In this article, a fault location technique based on artificial neural networks (ANN) for Terminal-Hybrid LCC-VSC-HVDC has been assessed and scrutinized. As is known, in conventional HVDC systems (LCC-based and VSC-based HVDCs), the same type of filter is used on both sides due to the use of similar converters in both sender and receiver terminals. In this article, it is concluded that due to the use of two different types of converters at the both ends of the utilized Terminal-hybrid LCC-VSC-HVDC system, and the use of different DC filters on both sides, fault location using positive and negative pole currents of the rectifier side has much better results than the rest of input signals. Therefore, it will be finalized that by increasing and designing suitable DC filters on the transmission line of HVDC systems, fault localization matter will be remarkably and surprisingly facilitated. Nowadays, the fault location of HVDC transmission lines with a value of more than 1% is generally discussed in most articles. In this research, the fault location with a value of 0.0045%, i.e., a distance of 22.5 meters from the fault point in the most satisfactory case is obtained, which shows the absolute feasibility of the ANN along with the wavelet transform. To validate the proposed method, a ±100 KV, Terminal-hybrid LCC-VSC-HVDC system is simulated via MATLAB. The outcomes verify that the proposed technique works perfectly under various fault locations, resistances, and fault types.

Implementation of high-capacity power transmission systems in power systems is a growing trend. Among these systems, HVDC and EHVAC power transmission systems are the most popular because of their capabilities and their low investment costs over the long distances. Despite of the mentioned advantages, the reliability of the high-capacity power transmission has been a major concern for power system operators. In terms of reliability, the occurrence of an error in a high-capacity power transmission system (such as HVDCs) causes a large loss of capacity in the transmission network, which can have a major effect on the performance of this system. Therefore, reliability assessment of high-capacity power transmission systems is necessary. In this paper, the reliability level of three modern technologies (HVDC-VSC, HVDC-LCC and EHVAC in different structures) is compared. By comparing these systems, the most proper system for high-capacity power transmission from the reliability viewpoint can be selected.

This paper presents a valued-based approach to select system enhancement alternatives based on the proposed system well-being analysis technique. The technique is used to rank the various system enhancement alternatives for an existing HVDC system. The system health states are classified according to three operating states namely, healthy, marginal and at risk. The reliability health indices with various improvement options are calculated for the HVDC transmission. The reliability health indices are then recalculated by including the outages of the generation. The options are then ranked according to their reliability benefits and their costs.

High voltage direct current transmission systems (HVDC) have been applied for several advantages as link between asynchronous AC systems, economical power transmission over long distances, power accurate control, stability, power quality and low power dissipation. HVDC technology based on voltage source converter (VSC-HVDC) is a kind of newly developed HVDC transmission technology. It is attractive for connecting weak AC networks, islands networks and renewable sources to a main grid. This new HVDC system has been studied in this paper and compared with conventional HVDC and HVAC. Some control schemes have been introduced to control the VSC-HVDC system.

In this paper a suitable mathematical model of the two terminal HVDC system is provided for optimal power flow (OPF) and optimal location based on OPF such power injection model. The ability of voltage source converter (VSC) -based HVDC to independently control active and reactive power is well represented by the model. The model is used to develop an OPF-based optimal location algorithm of two systems two terminal HVDC to minimize the total fuel cost and active power losses as objective function. The optimization framework is modeled as non-linear programming (NLP) and solved by Matlab and GAMS softwares. The proposed algorithm is implemented on the IEEE 14- and 30-bus test systems. The simulation results show ability of two systems two terminal HVDC in improving the power system operation. Furthermore، two systems two terminal HVDC is compared by PST and OUPFC in the power system operation from economical and technical aspects.

Because of low losses and voltage drop, fast control of power, the limitless connection distance and isolation issues, using the High Voltage Direct Current (HVDC) transmission system based on Voltage Source Converters (VSC) is recommended to the power transfer in the electrical power networks included the offshore wind power plants (OWPP). The OWPPs are expected to meet the grid code necessities when requested to maintain stability. Utilization of the VSC HVDC along with the OWPP, can improve the control of power flow and the power system dynamic stability. In this paper, the impact of control of VSC HVDC based OWPP, on the dynamic stability of power systems is evaluated.  In this way, the dynamic modeling of power system equipped by the VSC HVDC and OWPP are proposed. In the proposed model, using the concepts of controllability and observability of electromechanical modes of power systems, a new approach to the design a supplementary damping controller in VSC HVDC based OWPP is presented. The damping controller is designed based on the nonlinear adaptive neural networks concepts and trained by a proposed online method. The simulation results which are done in MATLAB, show the effectiveness of the proposed control strategy.

The use of high voltage direct current (HVDC) transmission lines in power systems not only increase the capacity of electrical power transmission systems, but also strengthen the stability of the power network. In order to optimize the HVDC influences on voltage-frequency stability, it is necessary to design supplementary controllers in the most optimal path between input-output signals of the whole power system. The supplementary controllers are added to the local control loop of HVDC to improve active-reactive power flow. In this paper, an optimized method based on the controllability concept is proposed for the coupling of the input-output (IO) signals of the power system equipped with voltage source converter (VSC)-based HVDC. Then, the optimal path is used for supplementary damping controller design based on a novel adaptive recurrent neural network (ARNN). The ARNN is trained online Using a new training algorithm. The simulation results, which are carried on using MATLAB software, show the effectiveness of the control strategy to improve the voltage profile and dynamic stability of the power system.

Voltage Source Converter based High Voltage Direct Current (VSC-HVDC) has been an area of growing interest during the recent years. Indeed, VSC-HVDC has the capability of controlling the active power and the reactive power; rapidly, independently, and simultaneously. The main focus of this research is on VSC-HVDC system modeling; in which, two different controllers, such as the PI controller and the fuzzy logic controller, have been implanted in the system. Furthermore, these two controllers have been analyzed and compared to each other. Whereas, the main objective of the work presented in this paper is finding the more suitable controller which could allow improving the robustness of the whole control system and its impact on the dynamic performance of the VSC-HVDC during parameter uncertainties, such as load change, parametric variation, and faults occurrence. The obtained results have shown that using the fuzzy controller could lead to a better performance of the studied system, compared to the other controller.

Life Cycle Costing (LCC) is a methodology used first time by the Department of Defense of United State, it’s an economic calculation of all costs propagated during the life span of any technical system. For Renewable Energy (RE) systems, LCC is a good methodology, which shows the cost-effectiveness of using RE as an alternative source compared to conventional power generations. A LCC model was introduced for Wind generation system. Data collection was done through four different cost data sources. The results shows that the capital investment cost is $1.968/W. For a 20 years PV project life-time, the operation and maintenance cost forms 19% of the total LCC of the system.

Life cycle costing (LCC) is a methodology used first time by the Department of Defense of United State, it’s an economic calculation of all costs propagated during the life span of any technical system. For Renewable Energy (RE) systems, LCC is a good methodology, which shows the cost-effectiveness of using RE as an alternative source compared to conventional power generations. A LCC model was introduced for PV generation system. Data collection was done through four different cost data sources. The results shows that the average module price is $0.56/Wp and the capital investment cost is $1.184/Wp. For a 20 years PV project life-time, the operation and maintenance cost forms 27% of the total LCC of the system.