Optimal Power Flow Constraints Research Articles

系統評価のための停止ランキングに基づく電源起動停止計画手法

This paper presents a practical algorithm for solving Unit Commitment (UC) problems with network constraints represented in Optimal Power Flow (OPF). The proposed algorithm is based on Successive Approximation Dynamic Programming (SADP) according to a Unit Decommitment Ranking (UDR) which is a priority list for unit decommitment procedure. The UDR can be determined by Dynamic Programming (DP) according to the information of OPF consisting of a set of Lagrange multipliers (dual variables). Since the set of Lagrange multipliers represents the relationship between the optimal value of objective function and OPF constraints, the proposed algorithm can determine power system resource scheduling in consideration of network constraints, such as line flow and voltage constraints. The feasibility and effectiveness of the proposed algorithm are demonstrated on a modified IEEE Reliability Test System. © 2001 Scripta Technica, Electr Eng Jpn, 138(2): 1–13, 2002

Cyclic security analysis for security constrained optimal power flow

The security of a power system may be enhanced by supplementing an optimal power flow model with a N-1 security rule (respect of voltage and power flow limits after any single line or generating unit outage). Including a security analysis in the optimal power flow model, a security constraints optimal power flow model is obtained. This paper deals with the application of a new contingency screening model to speed-up the security constrained optimal power flow (SCOPF), which makes possible the on-line applications. The SCOPF resolution process is an iterative one. A cyclic contingency selection model is designed in order to take advantage of the specific characteristics of the optimal power flow problem, such as the lower variations of the control variables between the SCOPF iterations. The cyclic security approach takes the results of a security analysis carried out at time t/sub k/ and extracts data for use by another security analysis at time t/sub k/+/spl Delta/t in order to reduce the computational burden. Tests performed show that the inclusion in the OPF of the proposed cyclic security procedure efficiently produces more secure conditions against critical contingencies and considerably speeds up the security constraint optimal power flow.

A practical resource scheduling with OPF constraints

This paper presents an efficient approach to short term power system resource scheduling based on the augmented Lagrangian relaxation method. The problem is divided into two stages, the commitment stage and the constrained economic dispatch stage. The proposed mathematical model incorporates optimal power flow (OPF) constraints in the unit commitment stage. By OPF constrains, the authors refer to the relevant active power constraints that are incorporated in the constrained economic dispatch stage (i.e. transmission capacity constraints, fuel and various regulated emission requirements). The inclusion of OPF constraints in the commitment stage will improve the feasibility of the constrained economic dispatch solution. Other unit commitment constraints such as spinning and operating reserve requirements, power balance as well as other relevant local constraints (i.e. unit ramping rates, upper and lower generation limits, minimum up and down times) are taken into account in the proposed model. As a larger number of constraints are dealt with, a more rigorous method is introduced for updating Lagrange multipliers to improve the solution convergence. A software package which addresses energy management systems requirements is developed and tested.

Enhanced Newton-Raphson algorithm for normal, controlled and optimal powerflow solutions using column exchange techniques

A column exchange approach for powerflow (PF) problems is presented, in which various functional Jacobian matrices are obtained from a new basic formulation. Transformations between these matrices are described, which allow simple and flexible algorithms to be programmed. An enhanced version of the partitioned Newton-Raphson algorithm for normal, controlled and optimal PF yielded by the new approach is also presented. The new approach is shown to be much more powerful than the standard method. In addition to the calculation of normal PF solutions, the new algorithm can conveniently and efficiently model simple control activities, such as generator VAr limits, load-tap-changing transformers and variable phase shifting transformers. Complex control activities, such as control of remote variables or nonstandard system controls, as well as the calculation of sensitivity vectors for both objective functions and system constraints in optimal PF (OFF) can also be handled efficiently. Even when generator VAr limits, LTC transformers and transformer tap limits are included, the new algorithm still exhibits quadratic convergence. Computational efficiency is much greater than the traditional Newton-Raphson implementation (about seven times faster for practical UK systems) and is comparable with the fast decoupled loadflow (FDLF). The algorithm is also very reliable for systems with either meshed or radial configurations, including ill-conditioned networks.

New modelling, analysis and computation techniques needed for power system control centres

In this paper the new modelling, analysis and computation techniques needed in the coming generation of electric power system control centres are outlined. The motivation is to provide better utilization of the power system. This means better economy, which requires more elaborate optimization, with acceptable security, which requires more accurate analysis of the system behaviour. At present, the optimization available is advancing from not considering system limits (economic dispatch) to taking into account the steady-state constraints (optimal power flow), while analysing the system is limited to its steady-state behaviour (static security analysis). The addition of dynamic analysis (transient, small perturbation, and voltage stabilities) is desperately needed but remains a challenge. The calculation of these security limits and their reflection into the optimization are also significant challenges. The effects of the coming deregulatory operational environment further adds to the optimization complexity.

Quasi-Newton method for optimal power flows

A prototype procedure for solving the optimal power flow problem with a quasi-Newton (variable metric) method is described. The method was developed by Powell and later extended by Berna, Locke and Westerberg. It is attractive for three reasons. First, it can accommodate optimal power flow constraints in a straightforward manner. Second, it is robust and will home in on a solution even from infeasible starting points. Third, it promises to be very fast. The adaptation of the method to the optimal power flow is discussed and illustrated with the results from tests on two small power systems.