This thesis presents a new way of combining non-linear optimization algorithms and electromagnetic transient (EMT) simulation. In this new combination, a non-linear optimization algorithm utilizes a real-time EMT simulation environment as objective function evaluator. However, as more applications of the off-line EMT simulation software implementation were made, the combination between non-linear optimization algorithms and off-line EMT simulation software revealed new need, which this research work attempts to address.
The first need arose from the speed of simulation of the off-line EMT simulation software. With a certain breed of non-linear optimization algorithms, heuristics bases algorithms in particular, a large number of objective function evaluations are required before the termination or convergence criterion in the selected algorithms is satisfied. Sometimes, the number of evaluations as well as the complexity of the simulation case where the objective function is based upon translates into a very long simulation time, which goes beyond the boundary of given resources. This research work attempts to address this simulation timing issue by capitalizing on the real timeness of the simulation environment as well as utilizing the multiple instances of the simulation environment in parallel.
The second need arose from the modeling requirement of the off-line EMT simulation software. In order to properly design the necessary objective function evaluator, which is largely a simulation case, a large amount of information needs to be embedded into the case. Under certain circumstances, the necessary information would not be available. Therefore, the simulation case needs to include approximations which may cause compromise in the end result. This limitation becomes more obvious when a real world device such as a commercial controller becomes involved. On the contrary, this limitation can be addressed by the real-time simulation environment because this environment can be directly interfaced with the real world device. In this way, the need for detailed information regarding the device is eliminated. This elimination would enlarge the application of the combination, between the non-linear optimization algorithm and EMT type simulation environment.
The effectiveness of the proposed approach is demonstrated by various examples throughout this thesis.
Identifer | oai:union.ndltd.org:MANITOBA/oai:mspace.lib.umanitoba.ca:1993/8912 |
Date | 21 September 2012 |
Creators | Park, In Kwon |
Contributors | Aniruddha, Gole (Electrical and Computer Engineering), Shaahin, Filizadeh (Electrical and Computer Engineering) Peter, Graham (Computer Science) Venkata, Dinavahi (University of Alberta) |
Source Sets | University of Manitoba Canada |
Detected Language | English |
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