OPTIMAL PLACEMENT OF TCSC BASED ON MIN-CUT ALGORITHM FOR CONGESTION MANAGEMENT IN DEREGULATED ELECTRICITY MARKET

ABSTRACT FACTS devices such as thyristor controlled series compensators (TCSC) by controlling the power flows in the network, can help to reduce the flows in heavily loaded lines resulting in an increased loadability of the network and reduced cost of production. This paper represents the Min-cut algorithm to determine the weakest zone (bottle -neck) of the power system that can often lead to congestion then combination with loss sensitivity index to determine optimal location of TCSC. With this method, the number of branches which need to be investigated to determine the position placement TCSC for congestion management in deregulated electricity market will significantly be decreased. Study results on IEEE 5-bus, IEEE 14-bus have proved the effectiveness of the algorithm

Optimal Location of Thyristor-controlled-series-capacitor using Min Cut Algorithm

Existence of many different Operators in the new electricity has brought many challenges in the system operation and control to obtain minimum generation cost and security. With the growing demand of electricity in the competitive electricity market environment, one or more transmission lines could be overloaded, therefore causing congestion. The congestion can be eliminated /alleviated by improving transfer capability of the network. Thyristor controlled series compensators (TCSC), with its ability to directly control the power flow can be very effective to improve the operation of transmission network. This paper describes an approach for determining the most suitable locations for installing TCSC devices in order to eliminate line overloads and minimize generation costs. The proposed approach is based on the minimum cut methodology that reduces the search space and using benefit index to decide on the best locations for the TCSC. The 5-bus, IEEE 14-bus and 30-bus test systems are used to demonstrate the proposed approach. Results show that the proposed method is capable of finding the best location for TCSC installation to minimize total costs. DOI : http://dx.doi.org/10.11591/telkomnika.v12i5.442

A Novel Improved Cuckoo Search Algorithm for Parameter Estimation of Photovoltaic (PV) Models

Parameter estimation of photovoltaic (PV) models from experimental current versus voltage (I-V) characteristic curves acts a pivotal part in the modeling a PV system and optimizing its performance. Although many methods have been proposed for solving this PV model parameter estimation problem, it is still challenging to determine highly accurate and reliable solutions. In this paper, this problem is firstly transformed into an optimization problem, and an objective function (OF) is formulated to quantify the overall difference between the experimental and simulated current data. And then, to enhance the performance of original cuckoo search algorithm (CSA), a novel improved cuckoo search algorithm (ImCSA) is proposed, by combining three strategies with CSA. In ImCSA, a quasi-opposition based learning (QOBL) scheme is employed in the population initialization step of CSA. Moreover, a dynamic adaptation strategy is developed and introduced for the step size without Lévy flight step in original CSA. A dynamic adjustment mechanism for the fraction probability (Pa) is proposed to achieve better tradeoff between the exploration and exploitation to increase searching ability. Afterwards, the proposed ImCSA is used for solving the problem of estimating parameters of PV models based on experimental I-V data. Finally, the proposed ImCSA has been demonstrated on the parameter identification of various PV models, i.e., single diode model (SDM), double diode model (DDM) and PV module model (PMM). Experimental results indicate that the proposed ImCSA outperforms the original CSA and its superior performance in comparison with other state-of-the-art algorithms, and they also show that our proposed ImCSA is capable of finding the best values of parameters for the PV models in such effective way for giving the best possible approximation to the experimental I-V data of real PV cells and modules. Therefore, the proposed ImCSA can be considered as a promising alternative to accurately and reliably estimate parameters of PV models