@article{zhu_bilbro_chow_1999, title={Phase balancing using simulated annealing}, volume={14}, ISSN={["0885-8950"]}, DOI={10.1109/59.801943}, abstractNote={Deregulation eliminates the boundary of the territory of the monopoly power industry. Competition forces utilities to improve power quality as well as to reduce investment and operation costs. Feeder imbalance describes a situation in which the voltages of a three-phase voltage source are not identical in magnitude, or the phase differences between them are not 120 electrical degrees, or both. It affects motors and other devices that depend upon a well-balanced three-phase voltage source. Phase balancing is to make the voltages balanced at each load point of the feeder. Phase swapping is a direct approach for phase balancing with the minimum cost. Phase balancing can enhance utilities' competitive capability by improving reliability, quality, and reducing costs. Therefore, phase balancing optimization is nowadays receiving more attention in the power industry, especially in today's deregulating environments. The nonlinear effects, such as, voltage drops and energy losses, make the problem difficult to solve. This paper introduces simulated annealing as an effective method to solve a power distribution phase balancing problem with its nonlinear effects.}, number={4}, journal={IEEE TRANSACTIONS ON POWER SYSTEMS}, author={Zhu, JX and Bilbro, G and Chow, MY}, year={1999}, month={Nov}, pages={1508–1513} }
 @article{chow_zhu_tram_1998, title={Application of fuzzy multi-objective decision making in spatial load forecasting}, volume={13}, ISSN={["0885-8950"]}, DOI={10.1109/59.709118}, abstractNote={Electric distribution system planning is to provide an economic expansion plan to meet the future demands in its territory. A forecast of the future electric demand and its geographic distribution is a prerequisite for distribution planning. The quality and accuracy of this forecast have a large influence on the quality of the electrical distribution system planning. Spatial load forecasting emerges to provide a more accurate prediction of both the magnitudes and locations of future electric loads. Since the load growth pattern is dominated by its land-use (residential, commercial, or industrial), the land usage study of small area is important to capture the future loads accurately. There are many factors which will affect the customer land-use decision, for example, distance to highway, distance to urban pole, and the costs. The customer's preferences can be estimated based on these objective factors. Then the land utilization and the electricity consumption can be estimated. Since the objectives sometimes are conflicting with each other, it can be cumbersome to use conventional cost function approach to determine the land usage decision. This paper applies a fuzzy multi-objective decision making scheme to the urban redevelopment and spatial load forecasting, which is more naturally and straight forwardly used to handle the spatial load forecasting problem. An example is used to illustrate the proposed methodology.}, number={3}, journal={IEEE TRANSACTIONS ON POWER SYSTEMS}, author={Chow, MY and Zhu, JX and Tram, H}, year={1998}, month={Aug}, pages={1185–1190} }
 @article{zhu_chow_zhang_1998, title={Phase balancing using mixed-integer programming}, volume={13}, DOI={10.1109/59.736295}, abstractNote={Unbalanced feeder systems cause deteriorating power quality and increase investment and operating costs. Feeder reconfiguration and phase swapping are two popular methods to balance the systems. For an unbalanced feeder system, feeder reconfiguration is difficult to meet the phase balancing criterion due to the limited number of sectionalizing switches available. Phase swapping is another alternative and direct approach for phase balancing. Phase swapping has not received its deserved attention due to the complexity of feeder systems, the dimension of problems, and totally overlooking the impacts of phase imbalance. Phase swapping can economically and effectively balance the feeder systems to improve power quality and reduce power system total cost. Deregulation arises competition on power quality, service reliability and electricity price. Therefore phase swapping can enhance a utilities' competitive capability. This paper proposes a mixed-integer programming formulation for phase swapping optimization. Single-phase loads are treated differently to three-phase loads. Nodal phase swapping and lateral phase swapping are also introduced. An example is used to illustrate the proposed method.}, number={4}, journal={IEEE Transactions on Power Systems}, author={Zhu, J. and Chow, M. Y. and Zhang, F.}, year={1998}, pages={1487–1492} }
 @article{zhu_chow_1997, title={A review of emerging techniques on generation expansion planning}, volume={12}, ISSN={["0885-8950"]}, DOI={10.1109/59.627882}, abstractNote={Power system generation expansion planning is a challenging problem due to the large-scale, long-term, nonlinear and discrete nature of generation unit size. Since the computation revolution, several emerging techniques have been proposed to solve large scale optimization problems. Many of these techniques have been reported as used in generation expansion planning. This paper describes these emerging optimization techniques (including expert systems, fuzzy logic, neural networks, analytic hierarchy process, network flow, decomposition method, simulated annealing and genetic algorithms) and their potential usage in solving the challenging generation expansion planning in future competitive environments in the power industry. This paper provides useful information and resources for future generation expansion planning.}, number={4}, journal={IEEE TRANSACTIONS ON POWER SYSTEMS}, author={Zhu, JX and Chow, MY}, year={1997}, month={Nov}, pages={1722–1728} }