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CASCADE: An Agent Based Framework For Modeling The Dynamics Of Smart Electricity Systems

Rylatt, M., Gammon, R., Boait, P. J., Varga, L., Allen, P., Savill, M., Snape, R., Lemon, M., Ardestani, B., Pakka, V., Fletcher, G., Smith, S., Fan, D. and Strathern, M. (2013) CASCADE: An Agent Based Framework For Modeling The Dynamics Of Smart Electricity Systems. Emergence: Complexity and Organization, 15 (2). pp. 1-13. ISSN 1521-3250 (Special Issue: Complexity and the Smart Electricity Grid)

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The Complex Adaptive Systems, Cognitive Agents and Distributed Energy (CASCADE) project is developing a framework based on Agent Based Modelling (ABM). The CASCADE Framework can be used both to gain policy and industry relevant insights into the smart grid concept itself and as a platform to design and test distributed ICT solutions for smart grid based business entities. ABM is used to capture the behaviors of diff erent social, economic and technical actors, which may be defi ned at various levels of abstraction. It is applied to understanding their interactions and can be adapted to include learning processes and emergent patterns. CASCADE models ‘prosumer’ agents (i.e., producers and/or consumers of energy) and ‘aggregator’ agents (e.g., traders of energy in both wholesale and retail markets) at various scales, from large generators and Energy Service Companies down to individual people and devices. The CASCADE Framework is formed of three main subdivisions that link models of electricity supply and demand, the electricity market and power fl ow. It can also model the variability of renewable energy generation caused by the weather, which is an important issue for grid balancing and the profi tability of energy suppliers. The development of CASCADE has already yielded some interesting early fi ndings, demonstrating that it is possible for a mediating agent (aggregator) to achieve stable demandfl attening across groups of domestic households fi tted with smart energy control and communication devices, where direct wholesale price signals had previously been found to produce characteristic complex system instability. In another example, it has demonstrated how large changes in supply mix can be caused even by small changes in demand profi le. Ongoing and planned refi nements to the Framework will support investigation of demand response at various scales, the integration of the power sector with transport and heat sectors, novel technology adoption and diffusion work, evolution of new smart grid business models, and complex power grid engineering and market interactions.

Item Type:Article
Divisions:Interdisciplinary centres and themes > Energy Research
Science > School of the Built Environment > Energy and Environmental Engineering group
ID Code:35830
Publisher:Emergent Publications

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