HOMEBOTS: Intelligent Decentralized Services for Energy Management

The deregulation of the European energy market, combined with emerging advanced capabilities of information technology, provides strategic opportunities for new knowledge-oriented services on the power grid. HOMEBOTS is the namewe have coined for one of these innovative services: decentralized power load management at the customer side, automatically carried out by a `society' of interactive household, industrial and utility equipment. They act as independent intelligent agents that communicate and negotiate in a computational market economy. The knowledge and competence aspects of this application are discussed, using an improved \ud version of task analysis according to the COMMONKADS knowledge methodology. Illustrated by simulation results, we indicate how customer knowledge can be mobilized to achieve joint goals of cost and energy savings. General implications for knowledge creation and its management are discussed

Decentralized Markets versus Central Control - A Comparative Study,

Multi-Agent Systems (MAS) promise to offer solutions to problems where established, older paradigms fall short. In order to validate such claims that are repeatedly made in software agent publications, empirical in-depth studies of advantages and weaknesses of multi-agent solutions versus conventional ones in practical applications are needed. Climate control in large buildings is one application area where multi-agent systems, and marketoriented programming in particular, have been reported to be very successful, although central control solutions are still the standard practice. We have therefore constructed and implemented a variety of market designs for this problem, as well as different standard control engineering solutions. This article gives a detailed analysis and comparison, so as to learn about differences between standard versus agent approaches, and yielding new insights about benefits and limitations of computational markets. An important outcome is that "local in..

Decentralized Markets versus Central Control: A Comparative Study

Multi-Agent Systems (MAS) promise to offer solutions to problems where established, older paradigms fall short. In order to validate such claims that are repeatedly made in software agent publications, empirical in-depth studies of advantages and weaknesses of multi-agent solutions versus conventional ones in practical applications are needed. Climate control in large buildings is one application area where multi-agent systems, and market-oriented programming in particular, have been reported to be very successful, although central control solutions are still the standard practice. We have therefore constructed and implemented a variety of market designs for this problem, as well as different standard control engineering solutions. This article gives a detailed analysis and comparison, so as to learn about differences between standard versus agent approaches, and yielding new insights about benefits and limitations of computational markets. An important outcome is that "local information plus market communication produces global control"

HOMEBOTS: Intelligent Decentralized Services for Energy Management

The deregulation of the European energy market, combined with emerging advanced capabilities of information technology, provides strategic opportunities for new knowledge-oriented services on the power grid. HOMEBOTS is the namewe have coined for one of these innovative services: decentralized power load management at the customer side, automatically carried out by a `society' of interactive household, industrial and utility equipment. They act as independent intelligent agents that communicate and negotiate in a computational market economy. The knowledge and competence aspects of this application are discussed, using an improved version of task analysis according to the COMMONKADS knowledge methodology. Illustrated by simulation results, we indicate how customer knowledge can be mobilized to achieve joint goals of cost and energy savings. General implications for knowledge creation and its management are discussed

Agent-based homeostatic control for green energy in the smart grid

With dwindling non-renewable energy reserves and the adverse effects of climate change, the development of the smart electricity grid is seen as key to solving global energy security issues and to reducing carbon emissions. In this respect, there is a growing need to integrate renewable (or green) energy sources in the grid. However, the intermittency of these energy sources requires that demand must also be made more responsive to changes in supply, and a number of smart grid technologies are being developed, such as high-capacity batteries and smart meters for the home, to enable consumers to be more responsive to conditions on the grid in real-time. Traditional solutions based on these technologies, however, tend to ignore the fact that individual consumers will behave in such a way that best satisfies their own preferences to use or store energy (as opposed to that of the supplier or the grid operator). Hence, in practice, it is unclear how these solutions will cope with large numbers of consumers using their devices in this way. Against this background, in this paper, we develop novel control mechanisms based on the use of autonomous agents to better incorporate consumer preferences in managing demand. These agents, residing on consumers' smart meters, can both communicate with the grid and optimise their owner's energy consumption to satisfy their preferences. More specifically, we provide a novel control mechanism that models and controls a system comprising of a green energy supplier operating within the grid and a number of individual homes (each possibly owning a storage device). This control mechanism is based on the concept of homeostasis whereby control signals are sent to individual components of a system, based on their continuous feedback, in order to change their state so that the system may reach a stable equilibrium. Thus, we define a new carbon-based pricing mechanism for this green energy supplier that takes advantage of carbon-intensity signals available on the internet in order to provide real-time pricing. The pricing scheme is designed in such a way that it can be readily implemented using existing communication technologies and is easily understandable by consumers. Building upon this, we develop new control signals that the supplier can use to incentivise agents to shift demand (using their storage device) to times when green energy is available. Moreover, we show how these signals can be adapted according to changes in supply and to various degrees of penetration of storage in the system. We empirically evaluate our system and show that, when all homes are equipped with storage devices, the supplier can significantly reduce its reliance on other carbon-emitting power sources to cater for its own shortfalls. By so doing, the supplier reduces the carbon emission of the system by up to 25% while the consumer reduces its costs by up to 14.5%. Finally, we demonstrate that our homeostatic control mechanism is not sensitive to small prediction errors and the supplier is incentivised to accurately predict its green production to minimise costs

Market-Based Allocation with Indivisible Bids

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/73571/1/j.1937-5956.2007.tb00275.x.pd

Intra-individual variability of saccadic velocity measured with the infrared reflection and magnetic scleral search coil methods.

BACKGROUND: The infrared (IR) and the magnetic scleral search coil (MSC) systems for eye tracking were studied with regard to the intra-individual variability in saccadic eye movement recordings. METHOD: Three healthy subjects performed similar saccadic eye movement tasks at five different occasions with both the IR (Orbit XY-1000) and the MSC (Skalar Medical) techniques. The maximum velocity (VMAX) and slope constant (C) of the main sequence plots were analyzed with regard to the coefficient of variation (CV) and the intraclass correlation coefficient (Ricc). In addition, the possible reasons for variability in the IR recordings, especially different causes for noise, were analyzed and discussed. RESULTS: The main sequence data showed intra-individual variation with both recording systems, but the coefficient of variation was higher for VMAX with the IR compared to the MSC method. Ricc analysis showed that 36% of the variance of VMAX and 49% of the variance of C resulted from intra-individual variability in recordings of the IR system. The corresponding results for the MSC recordings regarding VMAX and C were 48% and 88%. CONCLUSIONS: Saccadic eye movement recordings yielded a larger intra-individual variability with the IR system than with the MSC system. The effect that the MSC annulus may have on the ocular motor command signal and the possible low pass filter caused by the coil slipping on the surface of the eye may partly explain the relatively lower velocity in the MSC recordings. Also, noise in the IR recordings induces peaks of eye velocity, which can be reduced considerably by filtering. However, the variability in the recordings, which was larger in the IR than in the MSC recordings, did not seem to be decreased by filtering. The basic level of noise in the recordings was not clearly associated with the amount of reduction of VMAX when the IR recordings were filtered. We suggest that artefacts of the saccadic signal, which can be related to changes in the reflecting surface of the eyes and eyelids, are important factors for explaining the variability and high-velocity peaks in the IR recordings. Lighting conditions was confirmed as a cause for noise, but temperature and air humidity changes in the goggles were not suspected to influence data in the normal experimental setting. Although noise, shortcomings of the recording technique and procedure may offer explanations for the intra-individual variability, the calibration procedure and changes in attention and fatigue of the subject should also be considered