Power Load Management as a Computational Market

Power load management enables energy utilities to reduce peak loads and thereby save money. Due to the large number of different loads, power load management is a complicated optimization problem. We present a new decentralized approach to this problem by modeling direct load management as a computational market. Our simulation results demonstrate that our approach is very efficient with a superlinear rate of convergence to equilibrium and an excellent scalability, requiring few iterations even when the number of agents is in the order of one thousand. Aframework for analysis of this and similar problems is given which shows how nonlinear optimization and numerical mathematics can be exploited to characterize, compare, and tailor problem-solving strategies in market-oriented programming

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

Constructing Speculative Demand Functions in Equilibrium Markets

In computational markets utilizing algorithms that establish a general equilibrium, competitive behavior is usually assumed: each agent makes its demand (supply) decisions so as to maximize its utility (profit) assuming that it has no impact on market prices. However, there is a potential gain from strategic behavior via speculating about others because an agent does affect the market prices, which affect the supply/demand decisions of others, which again affect the market prices that the agent faces. Determining the optimal strategy when the speculator has perfect knowledge about the other agents is a well known problem which has been studied in oligopoly theory in economics. We describe the computation of such a strategy, and focus on an issue that has received little attention in economics, but which is of fundamental importance in computational markets: the revelation of demand strategies that drive the market to the desired equilibrium. The more realistic setting where the speculator has imperfect information about the other agents is more delicate. We demonstrate how speculation under biased beliefs about the other agents can result in considerable losses if traditional oligopoly strategies for perfect information are used. Furthermore, we show how the optimal demand is computed from probability distributions on the other agents\u27 supply/demand functions. We also theoretically show when an optimal revealed demand function can be constructed independently of the probability distributions. Some pragmatics of choosing a demand function in the case of imperfect information (particularly useful for construction of computational agents for equilibrium markets) are given, and we show - with some empirical support - that it can be relatively easy to construct demand functions that results in a gain from speculation, even when estimation errors are large. Finally, game theoretic issues related to multiple agents counterspeculating simultaneously 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

Psychometric properties of a short version of the HIV stigma scale, adapted for children with HIV infection

Background: HIV is a stigmatizing medical condition. The concept of HIV stigma is multifaceted, with personalized stigma (perceived stigmatizing consequences of others knowing of their HIV status), disclosure concerns, negative self-image, and concerns with public attitudes described as core aspects of stigma for individuals with HIV infection. There is limited research on HIV stigma in children. The aim of this study was to test a short version of the 40-item HIV Stigma Scale (HSS-40), adapted for 8–18 years old children with HIV infection living in Sweden. Methods: A Swedish version of the HSS-40 was adapted for children by an expert panel and evaluated by think aloud interviews. A preliminary short version with twelve items covering the four dimensions of stigma in the HSS-40 was tested. The psychometric evaluation included inspection of missing values, principal component analysis (PCA), internal consistency, and correlations with measures of health-related quality of life (HRQoL). Results: Fifty-eight children, representing 71% of all children with HIV infection in Sweden meeting the inclusion criteria, completed the 12-item questionnaire. Four items concerning participants’ experiences of others’ reactions to their HIV had unacceptable rates of missing values and were therefore excluded. The remaining items constituted an 8-item scale, the HIV Stigma Scale for Children (HSSC-8), measuring HIV-related disclosure concerns, negative self-image, and concerns with public attitudes. Evidence for internal validity was supported by a PCA, suggesting a three factor solution with all items loading on the same subscales as in the original HSS-40. The scale demonstrated acceptable internal consistency, with exception for the disclosure concerns subscale. Evidence for external validity was supported in correlational analyses with measures of HRQoL, where higher levels of stigma correlated with poorer HRQoL. Conclusion: The results suggest feasibility, reliability, as well as internal and external validity of the HSSC-8, an HIV stigma scale for children with HIV infection, measuring disclosure concerns, negative self-image, and concerns with public attitudes. The present study shows that different aspects of HIV stigma can be assessed among children with HIV in the age group 8–18

Market-Based Allocation with Indivisible Bids

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

Conditions for parents' participation in the care of their child in neonatal intensive care – a field study

<p>Abstract</p> <p>Background</p> <p>To promote participation by parents in the care of their child in neonatal intensive care units (NICU), health professionals need better understanding of what facilitates and what obstructs participation. The aim was to elucidate conditions for parents' participation in the care of their child in NICUs.</p> <p>Methods</p> <p>A field study with a hermeneutic lifeworld approach was used and data were collected at two NICUs through participative observations and interviews with representatives of management, staff and parents.</p> <p>Results</p> <p>The results point to a number of contradictions in the way parents were offered the opportunity to participate in neonatal intensive care. Management and staff both had good ambitions to develop ideal care that promoted parent participation. However, the care including the conditions for parental participation was driven by the terms of the staff, routines focusing on the medical-technical care and environment, and budgetary constraints.</p> <p>Conclusion</p> <p>The result shows that tangible strategies need to be developed in NICUs aimed at optimising conditions for parents to be present and involved in the care of their child.</p