دانلود مقاله ISI انگلیسی شماره 16674
عنوان فارسی مقاله

عامل رقابت تجاری قدرت : شبیه سازی اقتصادی رقابتی شبکه های هوشمند

کد مقاله سال انتشار مقاله انگلیسی ترجمه فارسی تعداد کلمات
16674 2013 9 صفحه PDF سفارش دهید محاسبه نشده
خرید مقاله
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عنوان انگلیسی
Power TAC: A competitive economic simulation of the smart grid
منبع

Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)

Journal : Energy Economics, Volume 39, September 2013, Pages 262–270

کلمات کلیدی
شبیه سازی رقابتی - شبکه هوشمند - عوامل بازرگانی - بازارهای انرژی -
پیش نمایش مقاله
پیش نمایش مقاله عامل رقابت تجاری قدرت : شبیه سازی اقتصادی رقابتی شبکه های هوشمند

چکیده انگلیسی

Sustainable energy systems of the future will need more than efficient, clean, low-cost, renewable energy sources; they will also need efficient price signals that motivate sustainable energy consumption as well as a better real-time alignment of energy demand and supply. The Power Trading Agent Competition (Power TAC) is a rich competitive simulation of future retail power markets. This simulation will help us to understand the dynamics of customer and retailer decision-making and the robustness of market designs, by stimulating researchers to develop broker agents and benchmark them against each other. This will provide compelling, actionable information for policymakers and industry leaders. We describe the competition scenario in detail, and we demonstrate behaviors that arise from the interaction of customer and broker models.

مقدمه انگلیسی

Many of the sustainable energy resources (solar, wind, tidal, etc.) that could displace our dependence on fossil fuels are diffuse and do not necessarily produce power when it is needed. They are therefore difficult to integrate into our power grids and into their traditional control and capital structures. There have been many proposals to upgrade our electric power infrastructure into a “smart grid” (Amin and Wollenberg, 2005 and United States Department of Energy, 2012) with components that can monitor energy usage in real time and help consumers better manage their energy usage. However, this is only the technical foundation. There is a clear need for new market structures that motivate sustainable behaviors by all participants. Energy prices that truly reflect energy availability can motivate consumers to shift their loads to minimize cost, and more effectively utilize distributed, small-scale energy storage and production resources (Joskow and Tirole, 2006). Unfortunately, it can be difficult to introduce creative and dynamic pricing schemes when energy is produced and sold by regulated monopolies, and transitions to competitive markets can be risky (Borenstein, 2002). There is hope — energy markets are being opened to competition around the world in much the same way the telecom markets were opened in the 1990's (Lazer and Mayer-Schonberger, 2001). However, the scope of retail electric power markets is limited in the absence of smart metering infrastructure that allows a retailer to observe the consumption behavior of its customer portfolio, and where technical infrastructure does not effectively support energy storage and production in the retail (or “distribution”) domain. Any serious proposal to change the way the electric power enterprise works must address several significant challenges: Reliability: Frequency, voltage, and power factor must be closely managed to ensure safety and prevent outages. Balancing: Supply and demand must be kept in balance, through a combination of supply and demand management. Peak demand management: The need to serve peak demand that substantially exceeds steady-state demand drives investment in under-utilized supply and transmission resources. Energy efficiency: Investment in demand reduction must be balanced against investments in production capacity. Externality reduction: Production of energy has been the cause of considerable environmental degradation and resource depletion, a cost that must be borne by future generations. What is needed is a low-risk means for modeling and testing market designs and other policy options for retail power markets. We are addressing this need by organizing an open competition that will challenge participants to build autonomous, self-interested agents to compete directly with each other in a rich simulation focused on the structure and operation of retail power markets. The Power Trading Agent Competition (Power TAC) (Ketter et al., 2012b) is an example of a Trading Agent Competition1 (Wellman et al., 2007) applied to electric power markets. It addresses important elements of the smart grid challenges outlined in Ramchurn et al. (2012), since many of these challenges involve economically motivated decisions of large numbers of actors. The Power TAC simulation can be used to evaluate a range of market-based approaches to addressing the challenges we have identified. It contains realistic models of energy consumers, producers, and markets, along with environmental factors, such as weather, that affect energy production and consumption. Alternative market mechanisms and policy options can be applied to the simulation model and tested in open competitions. Research results from Power TAC will help policy makers create mechanisms that produce the intended incentives for energy producers and consumers. They will also help to develop and validate intelligent automation technologies that can support effective management of participants in these market mechanisms. The paper is organized as follows. In Section 2 we give an overview of the dominating Smart Grid challenges and related work regarding different simulation approaches. Section 3 describes the competition scenario in some detail, and Section 4 presents the simulation platform. In Section 5 we demonstrate the Power TAC platform and give an overview of pilot tournaments that took place in 2011 and 2012. We conclude with a call for participation in future Power TAC tournaments in Section 6.

نتیجه گیری انگلیسی

Our energy-dependent society must adapt itself to more sustainable sources of energy. This will require a number of changes, including new market structures that motivate sustainable behaviors on the part of energy producers and consumers. It will also require us to make effective use of diffuse, volatile sources such as small-scale solar and wind installations, as well as small-scale energy storage capabilities such as electric vehicle batteries. Competitive retail power markets have the potential to drive investment and behaviors that enhance sustainability. Power TAC is a rich competitive simulation of these future retail power markets. The competition will stimulate researchers to develop broker agents and benchmark them against each other and against the market structures embedded in the Power TAC scenario, helping us to better understand the dynamics of customer and retailer decision-making and the robustness of market designs, while providing actionable information for policymakers and industry leaders. Power TAC is designed to support a research program centered around an annual tournament, a model that has been very effective in stimulating research. Prominent examples include RoboCup (Ros et al., 2009) and TAC (Ketter and Symeonidis, 2012). Tournaments are typically held in conjunction with a relevant major conference where participants can present their work, discuss what they have learned, and begin planning for the next cycle. After a tournament, teams are encouraged to release their agent code (either binary or source), so that all teams can design and run their own experiments using a range of agent behaviors and market design details. Teams are then able to incorporate results of this research into their agent designs for the following year. Each year, the scenario may be updated to add new challenges, and if necessary to tune the market designs and level of realism, in order to enhance the relevance of the shared enterprise for both research value and policy guidance. Power TAC models power markets primarily from an economic rather than from a physical viewpoint; it does not simulate the details of the physical infrastructure. In the future, we anticipate integrating the market simulation with a physical simulation in order to be able to evaluate the technical feasibility of the market's energy allocation over time. Power TAC builds on the authors' extensive experience with the Trading Agent community and with the Trading Agent Competition for Supply Chain Management (TAC SCM) (Collins et al., 2010b). The strength of the world-wide TAC community is its individual research groups. Most are part of a university or business research organization. Due to the complexity of building a competitive autonomous agent, most groups are currently associated with Computer Science departments. Many existing teams have formed partnerships with business schools, economics departments, and electrical engineering departments. For the future, we are working on a broker framework that leverages a popular visual-programming system for building simulation models. We expect this will lower the barrier of entry for teams outside the computer science community. Three Power TAC tournaments were held in 2012, to test and validate all components of the Power TAC platform. The “official” tournament for 2013 will be held in July in conjunction with the AAAI-2013 conference in Bellevue, Washington, USA. Other tournaments may be run if participants request them. Further information, including a detailed specification and development resources are available at http://www.powertac.org.

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