Stochastic multi-objective congestion management in power markets improving voltage and transient stabilities

Abstract

Congestion management is traditionally done using deterministic values of power system parameters. After relieving congestion using conventional methods, the network may be operated with a low voltage or transient stability margin because of hitting security limits. In this paper, a stochastic multi-objective framework considering power system uncertainties is proposed to enhance voltage and transient stabilities after congestion management. The uncertainty sources incorporate contingencies of generating units and branches. The proposed multi-objective framework simultaneously optimizes competing objective functions of congestion management cost, voltage security, and dynamic security under a stochastic framework. The proposed framework not only captures a more uncertainty spectrum of the power system compared with deterministic methods, but also establishes a sufficient level of voltage and dynamic security after congestion management. Results of testing the proposed framework and previous congestion management methods on the New-England power system, discussed in detail, elaborate the efficiency of the proposed framework.

Placement of minimum distributed generation units observing power losses and voltage stability with network constraints

“…We can enhance VSM by managing where and how much DG units are being installed. VSM is indeed a function of active and reactive powers injected into or absorbed from buses [21]. In our application of DG placement here, VSM can be altered by active and reactive powers injected/absorbed by DGs at their installed nodes.…”

“…The linearity of VSM can be investigated by increasing load level at each bus individually and then by observing VSM variation. In fact, VSM is tightly related to voltage of buses along P-V curve because of larger sensitivities in the (Q-V) Jacobian sub-matrix [21]. That is www.ietdl.org bus voltages are more sensitive to their reactive powers than active powers.…”

Social welfare maximization for congestion management in multiutility market using improved PSO incorporating transmission loss cost allocation

“…The expression (34) can be used as sensitivity information by the ISO. After applying the steps described in Esmaili et al, 20 the following relations are obtained:…”

“…17,18 The methods used for congestion management depend on the form of market. [19][20][21][22] In multiutility markets, the centralized decision to mitigate congestion affects the economic welfare of some of the participants who are not responsible for the congestion. This may cause dissatisfaction among such participants resulting in dispute during market operation.…”

Chance‐constrained programming approach to stochastic congestion management considering system uncertainties

“…These uncertainties may be related to different sections of the power system, including generation, transmission and distribution [8]. Incorporation of the uncertainties in the CM models and algorithms can seriously improve the feasibility of the resultant operating point and improve the power system security level [9]. As an example, in Esmaili et al [10], proposed a stochastic CM technique using a scenario‐based approach.…”