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This paper applies basic economic principles which have been developed in financial markets to a future smart grid scenario. Our method allows for autonomous bidding for electricity units to create an emerging market price for electricity. We start with replicating the popular Zero-Intelligence-Plus algorithm and setting it in a electricity supplier-consumer scenario. We identify significant weaknesses of applying this in an electricity market especially when intermittent sources of energy are present or when the supplier to consumer ratio is very small. A new algorithm (ZIP-260) is proposed which includes a measure of fairness based on minimising the deviation across all un-matched demand for a given period. This approach means that no consumer in the system is constantly experiencing an electricity supply deficit. We show and explain how market conditions can lead to collective bargaining of consumers and monopolistic behaviour of suppliers and conclude with observations on automated trading for smart grids. © IFIP International Federation for Information Processing 2014.
Laffoy, B., Dave, S., & Sooriyabandara, M. (2014). Automated trading for smart grids: Can it work? In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8221 LNCS, pp. 1–13). Springer Verlag. https://doi.org/10.1007/978-3-642-54140-7_1