Conference paper
Day-Ahead Self-Scheduling of Thermal Generator in Competitive Electricity Market Using Hybrid PSO
This paper presents a hybrid particle swarm optimization algorithm (HPSO) to solve the day-ahead selfscheduling for thermal power producer in competitive electricity market. The objective functions considered to model the selfscheduling problem are: 1) to maximize the profit from selling energy in day-ahead energy market subject to operational constraints and 2) at the same time, to minimize the risk due to uncertainty in price forecast.
Therefore, it is a conflicting biobjective optimization problem which has both binary and continuous optimization variables considered as constrained mixed integer nonlinear programming. To demonstrate the effectiveness of the proposed method for self-scheduling in a dayahead energy market, the locational margin price (LMP) forecast uncertainty in PJM electricity market is considered.
An adaptive wavelet neural network (AWNN) is used to forecast the dayahead LMPs. The effect of risk is explicitly modeled by taking into account the estimated variance of the day-ahead LMPs.
| Language: | English |
|---|---|
| Publisher: | IEEE |
| Year: | 2009 |
| Pages: | 1-6 |
| Proceedings: | International Conference on Intelligent System Applications to Power Systems |
| ISBN: | 1424450977 , 1424450985 , 1509070141 , 9781424450978 , 9781424450985 and 9781509070145 |
| Types: | Conference paper |
| DOI: | 10.1109/ISAP.2009.5352896 |
| ORCIDs: | Østergaard, Jacob |
Day-ahead self-scheduling Electricity market. Hybrid particle swarm optimization, LMP forecast,
Adaptive systems Constraint optimization Economic forecasting Electricity market Electricity supply industry Hybrid particle swarm optimization Hybrid power systems LMP forecast Load forecasting Particle swarm optimization Power generation Predictive models Uncertainty adaptive wavelet neural network day-ahead self-scheduling electricity market energy market hybrid particle swarm optimization algorithm locational margin price forecast uncertainty particle swarm optimisation power markets pricing thermal generator thermal power producer thermal power stations
