Research On Available Transfer Capability Considering Uncertianties

As an index for describing the available capability of network, Available Transfer Capability (ATC) is an important reference for market participators to make decisions, as well as a judgment for system operators to alleviate transmission congestion, and an important reference for system planning and expansion. The electric power utilities have been undergoing rapid changes. In new environment, open access to transmission network, uncertainties involved in trading and power flow, are commonly recognized. The market participators will maximize the profits to make the network operate in an extreme condition. In order to evaluate the transfer capability of network, find the weakness and improve the transfer capability of the network, ATC calculation and evaluation should be quick and correct in new market environment.Considering the dynamic, uncertainties and time-varying nature of the power system, a novel method is proposed to calculate continuous ATC based on Markov chain and contingency selection. Markov chain has the ability describing large amount of uncertainties, and forecasting the future states of power systems based on the initial state and transition probability. The continuous ATC curve can be obtained through the contingency selection and probability method. IEEE 14-bus test system is used to verify the presented approach. The results show that the model and algorithm is correct and effective and could be a more effective method to give more accurate information of network operation and guide power transactions.ATC is varying with time and space, so the probabilistic method is suitable for ATC evaluation. A series of ATC probabilistic indices are proposed to evaluate ATC considering the impacts of the uncertainties and time-varying. Both unsequential and sequential Monte Carlo simulation methods are proposed to calculate the ATC probabilistic indices to the long time transfer capability assessment of the network. The case study results show that the model and algorithm could be a more effective method to power system's operation, planning and expansion.According to the definition of ATC, ATC not only depends on the topology of power network but also on the parameters of components. Through thorough analyses on ATC probabilistic indices, the sensitivities of components parameters to these indices are deduced. The impact of components parameters'small variations on ATC can be reflected by these sensitivities, the importance degree of each component can be embodied. Furthermore, by sensitivity analysis we can effectively identify ATC bottlenecks and get important guide information for investment decision-making and maintenance.Demand Side Management (DSM) is now an important consideration for electric power utilities. Enhancing the DSM activities could help not only the system operate more efficiently, but also benefit the system ATC. An integrated framework for evaluating impacts of DSM on ATC is presented. A set of load management models for peak clipping/shifting and valley filling, strategic conservation and strategic load growth are presented. To investigate the impacts of DSM actions in different areas on ATC, the sensitivity analysis is adopted to guiding the key areas of implementing DSM.