Karl Stephan Stille

Local demand response and load planning system for intelligent domestic appliances

An energy management system for intelligent domestic appliances is presented, optimizing the operation of appliances in an environment with time-variable energy tariffs. In a standalone operation this results in a least-cost operation of the appliance. As these time-variable tariffs reflect the availability of generated power, particularly of renewables, the proposed system helps consuming electrical energy when renewable generation is high and vice versa. By static load shifting the process cost can be lowered. The proposed system guarantees the same process results tough operation programs are different or the process is interrupted. By this the load shifting potential is maximized. Besides the standalone mode, the proposed system can be the viewed as lowest level optimizer in a hierarchical optimization structure spanning from the domestic appliance over the complete household up to the local distribution grid or even further. In this operation mode the optimizer pre-optimizes the possible operation programs and starting times of the appliance and sends a set of possible optimal and near-optimal solutions to the household energy management system. By pre-optimizing the resulting load flexibilities and offering them to the household level optimizer, these flexibilities can be used for peak shaving or valley filling on that or even on a higher level.

Self-optimization energy management considering stochastic influences for a hybrid energy storage of an electric road vehicle

Electric and hybrid-electric vehicles place high demands for peak power, energy content and efficiency on the energy storage. By hybridization of the storage, adding double layer capacitors, the battery can be relieved from the stress of peak power and even downsized to meet only energy demands instead of power demands. Thus, the storage weight and losses can be significantly reduced. An energy management to distribute the power to both storages can be mathematically optimized applying Stochastic Dynamic Programming (SDP), considering stochastic influences of the driving process. To handle different conditions and driving cycles, we propose self-optimization control strategies involving multi-objective optimization. These strategies are able to autonomously adapt their behavior and relevance of objectives, offering an optimal and secure operation in different situations.

Online capable optimized planning of power split in a hybrid energy storage system

A hybrid energy storage system is an energy storage consisting of more than one type of energy storages combining their advantages. The system treated in this paper consists of NiMH batteries and double layer capacitors. The power flow needs to be split up between the storage devices. This defines a multi-objective optimization with the minimization of energy loss and maximization of the abilty to react on unforeseen power demands as objectives. So far this had to be optimized by offline methods on typical situations. This paper presents an optimization method that is capable of planning the power flow split at run time. For this purpose a Pareto Point search algorithm is used which geometrically constructs a function to minimize in the image space of objective functions. This is done by using single-objective optimization to find the endpoints of the Pareto Front. The function to be minimized then defines a trail on which the optimal solution for a given trade-off parameter is searched.

Local grid load coordination for load-shiftable domestic appliances in a variable-tariff environment

Some domestic appliances can shift their load by a least-cost optimization in a variable-tariff environment. As decisions of all appliances are highly correlated, high load peak arise. With the presented coordination in an optimization hierarchy, load peak is significantly lowered by load distribution in time.

Haushaltsgeräte im Smart Grid

In diesem Kapitel werden zunachst die Flexibilitaten von Haushaltsgrosgeraten im Bezug auf Prozessgestaltung und Prozessunterbrechung vorgestellt. Dabei werden die Moglichkeiten der Nutzung von Label- und Schnell-Waschprogrammen im Kontext der optimierten Prozessfuhrung beleuchtet. Anschliesend wird eine Modellierung des realen Benutzerverhaltens, also der Wahl des Beladungszeitpunktes des Gerates, und, in Abhangigkeit davon, des bei der Beladung gesetzten Fristzeitpunktes vorgestellt. Diese Modellierung ist fur die spatere Simulation, angesichts fehlender belastbarer Daten zum Benutzerverhalten, essentiell.

Methoden der dezentralen Lastoptimierung

In diesem Buch wird gezeigt, wie Haushaltsgrosgerate genutzt werden konnen, um die elektrische Last im Netz der Erzeugung anzupassen. In diesem Kapitel soll zur Orientierung ein Uberblick uber die verschiedenen Arten der Lastbeeinflussung und die bisher verfolgten und publizierten Konzepte geliefert werden. Dabei liegt der Fokus auf dem indirekten Lastmanagement in und mit Privathaushalten. Direkte Laststeuerung, bei der Gerate nur auf externe Steuersignale reagieren, wird dazu explizit nicht betrachtet.

Zusammenfassung, Fazit und Ausblick

Dieses Kapitel bildet die Zusammenfassung und das Fazit des Buches. Anschliesend werden weitere notwendige politische und technische Entwicklungen genannt.

Integration of home photovoltaic generation into electricity tariff for load optimization

In an electric power grid with a growing share of renewable sources a growing need to control the load on the demand side arises. A fast and effective measure are market-based time-variable electricity tariffs which reflect the load to energy supply ratio in the grid. These can be used for sot minimization leading to load shifting to low-load times. If the household is also equipped with a generation device as a solar panel, the feed-in tariff becomes important. This publication treats the calculation of an effective electricity tariff out of different tariffs for consumption and feed-in, taking the constraints of the generation device into account. This effective tariff is a means for a suitable visualizaiton and automatic load optimization.

Supervisionai load optimization for households with intelligent domestic appliances

An environment with time-variable electricity tariffs for private customers is an incentive to enable shifting of electrical loads to times of high generation. However, with automatically optimizing domestic appliances, load peaks arise, as all appliances choose the same least-cost operation time. This publication presents a system for household-wide optimization to avoid same-time operation of appliance while still optimizing for least overall cost. It facilitates integration into a hierarchical optimization scheme with another load optimizer on local grid level.

Examples of Self-optimizing Systems

In this chapter, the benefits resulting from self-optimization will be described based on application examples from the Collaborative Research Center 614 “Self-optimizing Concepts and Structures in Mechanical Engineering”. First, the autonomous rail vehicle RailCab developed at the University of Paderborn is introduced. Then, the RailCab subsystems Self-Optimizing Operating Point Control, Intelligent Drive Module, Active Suspension Module, Active Guidance Module and Hybrid Energy Storage System and their test rigs are described in detail as well as an overall approach for Energy Management. The chapter concludes with the presentation of other development platforms such as the BeBot, an intelligent miniature robot acting optimally in groups, and the X-by-wire vehicle Chameleon with independent single-wheel chassis actuators. All the above mentioned demonstrators are used to validate the methods and procedures developed in the Collaborative Research Center. The experiences gained, provide direct input into further development and optimization of the design as well as the self-optimization process.