Iranian Journal of Electrical and Electronic Engineering

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Electric power restructuring offers a major change to the vertically integrated monopoly. The change manifests the main part of engineers’ efforts to reshape the three components of today’s vertically integrated monopoly: generation, distribution and transmission. In a restructured environment, the main tasks of these three components will remain the same as before, however, to comply with FERC orders, new types of unbundling, coordination and rules are to be established to guarantee competition and non-discriminatory open access to all users. This paper provides the generation schedule of a GENCO in a deregulated power system. It is shown that the goal of generation schedule in the new structure is different from the traditional centralized power systems. The modeling of generation scheduling problem in a competitive environment is demonstrated by taking into account the main purposes of GENCOs which are selling electricity as much as possible and making higher profit. The GENCOs of an area are introduced via a model whose objective function consists of hourly spot market price as income and different kinds of costs. The constraints are the general ones of such a problem e.g. minimum up/down time, minimum and maximum generation and ramp rate. Using one of the classical optimization methods, the hourly generation schedule of the generating units will be obtained in this competitive environment. The results of this section will be used by ISO. The ISO will finalize the schedules of GENCOs by taking into account the technical considerations like the power flow of transmission lines. The model and the optimization methods are implemented on IEEE-RTS benchmark with 24 buses and 32 generating units.

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This paper proposes a novel approach for generation scheduling using sensitivity

characteristic of a Security Analyzer Neural Network (SANN) for improving static security

of power system. In this paper, the potential overloading at the post contingency steadystate

associated with each line outage is proposed as a security index which is used for

evaluation and enhancement of system static security. A multilayer feed forward neural

network is trained as SANN for both evaluation and enhancement of system security. The

input of SANN is load/generation pattern. By using sensitivity characteristic of SANN,

sensitivity of security indices with respect to generation pattern is used as a guide line for

generation rescheduling aimed to enhance security. Economic characteristic of generation

pattern is also considered in the process of rescheduling to find an optimum generation

pattern satisfying both security and economic aspects of power system. One interesting

feature of the proposed approach is its ability for flexible handling of system security into

generation rescheduling and compromising with the economic feature with any degree of

coordination. By using SANN, several generation patterns with different level of security

and cost could be evaluated which constitute the Pareto solution of the multi-objective

problem. A compromised generation pattern could be found from Pareto solution with any

degree of coordination between security and cost. The effectiveness of the proposed

approach is studied on the IEEE 30 bus system with promising results.