4.7 Article

A Decision-Making Framework and Simulator for Sustainable Electric Energy Systems

Journal

IEEE TRANSACTIONS ON SUSTAINABLE ENERGY
Volume 2, Issue 1, Pages 37-49

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TSTE.2010.2074217

Keywords

Adaptive sustainability; future electric energy systems; just-in-context (JIC) services; just-in-place (JIP) services; just-in-time (JIT) services; price-responsive demand; renewable resources

Funding

  1. Delft University of Technology
  2. Bosch
  3. U.S. National Science Foundation ITR Project [CNS0428404]
  4. Carnegie Mellon-Portugal Program through Information and Communications Technology Institute (ICTI) at Carnegie Mellon

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In this paper, we propose a new framework for the organization of the electric power industry, based on extensive use of information technology (IT) and on interactive decision making, where consumers and distributed producers join the traditional actors, utilities in particular, in making decisions. While many ideas considered in this paper have been put forward in recent years, such as the need to manage intermittency of renewable resources by means of proactive forecasting, and coordination with responsive demand and storage, we introduce a possible systematic IT-enabled mechanism necessary for the actual implementation of these technologies. We point out that in order to achieve a long-term sustainable energy utilization, it is essential to provide on-line information to internalize the value of just-in-time, just-in-place, and just-in-context distributed adaptation across the entire supply chain, ranging from the smallest consumers and energy providers, through their aggregators and system coordinators. We illustrate using our model-based novel simulator, how a carefully designed multidirectional and multi-temporal information exchange could enable sustainable decision making while accounting for unique needs and capabilities of various resources and users. At the same time, information incentivizes the resources and users to contribute to system-wide sustainability objectives at value. We illustrate the dependence of such decisions-driven industry evolution on the industry rules (choice of performance objectives), as well as on the operating and planning practices for implementing the industry rules (temporal and spatial factors). Our model-based simulator could be used as a means of designing novel regulation defining rules, rights, and responsibilities regarding the type and rate of information to be exchanged in support of sustainable industry evolution.

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