Global analysis of the power system markets shows that the Automatic Generation Control (AGC) is one of the most profitable ancillary services at these systems. This service is related to the short-term balance of energy and frequency of...
moreGlobal analysis of the power system markets shows that the Automatic Generation Control (AGC) is one of the most profitable ancillary services at these systems. This service is related to the short-term balance of energy and frequency of the power systems and acquires a principal role to enable power exchange and to provide better condition for electricity trading. The main goal of AGC problem is to maintain zero steady state errors for frequency deviation and good tracking load demands in a multi-area power system. This paper provides an overview of control strategies, as well as their current use in the field of AGC problem. The history of control strategies is outlined. Various control methodologies based on the classical and optimal control, robust, adaptive, self tuning control, variable structure controller systems, digital and artificial intelligent/soft computing control techniques are discussed. We make various comparisons between these approaches and the main advantages an...
... on Evolutionary Computation, Vol. 6, No. 1, pp. 58–73, 2002. [20] KW Chau, “Application of a PSO-based neural network in analysis of outcomes of constructionclaims”, Automation in Construction, Vol. 16, pp. 642–646, 2007. ...
... genetic algorithms (GA), evolutionary programming, tabu search, simulated annealing and rulebased bacteria foraging [11], [12 ... A novel chaotic approach is proposed here based on the Lozi map. ... two main steps: firstly mapping...
more... genetic algorithms (GA), evolutionary programming, tabu search, simulated annealing and rulebased bacteria foraging [11], [12 ... A novel chaotic approach is proposed here based on the Lozi map. ... two main steps: firstly mapping from the chaotic space to the solution space, and ...
ABSTRACT - The artificial neural network (ANN) technique for short term load forecasting (STLF) has been proposed by several authors, and gained a lot of attention recently. In order to evaluate ANN as a viable technique for STLF, one has...
moreABSTRACT - The artificial neural network (ANN) technique for short term load forecasting (STLF) has been proposed by several authors, and gained a lot of attention recently. In order to evaluate ANN as a viable technique for STLF, one has to evaluate the performance of ...
On the basis of the linearized Phillips–Herffron model of a single machine power system, we design optimally the unified power flow controller (UPFC) based damping controller in order to enhance power system low frequency oscillations....
moreOn the basis of the linearized Phillips–Herffron model of a single machine power system, we design optimally the unified power flow controller (UPFC) based damping controller in order to enhance power system low frequency oscillations. The problem of robustly UPFC based damping controller is formulated as an optimization problem according to the time domain-based objective function which is solved using
... genetic algorithms (GA), evolutionary programming, tabu search, simulated annealing and rulebased bacteria foraging [11], [12 ... A novel chaotic approach is proposed here based on the Lozi map. ... two main steps: firstly mapping...
more... genetic algorithms (GA), evolutionary programming, tabu search, simulated annealing and rulebased bacteria foraging [11], [12 ... A novel chaotic approach is proposed here based on the Lozi map. ... two main steps: firstly mapping from the chaotic space to the solution space, and ...
ABSTRACT In this paper, a particle swarm optimization (PSO) technique is proposed for solution of the generation expansion planning (GEP) problem in a competitive electricity market. GEP is one of the important decision-making activities...
moreABSTRACT In this paper, a particle swarm optimization (PSO) technique is proposed for solution of the generation expansion planning (GEP) problem in a competitive electricity market. GEP is one of the important decision-making activities in electric utilities and acquires a principle role in the deregulated environment for electricity trading. It is highly constrained non-linear dynamic optimization problem that can only be fully solved by complete enumeration and is computationally impossible for a real world GEP problem. The utility has to take both independent power producers participation and environment impact (CO2 emission) with satisfying all electrical and energy market constraints simultaneously. The proposed PSO based method has a strong ability to find most optimistic results and is robust for solution problem featuring non-linearity, non-differentiability and high-dimensionality. The proposed method is compared with a GA based technique to illustrate its robust performance considering different purchase prices for IPPs and CO2 emission limits. Analysis reveals that the proposed approach is an inherent, effective and economical tool for the solution of the competitive GEP problem that is easy to implement and is also superior to the GA based technique.
In this paper, a decentralized radial basis function neural network (RBFNN) based controller for load frequency control (LFC) in a deregulated power system is presented using the generalized model for LFC scheme according to the possible...
moreIn this paper, a decentralized radial basis function neural network (RBFNN) based controller for load frequency control (LFC) in a deregulated power system is presented using the generalized model for LFC scheme according to the possible contracts. To achieve decentralization, the connections between each control area with the rest of system and effects of possible contracted scenarios are treated as
In this paper, a new approach by accomplishing dynamic transmission expansion planning (DTEP) problem, the optimum generation level of generators is determined for annual load peak using a genetic algorithm (GA) based quadratic...
moreIn this paper, a new approach by accomplishing dynamic transmission expansion planning (DTEP) problem, the optimum generation level of generators is determined for annual load peak using a genetic algorithm (GA) based quadratic programming (QP) method. This study is carried out in order to achieve a better prospect from the generation network and consequently the suitable planning for its future
ABSTRACT - The artificial neural network (ANN) technique for short term load forecasting (STLF) has been proposed by several authors, and gained a lot of attention recently. In order to evaluate ANN as a viable technique for STLF, one has...
moreABSTRACT - The artificial neural network (ANN) technique for short term load forecasting (STLF) has been proposed by several authors, and gained a lot of attention recently. In order to evaluate ANN as a viable technique for STLF, one has to evaluate the performance of ...
