Christian HinrichsJade University of Applied Sciences
Christian Hinrichs
Professor
About
26
Publications
6,252
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407
Citations
Publications
Publications (26)
The aggregation of controllable distributed energy resources (DER) to virtual power plants (VPPs) forms a possible integration path for DER in future energy systems. The authors present a fully distributed scheduling heuristic for VPPs. The approach is realised by representing each participant of a VPP by a self-interested agent. Both the global, o...
Following
the
long-term
goal
of substituting conventional, fossil power generation completely with cleaner, renewable energy will consequently lead to an integration of a large share of small energy generation units imposing large problem sizes for coordination. Hardly predictable, stochastic feed-in makes the problem even harder. Predictive schedu...
The aggregation of distributed energy resources in virtual power plants (VPPs) is a feasible approach to overcome entry barriers for energy markets like, e.g., the European Power Exchange SE (EPEX SPOT SE). An increasing number of energy supply companies offer the integration of decentralized units in VPPs aiming to achieve the maximum profit by tr...
Following the long-term goal of substituting conventional power generation with cleaner energy will lead to an integration of a large share of small energy generation units imposing large problem sizes for coordination. The expected huge number of entities leads to a need for new techniques reducing the computational effort for coordination. Predic...
In this contribution we present an approach on how to include local soft constraints in the fully distributed algorithm COHDA for the task of energy units scheduling in virtual power plants (VPP). We show how a flexibility representation based on surrogate models is extended and trained using soft constraints like avoiding frequent cold starts of c...
The "Royal Road" objective function was proposed by J. H. Holland in 1993 as a very hard benchmark problem for evolutionary algorithms. Generally, it belongs to the class of combinatorial optimization problems. In our work, we solve the problem in a distributed way by assigning each decision variable to an autonomous agent. The resulting multi-agen...
In this contribution we want to sum up how computer science, ecological modeling and
control of distributed power systems mutually influence. First we show, how ecological modeling has
been influenced by the availability of faster computers and easier to use programming environments.
Then we argue that adaption and emergent behavior in biological s...
The increasing pervasion of information and communication technology (ICT) in the power grid motivates innovative research towards intelligent system control. Especially against the background of the growing share of renewable generation, novel approaches that mitigate e.g. grid expansion costs are of great interest. In this paper, the self-organiz...
Renewable Energy Sources (RES) are considered a solution for a sustainable power supply. But integrating these decentralized power sources into the current power grid designed for a centralized power supply is a challenging task. We suggest distributed, agent-based and self-organized control algorithms for distributed units in a ‘‘Smart Grid’’ as a...
In many countries, the currently observable transformation of the power
supply system from a centrally controlled system towards a complex "system of
systems", comprising lots of autonomously interacting components, leads to a
significant amount of research regarding novel control concepts. To facilitate
the structured development of such approache...
Solving Distributed Constraint Optimization Problems has a large significance in today's interconnected world. Complete as well as approximate algorithms have been discussed in the relevant literature. However, these are unfeasible if high-arity constraints are present (i. e., a fully connected constraint graph). This is the case in distributed com...
We present a decentralized heuristic applicable to multi-agent systems (MAS), which is able to solve multiple-choice combinatorial optimization problems (MC-COP). First, the MC-COP problem class is introduced and subsequently a mapping to MAS is shown, in which each class of elements in MC-COP corresponds to a single agent in MAS. The proposed heur...
In collaborative multi-agent systems, the participating agents have to join forces in order to solve a common goal. The necessary coordi-nation is often realized by message exchange. While this might work per-fectly in simulated environments, the implementation of such systems in a field application usually reveals some challenging properties: arbi...
The increasing pervasion of information and com-munication technology (ICT) in energy systems allows for the development of new control concepts on all voltage levels. In the distribution grid, this development is accompanied by a still increasing penetration with distributed energy resources like photovoltaic (PV) plants, wind turbines or small sc...
In the context of Smart Grid applications, distributed control algorithms show advantageous properties over classical centralized approaches. Regarding their operation in a critical infrastructure, however, it is of utmost importance to validate the correct behavior of such approaches beforehand. In this paper, we give an overview on different aspe...
In distributed combinatorial optimization problems, the underlying decision variables are usually constrained by interdependencies. For a successful optimization, a coordination strategy based on information exchange is thus necessary. An example for such a problem is the day-ahead planning of controllable distributed energy units (DEU). Here, each...
In many virtual power plant (VPP) scenarios, numerous individually configured units within a VPP have to be scheduled regarding both global constraints (i.e. external market demands) and local constraints (i.e. technical, economical or ecological aspects for each unit). Approaches for global and local constraint handling have been discussed in the...
Whenever multiple stakeholders try to optimize a common objective function in a distributed way, an adroit coordination mechanism is necessary. This contribution presents a formal model of distributed combinatorial optimization problems. Subsequently, a heuristic is introduced, that uses self-organizing mechanisms to optimize a common global object...
Multi-agent systems often consist of heterogeneous agents with different capabilities and objectives. While some agents might try to maximize their system's utility, others might be self-interested and thus only act for their own good. However, because of their limited capabilities and resources, it is often necessary that agents cooperate to be ab...
This paper provides an introduction to self-organizing mech-anisms in the domain of energy systems. We motivate the use of such mechanisms by outlining the drawbacks of present control systems and providing some advantageous proper-ties of self-organizing systems. We address the problem of a supply and demand matching of a large number of dis-tribu...
Zukünftige (elektrische) Transport- und Verteilnetze zeichnen sich im Gegensatz zu heutigen hierarchischen, statischen Netzen durch eine variierende Anzahl von Teilnehmern aus, die die Netze bidirektional in stark fluktuierender Intensität beanspruchen werden. Um den Ansprüchen solch einer heterogenen, schwierig vorherzusagenden Nutzung gerecht zu...
The eCarUs tool implements heuristic optimizations to find the optimal placement for battery stations for electric cars by using a simulation of traffic using real world data. A second optimization phase can calculate the required number of battery slots for each station.
Power grid stability is currently maintained by the grid operators through the use of stand-by generators. Another approach to this task is demand side management. There, devices with load shedding capabilities are used to support balancing the grid. This paper adresses the use of refrigerators in private households as controllable thermal storage....
Today's households face a huge variety of electricity consuming devices on the one hand, and increasing electricity prices and increased awareness for environmental sustainability on the other hand. Fluctuating electricity tariffs currently evaluated by electricity suppliers have the potential to make it even more com- plex for the electricity cons...
Questions
Question (1)
Market-based (i.e. microeconomic) approaches may be used in distributed settings for a number of tasks, including e.g. the Utility Maximization Problem. However, such problems target at optimizing individual (=local) objectives.
On the other hand, in distributed combinatorial optimization problems (e.g. the Multiple-Choice Subset-Sum Problem, or the Multiple-Choice Knapsack Problem) the task is to find a combination of (distributed) items that maximize a single *global* objective.
Question: Is there a way to apply market-based approaches to distributed combinatorial optimization?