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Different network architectures are being used to build remote laboratories. Historically, it has been difficult to integrate industrial control systems with higher level IT systems like enterprise resource planning (ERP), manufacturing execution systems (MES), and manufacturing operations management (MOM). Getting these systems to communicate with one another has proven to be relatively difficult due to the absence of shared protocols between them. The Open Platform Communications United Architecture (OPC-UA) protocol was introduced as a remedy for this issue and is gaining popularity, but what if open-source protocols that are widely used in the IT industry could be used instead? This paper presents the development of an IT-Architecture for a cyber-physical industrial control systems laboratory that enables a seamless interconnection and integration of its elements. The architecture utilises Node-Red technology. Node-RED is an open-source programming platform developed by IBM that is focused on making it simple to link physical components, APIs, and web services. This cyber-physical laboratory is for learning principles of an industrial cascaded process control factory. Finally, this text will also discuss future work relating to digital twin (DT). A coupled tank system is selected as a teaching factory to illustrate a range of fluid control application in a typical chemical process factory.
The presented research is dedicated to estimation of the correlation between the level of renewable energy sources and the costs of congestion management in electric networks in selected European countries. Data of six countries in North-West European area (Italy, Spain, Germany, France, Poland and Austria) were investigated. Factors considered included grid congestion costs including re-dispatching costs as well as countertrading costs, gross electricity generation, installed capacity of electric generating facilities, installed capacity of electric non-dispatchable renewable energy sources and total electricity consumption. Special attention is paid to the share of renewable energy sources. It is found that the grid congestion costs are not clearly affected by penetration of non-dispatchable renewables in all the analysed countries and therefore a clear mathematical correlation cannot no be extrapolated with the available data. The results of this research show in general a loose dependency of the grid congestion costs on the penetration of renewables and a strong dependency on the total electrical consumption of the country.
This article presents a modified method of performing power flow calculations as an alternative to pure energy-based simulations of off-grid hybrid systems. The enhancement consists in transforming the scenario-based power flow method into a discrete time-dependent algorithm with the inclusion of bus and controller dynamics.
This paper aims at presenting a solution that enables end customers of the energy system to participate in new local micro-energy-markets by providing them with a distributed, decentralized, transparent and secure Peer to Peer (P2P) payment system, which functions automatically applying new concepts of Machine to Machine (M2M) communication technologies. This work was performed within the German project VK_2G, funded by the DBU. The key results were: Providing means to perform microtransactions in a P2P fashion between end consumers and prosumers in local communities at low cost in a transparent and secure manner; Developing a platform with pre-defined smart contracts able to be tailored to different end customers ‘needs in an easy way and; Integrating both the market platform as well as the local control of generation and loads. This solution has been developed, integrated and tested in a laboratory prototype. This paper discusses this solution and presents the results of the first test.
This paper presents a novel emulation concept for the test of smart contracts and Distributed Ledger Technologies (DLT) in distribute control or energy economy tasks and use cases. The concept uses state of the art behavioral modeling tools such as Matlab Simulink but presents a possible way to solve the shortfall of Simulink in communicating to DLT-Nodes directly. This is solved through a middleware solution. After this, an example used in verifying the test bed is presented and the target demonstration object is described. Finally, the possible expansion of the system is discussed and presented.
The purpose of this article is to provide insight of a new simple forecasting method based on a state-estimation algorithm known as the Kalman filter. While the accuracy of such algorithm is not comparable to state-of-the-art forecasting algorithms for PV-power production it does not require any internet connection, eyefish cameras or time intensive training. The algorithm was tested with several months of real high-resolution data with adequate results for the intended applications. The minimization of the necessary spinning reserve on a PV-diesel hybrid system to increase the solar fraction and reduce diesel consumption.
The diversity of energy prosumer types makes it difficult to create appropriate incentive mechanisms that satisfy both prosumers and energy system operators alike. Meanwhile, European energy suppliers buy guarantees of origin (GoO) which allow them to sell green energy at premium prices while in reality delivering grey energy to their customers. Blockchain technology has proven itself to be a robust paying system in which users transact money without the involvement of a third party. Blockchain tokens can be used to represent a unit of energy and, just as GoOs, be submitted to the market. This paper focuses on simulating marketplace using the ethereum blockchain and smart contracts, where prosumers can sell tokenized GoOs to consumers willing to subsidize renewable energy producers. Such markets bypass energy providers by allowing consumers to obtain tokenized GoOs directly from the producers, which in turn benefit directly from the earnings. Two market strategies where tokens are sold as GoOs have been simulated. In the Fix Price Strategy prosumers sell their tokens to the average GoO price of 2014. The Variable Price Strategy focuses on selling tokens at a price range defined by the difference between grey and green energy. The study finds that the ethereum blockchain is robust enough to functions as a platform for tokenized GoO trading. Simulation results have been compared and the results indicate that prosumers earn significantly more money by following the Variable Price
Strategy.
Industrial hybrid systems with high pv penetration : performance, analysis and key success factors
(2016)
Since the first industrial-scale hybrid system was installed by SMA in 2012, information about the performance of several hybrid systems around the world has been monitored. This paper analyses the performance of SMA’s largest PV-Diesel hybrid system in the industrial-scale installed in Bolivia in 2014 and summarizes the lessons learned by managing this system with large-scale energy storage. The paper finally concludes with an outlook for future hybrid systems.