Optimisation methods applied to compensator placement

[摘要] ENGLISH ABSTRACT: The optimal placement of different types of compensators on electrical networks is a complextask faced by network planners and operations engineers. The successful placement of thesedevices normally involves a large number of power flow studies and relies heavily on theexperience of the engineer. Firstly the operation and application of the different types ofcompensators must be clearly understood. Secondly the application of combinations ofdifferent compensators on a specific network must be investigated. Then the dynamics of thenetwork and interaction between the network and the compensator/s must be studied under awide variety of network conditions and load levels. This task is further complicated by thenon-linear nature of the mathematical equations that govern the power flow and voltagedistribution on an electrical network. Yet another complication is the fact that some of thevariables that describe an electrical network can be non smooth or discrete. For instance, thediscrete value of a tap position of a power transformer can only assume an integer value. Tosimplify the problem of compensator placement, advanced software tools are available thatare capable of solving power flows of networks containing compensators. To a large degree,however, these tools still rely on the user to make intelligent decisions as to the configurationof networks and the placement of compensators. In many cases trial and error is the only wayto find a good solution.The purpose of this thesis is to show the different techniques available to implementintelligent algorithms capable of finding optimal solutions specific to the placement of voltageregulators. State of the art algorithms are implemented in Matlab that can place voltageregulators on sub transmission, reticulation and low voltage networks. The sub transmissionand reticulation placement algorithm is a combination of an SQP technique and a simplecombinatorial algorithm. The low voltage placement program is based on a simple geneticalgorithm with a few customized features that has been developed to ensure fast convergence.The programs developed were used to do optimal voltage regulator placement on a number ofnetworks. As far as possible real world networks were used. Where real world networkswere not available test networks were used that closely resemble real networks, as they existon typical networks owned by Eskom Distribution.It was found that SQP is a very efficient algorithm for optimising large non-linear problemssuch as the placement of a Step Voltage Regulator on a large electrical network. Thisalgorithm however does not handle discrete variables very well and is also limited in handlingany reconfiguration of the network due to the placement of series devices such as voltageregulators. To cater for reconfiguration, it is necessary to combine the SQP algorithm with acombinatorial algorithm.The genetic algorithm used to do optimal placement of multiple Electronic VoltageRegulators on low voltage networks was found to be very efficient and robust. This can beattributed to the simplicity of the algorithm as well as the fact that it does not rely on theavailability of derivative and second derivative information to move towards an optimalsolution. Instead, it only uses fitness values obtained from function evaluations to optimisethe placement problem. Another useful feature of using a genetic algorithm is that thealgorithm does not get stuck in sub optimal areas in the solution space. Both the placementprograms developed are relatively simple and do not consider all the factors involved in theplacement of voltage regulators. However, the addition of any number of factors is howeverpossible with further development of the programs as presented in this thesis.

[发布机构] Stellenbosch University