Abstract
It is a well known phenomena that some combinations of load and generation patterns can lead to system stability, and hence system security issues. This type of problem is generally alleviated by altering the generation pattern, since the utility has no, or only limited, control of the load pattern. In deregulated markets, this necessary operational function can incur costs, which is undesirable for the system operators. An alternative to changing generation pattern by imposing real power constraints is to attempt to modify the dynamic performance of the system to improve stability at its given (most economic or ideal) load and generation configuration. This paper details such a method of optimisation based on a genetic algorithm (GA) to manipulate system control plant parameters. The objective function used is based on time domain simulation of the system in order to retain full modelling detail, and the controllable parameters are based on existing controllers found within the UK system. In cases where adequate stability cannot be attained by controller parameter optimisation alone, a hybrid solution is found with a minimal level of real power constraint
Original language | English |
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Pages | 499-503 vol.2 |
Publication status | Published - 2001 |
Event | Power Engineering Society Winter Meeting, 2001. IEEE - Duration: 1 Jan 2001 → … |
Conference
Conference | Power Engineering Society Winter Meeting, 2001. IEEE |
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Period | 1/01/01 → … |
Keywords
- electric utility
- power system control
- genetic algorithms
- genetic algorithm
- time domain simulation
- controllable parameters
- optimal control
- dynamic performance
- power system economics
- objective function
- UK
- control simulation
- control system analysis
- power system stability improvement
- power system stability
- power constraints coordination
- power system economy improvement
- controller settings coordination
- control design
- deregulated markets
- control system synthesis
- load pattern
- generation pattern