Showing papers by "Chen-Ching Liu published in 2004"

Coherency and aggregation techniques incorporating rotor and voltage dynamics

Abstract: Dynamic equivalents have been widely used to reduce computational efforts when a large number of scenarios have to be studied to evaluate the stability of interconnected power systems. Most coherency methods developed for model reduction do not consider the effect of voltage variations on the coherency of generators due to weak coupling between real power and voltage. In reality, however, the coherency of generators can be influenced by voltage related factors such as location and speed of AVR controls, generator terminal voltage variation, and load bus voltage variation. The reduced dynamic equivalent is not accurate if the voltage characteristics of the original system are not included in the model. This paper presents coherency identification techniques incorporating rotor and voltage dynamics in order to improve the accuracy of dynamic equivalents. This paper also presents a new method to match the power flow conditions for generator aggregation. This new technique is shown to be critical for the accuracy of aggregated dynamic models. Numerical results based on the model of an actual power system in Asia are presented to demonstrate the performance of the proposed method.

Optimization techniques for Available Transfer Capability (ATC) and market calculations

Abstract: The recent movement towards an open, competitive market environment introduced new optimization problems such as market clearing mechanism, bidding decision and Available Transfer Capability (ATC) calculation. These optimization problems are characterized by the complexity of power systems and the uncertainties in the electricity market. Accurate evaluation of the transfer capability of a transmission system is required to maximize the utilization of the existing transmission systems in a competitive market environment. The transfer capability of the transmission networks can be limited by various system constraints such as thermal, voltage and stability limits. The ability to incorporate such limits into the optimization problem is a challenge in the ATC calculation from an engineering point of view. In the competitive market environment, a power supplier needs to find an optimal strategy that maximizes its own profits under various uncertainties such as electricity prices and load. On the other hand, an efficient market clearing mechanism is needed to increase the social welfare, i.e. the sum of the consumers’ and producers’ surplus. The need to maximize the social welfare subject to system operational constraints is also a major challenge from a societal point of view. This paper presents new optimization techniques motivated by the competitive electricity market environment. Numerical simulation results are presented to demonstrate the performance of the proposed optimization techniques.

Topology error identification for the NEPTUNE power system using an artificial neural network

Abstract: The goal of the North Eastern Pacific Time-Series Undersea Networked Experiment (NEPTUNE) is to construct a cabled observatory on the floor of the Pacific Ocean, encompassing the Juan de Fuca Tectonic Plate. The power system associated with the proposed observatory is unlike conventional terrestrial power systems in many ways due to the unique operating conditions of cabled observatories. The unique operating conditions of the system require hardware and software applications that are not found in terrestrial power systems. This paper builds upon earlier work and describes a method for topology error identification in the NEPTUNE system that utilizes an artificial neural network (ANN) to determine single contingency topology errors.