Competitive Benchmarking: An IS Research Approach to Address Wicked Problems with Big Data and Analytics

Wicked problems like sustainable energy and financial market stability are societal challenges that arise from complex socio-technical systems in which numerous social, economic, political, and technical factors interact. Understanding and mitigating them requires research methods that scale beyond the traditional areas of inquiry of Information Systems (IS) “individuals, organizations, and markets” and that deliver solutions in addition to insights. We describe an approach to address these challenges through Competitive Benchmarking (CB), a novel research method that helps interdisciplinary research communities to tackle complex challenges of societal scale by using different types of data from a variety of sources such as usage data from customers, production patterns from producers, public policy and regulatory constraints, etc. for a given instantiation. Further, the CB platform generates data that can be used to improve operational strategies and judge the effectiveness of regulatory regimes and policies. We describe our experience applying CB to the sustainable energy challenge in the Power Trading Agent Competition (Power TAC) in which more than a dozen research groups from around the world jointly devise, benchmark, and improve IS-based solutions

Autonomous agents in future energy markets: The 2012 power trading agent competition (abstract)

Sustainable energy systems of the future will need more than efficient, clean, and low-cost energy sources. They will also need efficient price signals that motivate sustainable energy consumption behaviors and a tight real-time alignment of energy demand with supply from renewable and traditional sources. The Power Trading Agent Competition (Power TAC) is a rich, competitive, open-source simulation platform for future retail power markets built on real-world data and state-of-the-art customer models. Its purpose is to help researchers understand the dynamics of customer and retailer decision-making as well as the robustness of proposed market designs. Power TAC invites researchers to develop autonomous electricity broker agents and to pit them against best-in-class strategies in global competitions, the first of which will be held at AAAI 2013. Power TAC competitions provide compelling, actionable information for policy makers and industry leaders. We describe the competition scenario, demonstrate the realism of the Power TAC platform, and analyze key characteristics of successful brokers in one of our 2012 pilot competitions between seven research groups from five different countries

Pricing mechanism for real-time balancing in regional electricity markets

We consider the problem of designing a pricing mechanism for precisely controlling the real-time balance in electricity markets, where retail brokers aggregate the supply and demand of a number of individual customers, and must purchase or sell power at the wholesale level such that the total supply matches total demand. This is typically done for future time periods by buying and selling power, and by setting variable prices for retail customers. In real time, balancing must be done through purchase of regulating services, and by remotely controlling portions of their retail customer loads and sources. We enumerate the desirable properties of a market-based balancing mechanism, and analyze the applicability of known theory in two scenarios: a baseline scenario in which brokers have no ability to manipulate their customers’ supply and demand, and a single-period scenario with controllable loads. The latter provides promising results for a scenario that takes interactions among time periods into account.Software Computer TechnologyElectrical Engineering, Mathematics and Computer Scienc

Renewable Energy for Electric Vehicles: Price Based Charging Coordination

In this paper we investigate the charging coordination of battery electric vehicles (BEV) with respect to the availability of intermittent renewable energy generation considering individual real world driving profiles in a deterministic simulation based analysis, mapping a part of the German power system in 2009. We propose a price based charging approach, initiated by an aggregator, which combines numerous BEVs in his fleet in order to optimize the utilization of energy from renewable sources, here wind and solar, thus offering a renewable tariff to consumers. Our results show that a price mechanism based on the availability of renewable energy and the charging availability of the BEVs combined with a voluntary reduction of the individual charging power to 1 kW, can increase the share of renewable energy charged in a year from 53 % to 75 % as compared to no charging coordination under similar conditions. An additional average cost evaluation of the proposed renewable energy tariff shows that wind power can be competitive with conventional sources at the end consumer level, while enabling considerable carbon emission reductions.Infrastructures, Systems and ServicesTechnology, Policy and Managemen

The Power Trading Agent Competition

This is the specification for the Power Trading Agent Competition for 2012 (Power TAC 2012). Power TAC is a competitive simulation that models a “liberalized” retail electrical energy market, where competing business entities or “brokers” offer energy services to customers through tariff contracts, and must then serve those customers by trading in a wholesale market. Brokers are challenged to maximize their profits by buying and selling energy in the wholesale and retail markets, subject to fixed costs and constraints. Costs include fees for publication and withdrawal of tariffs, and distribution fees for transporting energy to their contracted customers. Costs are also incurred whenever there is an imbalance between a broker’s total contracted energy supply and demand within a given timeslot. The simulation environment models a wholesale market, a regulated distribution utility, and a population of energy customers, situated in a real location on Earth during a specific period for which weather data is available. The wholesale market is a relatively simple call market, similar to many existing wholesale electric power markets, such as Nord Pool in Scandinavia or FERC markets in North America, but unlike the FERC markets we are modelling a single region, and therefore we do not model location-marginal pricing. Customer models include households and a variety of commercial and industrial entities, many of which have production capacity (such as solar panels or wind turbines) as well as electric vehicles. All have “real-time” metering to support allocation of their hourly supply and demand to their subscribed brokers, and all are approximate utility maximizers with respect to tariff selection, although the factors making up their utility functions may include aversion to change and complexity that can retard uptake of marginally better tariff offers. The distribution utility models the regulated natural monopoly that owns the regional distribution network, and is responsible for maintenance of its infrastructure and for real-time balancing of supply and demand. The balancing process is a market-based mechanism that uses economic incentives to encourage brokers to achieve balance within their portfolios of tariff subscribers and wholesale market positions, in the face of stochastic customer behaviors and weather-dependent renewable energy sources. The broker with the highest bank balance at the end of the simulation wins.Software Computer TechnologyElectrical Engineering, Mathematics and Computer Scienc