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The Strathprints institutional repository is a digital archive of University of Strathclyde research outputs.

Strathprints serves world leading Open Access research by the University of Strathclyde, including research by the Strathclyde Institute of Pharmacy and Biomedical Sciences (SIPBS), where research centres such as the Industrial Biotechnology Innovation Centre (IBioIC), the Cancer Research UK Formulation Unit, SeaBioTech and the Centre for Biophotonics are based.

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Dispatch optimisation of renewable energy generation participating in a liberalised electricity market

Bhandari, N.M. and Burt, G.M. and Dahal, K. and Galloway, S.J. and McDonald, J.R. (2007) Dispatch optimisation of renewable energy generation participating in a liberalised electricity market. International Journal of Emerging Electric Power Systems, 8 (3). ISSN 1553-779X

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Abstract

This paper focuses on dispatching of mixed generation portfolio of renewable energy (RE) and non-RE (firm) units. A genetic algorithm (GA) based rolling window approach is developed for solving economic dispatch (ED) problem. Profit maximisation ED problem is formulated and solved which also considers New Electricity Trading Arrangements for England and Wales (NETA) market features. In this problem, a penalty approach is used in order to consider intermittency problem of RE generation output. A single GA technique is also applied for solving the formulated problem. Of these, GA based rolling window approach achieved promising results for a Generator Company, which holds both renewable and fossil fuel units and participates in the short-term market trading. It is also shown that a Generator Company can get more profit by using the possibility of increase in generation output of RE sources from their forecast positions by combining both RE and non-RE units and participating in a NETA-like market trading. This approach allows to some extent the management of uncertainty problem of RE generation output, which also accounts risk associated with power non-delivery.