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

N.M. Bhandari, G.M. Burt, K. Dahal, S.J. Galloway, J.R. McDonald

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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.
LanguageEnglish
Number of pages22
JournalInternational Journal of Emerging Electric Power Systems
Volume8
Issue number3
DOIs
Publication statusPublished - 28 Aug 2007

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Genetic algorithms
Profitability
Economics
Fossil fuels
Industry
Electricity
Power markets
Uncertainty

Keywords

  • renewable energy
  • energy generation
  • market trading

Cite this

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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.",
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AU - Burt, G.M.

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AU - McDonald, J.R.

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N2 - 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.

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