Combined Smart Energy Systems

In smart and micro grids the control tasks of large power plants are obtained through the control of many small distributed generation systems, the flexibility of the current loads (for example, the production of thermal energy from power) and through the use of energy storage. But this means much more dynamic and unstructured operations within the power system which leads to a significantly increasing regulatory and data collection effort. Concurrently it is necessary to guarantee for stable operations as well as a cost-effective and environmentally friendly energy supply. This leads to an extended use of different communication systems which, in turn, affect the control. Eventually even factors such as privacy, limited access to measurement data, operational safety and user's personal factors have to be taken into account. All these various aspects provide an overview of the research content of CoSES laboratories and imply the need for interdisciplinary cooperation.

About CoSES Research Laboratory

The CoSES research lab provides a real micro grid consisting of 4 family houses (EFH1-4) and a multi-family house (MFH) used as laboratory. That is real energy is generated, transmitted and regulated in real-time.

Fluctuating energy generators such as photovoltaic (PV), wind energy and solar thermal are mainly dependent on external conditions such as solar irradiation or wind blowing in their current production capacity. The laboratory is designed so that these external conditions can be specified either by simulation or there are actual plants with natural weather conditions used for the experiment. A special feature in this laboratory is the local heating network. Conventional heating networks are clearly defined in the energy flow from producers to consumers, but in a network with distributed energy each node should be able to act independently with every other node. That is, each node is both an infeed and exit point. The communication between the devices can take place in many ways e.g. Powerline, Ethernet, WiFi or LTE. For communication control new programmable switches are used to replicate the different influences of the communication scheme.

An incomplete list of interesting questions for the CoSES project

• How to optimize the heat supply line?
• How can a heating network with distributed nodes that may be consumers and producers at the same time be designed?
• How can new or future producers be integrated into the microgrid?
• Which traffic is generated by the components and systems of the microgrid? What are the statistical properties and how can they be used for the development of the exact traffic model? Which communication requirements must be met for a proper operation?
• How can efficient media access method be modeled to meet the communication needs?
• How is the stability of the power system affected by the trading of energy and how can this be guaranteed? How can the structure for the trading of energy (both electricity and heat) within the microgrid be derived?
• How can data protection aspects be taken into consideration by the scheme? To what extent this will help/complicate the distributed control and optimization?
• How can the efficiency and reliability be ensured for a system with limited resources (communication, computing, power)?
• How can the very different objectives of stabilization and optimization be achieved? How is it possible to automatically adjust the control when the structure of the microgrid is changed? (e.g. by taking away/adding consumers or producers (plug and play) or by changing external conditions, such as altered user behavior) (adaptive control)

ITR preliminary work on NCS

The design and optimization of control algorithms for complex dynamical systems is a focal aspect in this project. In our works [1, 2, 5], we consider a linear time-invariant system and a quadratic cost functional. The work in [1] considers a multiple-loop networked control system (NCS) where all control loops share a communication network. This introduces coupling through the communication channel although no physical coupling is considered. Medium Access Control (MAC) is performed in a contention-based fashion where each control loop decides locally whether to attempt a transmission based on some error thresholds (i.e., decentralized threshold-based scheduling policy). Furthermore, a local event-based resource-aware scheduling design with an adaptive choice of the error thresholds for a transmission is introduced. Additionally a bi-character deterministic-probabilistic scheduling mechanism which dynamically assigns access priorities to each sub-system at each time-step according to an error-dependent priority measure is introduced. This leads to a hybrid channel access mechanism where the control loops are deterministically categorized into two sets of eligible and ineligible sub-systems for transmission in an event-based fashion, before a random process selects the available channels.

In [2], which is an extension of the work in [1], the problem of event-based data scheduling for a class of physically interconnected networked control systems which compete for limited communication resources is studied. The overall interconnected system consists of multiple heterogeneous LTI sub-systems with the physical interconnection being modelled by a directed acyclic graph (DAG). This is the case when, for example, there is physical coupling between microgrids. For these systems we have developed distributed optimal control approaches and tools for the distributed analysis. We have studied the influence of the information topology on the performance in large-scale systems and proposed distributed approaches for optimal topology control (also including time delays) using eigenvalue sensitivity analysis and algebraic graph theory.

Employing the introduced policies, the stochastic stability of the resulting NCS in terms of Lyapunov stability in probability and ergodicity is shown. The efficiency of the proposed approach in terms of reducing the average networked-induced error variance is exploited numerically, and the superiority of the adaptive event-based scheduler compared to the scheduling design with non-adaptive thresholds is shown. Future work aims at finding the exact relation or a close approximation of the relation between the network state and the optimal transmission threshold.

Our proposed approach facilitates a distributed design of the distributed control law while guaranteeing stability and performance. The results are successfully applied for the damping control in the electrical power grid. Furthermore, we have developed a MATLAB toolbox for the simulation of large-scale networked systems.

Publications

•  [1] M. Vilgelm; M.H. Mamduhi; W. Kellerer; S. Hirche: Adaptive Decentralized MAC for Event-triggered Networked Control Systems. 19th International Conference on Hybrid Systems: Computation and Control (HSCC), 2016 more… BibTeX
• [2] M.H. Mamduhi; F. Deroo; S. Hirche: Event-based Data Scheduling for a Class of Interconnected Networked Control Systems. IEEE 54th Annual Conference on Decision and Control (CDC), 2015 more… BibTeX Volltext (mediaTUM)
• [3] Kuhn, Philipp; Huber, Matthias; Dorfner, Johannes; Hamacher, Thomas: Challenges and opportunities of power systems from smart homes to super-grids. Ambio 45, 2015, 50-62 more…
• [4] Dorfner, Johannes; Hamacher, Thomas: Large-Scale District Heating Network Optimization. IEEE Trans. Smart Grid 5 (4), 2014, 1884-1891 more…
•  [5] A. Molin; S. Hirche: On the Optimality of Certainty Equivalence for Event-triggered Control Systems. IEEE Transactions on Automatic Control no. 2 (58), 2013, 470-474 mehr… BibTeX Volltext (mediaTUM)

People involved in CoSES

The CoSES Research Laboratory is an interdisciplinary institution of CoSES Research Group under the joint control of:

• Dr. C. Hackl, MSE research group Control of renewable energy systems,
• Prof. Dr. rer. nat. T. Hamacher, Chair of Renewable and Sustainable Energy Systems,
• Prof. Dr.-Ing. S. Hirche, Chair of Information-oriented Control,
• Prof. Dr.-Ing. W. Kellerer, Chair Communication Networks,
• Prof. Dr.-Ing. Wagner, Institute for Energy Economy and Application Technology,
• Prof. Dr.-Ing. R. Witzmann, Chair of High Voltage Engineering and Switchgear Technology.