Scalable Integration of 4GL-Models and Algorithms for massive Smart Grid Simulations and Applications
Thomas Preisler, Gregor Balthasar, Tim Dethlefs, Wolfgang Renz · EnviroInfo · 2014
This paper presents a scalable integration approach for algorithms and models written in fourth g eneration (programming) languages for massive Smart Grid simulations as well as applications. While fourth generation languages (4GL) focus on rapid application development and the reduction of lines of code, they lack of integration and scalability features. Nevertheless, they are widely spread and often used by engineers. The scalable integration of such elements is achieved in this paper by wrapping the 4GL-models and algorithms with established web technologies like RESTful web services and load balancing. The provision of a seamless integration concept allows engineers to focus on rapid application development and liberates them from integration efforts. 1. Introduction Today’s energy grid undergoes a structural change towards the so-called Smart Grid. The power g rid will no longer be dominated by a relatively small number of large coal and nuclear power plants, but rather by a large number of distributed, renewable energy resources (DER). Hereby the control and coordination of this large number of DERs in order to balance the generation and demand is the main challenge. Due to the quantity and restrictions of the involved components it is a challenging task. With respect to the grid stability control strategies need to be developed as well as evaluated and tested particularly. To achieve this a wide range of simulation scenarios have to be established facilitating an economical transition towards a Smart Grid and ensuring its reliability [13]. The approach presented in this paper introduces a concept for the scalable integration of 4GL-models and algorithms for such Smart Grid simulations. It is also used in an