hydrogen cylinder bundles and a fuel cell for energy storage. Local generation is provided from photovoltaic panels, and the load is given by a fixed load profile combined with a flexible electrical load, which is a battery electric vehicle. The electrolyzer has ramp-up constraints which are modeled explicitly. The objective function includes, besides operational costs and an environmental indicator, a representation of peak power costs, thus leading to an overall peak load reduction under optimized operation. The model is used both for controlling a microgrid in a field trial set-up deployed in South-West Germany and for simulating the microgrid operation for defined period, thus allowing for economic system evaluation. Results from defined sample runs show that the energy storage is primarily used for trimming the peak of electricity drawn from the public grid and is not solely operated with excess power. The flexible demand operation also helps keeping the peak at its possible minimum.
Electric arc furnaces (EAF) are complex industrial plants whose actual behavior depends upon numerous factors. Due to its energy intensive operation, the EAF process has always been subject to optimization efforts. For these reasons, several models have been proposed in literature to analyze and predict different modes of operation. Most of these models focused on the processes inside the vessel itself. The present paper introduces a dynamic, physics-based model of a complete EAF plant which consists of the four subsystems vessel, electric system, electrode regulation, and off-gas system. Furthermore the solid phase is not treated to be homogenous but a simple spatial discretization is employed. Hence it is possible to simulate the energy input by electric arcs and fossil fuel burners depending on the state of the melting progress. The model is implemented in object-oriented, equation-based language Modelica. The simulation results are compared to literature data.
Proton Exchange Membrane Fuel Cell (PEMFC) is one of the most promising technologies for sustainable energy production due to the high power density, low operative temperature and more convenient use for several applications. Nevertheless, the high generated current that characterizes PEMFC requires a specific power conditioning. In addition, specific controller must be designed to fit with system operative points changing associated with the variation of this high current. To deal with this challenge, in this paper, an electrochemical system composed of a Proton Exchange Membrane Fuel Cell (PEMFC) feeding via two phases IBC has been proposed and investigated. For robustness, the used IBC for fuel cell voltage regulation is controlled by linear quadratic regulator (LQR). Then, genetic algorithms technique is applied to optimize the LQR controller parameters giving optimal control coefficients and can if necessary be adjusted according to each working situation change. The model of the entire system is studied using Matlab/Simulink environment. The simulation’s comparative standard and robustness results both demonstrate that the proposed GA-based LQR controller outperforms the conventional PI in terms of performance metrics (overshoot reduction: between 58.93% and 97.09%; response time reduction: between 56.40% and 77.00% and ripple reduction: between 84.00% and 94.86%).
Ecological concerns on the climatic effects of the emissions from electricity production stipulate the remuneration of electricity grids to accept growing amounts of intermittent regenerative electricity feed-in from wind and solar power. Germany’s eager political target to double regenerative electricity production by 2030 puts pressure on grid operators to adapt and restructure their transmission and distribution grids. The ability of local distribution grids to operate autonomous of transmission grid supply is essential to stabilize electricity supply at the level of German federal states. Although congestion management and collaboration at the distribution system operator (DSO) level are promising approaches, relatively few studies address this issue. This study presents a methodology to assess the electric energy balance for the low-voltage grids in the German federal state of Baden-Württemberg, assuming the typical load curves and the interchange potential among local distribution grids by means of linear programming of the supply function and for typical seasonal electricity demands. The model can make a statement about the performance and development requirements for grid architecture for scenarios in 2035 and 2050 when regenerative energies will—according to present legislation—account for more than half of Germany’s electricity supply. The study details the amendment to Baden-Württemberg’s electricity grid required to fit the system to the requirements of regenerative electricity production. The suggested model for grid analysis can be used in further German regions and internationally to systematically remunerate electricity grids for the acceptance of larger amounts of regenerative electricity inflows. This empirical study closes the research gap of assessing the interchange potential among DSO and considers usual power loads and simultaneously usual electricity inflows.
Am 1. Juli 2022 trafen sich im Rahmen des Abschlusskolloquiums des Projekts ACA-Modes rund 60 Teilnehmende aus Forschung, Lehre und Industrie zu einer internationalen Konferenz an der Hochschule Offenburg. Hier wurden die Projektergebnisse rund um die erfolgreiche Implementierung modellprädiktiver Regelstrategien vorgestellt, aktuelle Fragestellungen diskutiert und Entwicklungspfade hin zu einem netzdienlichen Betrieb von Energieverbundsystemen skizziert.