In a microgrid connected with both intermittent and dispatchable sources, intermittency caused by sources such as solar and wind power plants can be balanced by dispatching hydro power into the grid. Both intermittent generation and consumption are stochastic in nature, not known perfectly, and require future prediction. The stochastic generation and consumption will cause the grid frequency to drift away from a required range. To improve performance, operation should be optimized over some horizon, with the added problem that intermittent power varies randomly into the future. Optimal management of dynamic system over a future horizon with disturbances is often posed as a Model Predictive Control (MPC) problem. In this paper, we have employed an MPC scheme for generating a hydro-turbine valve signal for dispatching necessary hydro power to the intermittent grid and maintaining grid frequency. Parameter sensitivity analysis shows that grid frequency is mostly sensitive to the turbine valve signal. We have found that controller discretization time, grid frequency, and power injection into the grid are interrelated, and play an important role in maintaining the grid frequency within the thresholds. Results also indicate that the fluctuations in grid frequency are insignificant on the turbine valve position during power injection into the grid.

The past modelling of electrical powers systems used to be a the domain of a few major power system modelling tools. Commercial tools 1 like DIgSILENT PowerFactory [3], POWERSYS EMTP-RV [17], PSCAD TM [14], Siemens PSS/E R ⃝ [20] are just some examples. All of them very powerful but with their own proprietary format for the models created makes it hard to exchange validated models of power systems. In order to disconnect the dependency of the power system model from the power system tool a project funded by the European Commission was started called "iTesla-Innovative Tools for Electrical System Security within Large Areas" [7]. One of the results of the project was the creation of a open-source modelling library called iPSL [24]. The library was created using the open-source Modelica modelling language which in turn allows to be used with several different Modelica modelling tools. The strong focus during the project was the validation of the models contained in the library. Most components stem from other tools (e.g., PSAT [15], PSS/E R ⃝ [20]). But the iPSL is by far not the first open-source power system library written in Modelica. Other libraries which have been around before are: SPOT [1], ObjectStab [11] and PowerSystems [6] (an updated subset of SPOT). In addition the iPSL library has been "forked" as OpenIPSL [21] by SmartTS Lab which is one partners of the original "iTesla" project. This paper is going to investigate the differences of the different available power system libraries. Point out their specific strength and weaknesses with respect to userfriendliness, robustness, physical representation and validation.

Biogas upgrading to biomethane with microbial electrosynthesis (MES) is receiving much attention due to increasing biomethane demands and surplus renewable energy. Research has demonstrated the feasibility of MES to increase methane yield by reducing CO₂ in anaerobic digestion (AD). Such CO₂ reduction occurs at the cathode and requires the supply of both protons and electrons. The most studied sources of protons and electrons are oxidation of organic substances and water, generated at the anode. These anodic reactions, however, also imply the production of CO₂ and O₂, respectively, both with negative implications for the AD process. A source of protons and electrons without CO₂ and O₂ as by-products would be beneficial for MES-enhanced biomethane production. This opinion article discusses the possibility of ammonium to serve as a sustainable proton and electron source.

This article presents a flexible control interface based on low-cost hardware solutions for electric drives which classically come either with a proprietary hardware solution or a high-cost interface solution. The interface presented can be used to connect a standard PC with an electric drive to enable testing simulation and control applications. The control interface is developed based on the open-source Python scripting language and Arduino’s open-source and accessible hardware. The new interface communicates with the test stand through its I/O terminals via developed electronic amplifiers and creates a solid base for further development towards more extensive hardware in the loop simulations.

This article presents the different approaches and use cases for efficient parameterization of Modelica models by means of external data resources. The main motivation is to improve the overall quality, testability and reusability of Modelica application models (both on component and system level) by a separation of the behavioral implementation from its actual design parameters. The Modelica libraries ExternData and ModelicaTableAdditions are freely available to support library developers and vendors in their ambitions to offer clean and dedicated interfaces for the parameterization of the application models and to benefit from a large variability of commonly used file types, such as CSV, Excel, HDF, JSON, MATLAB MAT, XML or even domain-specific file types such as for tire properties or weather data.