Large-scale Transmission Network Research Articles

A parallel approach for ultra-fast state estimation in large power system using graph partitioning theory

This paper introduces a novel approach for multi-area state estimation in large transmission networks through the application of graph partitioning theory. By harnessing the eigenvalues and eigenvectors of the Laplacian matrix, a large-scale transmission network is partitioned into manageable sections. Within these partitions, state estimation processes run in parallel, markedly improving efficiency compared to conventional methods. Linear state estimation is employed within each area, expediting computations and making it adaptable to large-scale networks, which traditionally pose computational challenges. The method's efficacy is demonstrated through comprehensive validation, commencing with small networks and extending to real-world applications on the IEEE 118-bus test system and the 9241-bus European high-voltage transmission network. In comparison to the integrated network method, our approach has achieved state estimation answers with reduced computation time. The partitioning of the integrated network into multi areas has effectively mitigated computational loads, showcasing its potential for enhancing operational efficiency and reliability in complex power transmission systems. This approach not only offers a robust solution for state estimation but also represents a significant stride toward advancing the field of state estimation, promising to bolster the stability and performance of modern power grids.

Planning of electric vehicle charging infrastructure under the Background of Big Data

Today, the problems of power consumption and environmental pollution caused by road traffic are very serious. Automobiles produce large amounts of carbon monoxide and nitrogen, dust, and particles, which are the primary user of the fuel. Unconventional design methods will prevent the international process of replacing fuel-filled vehicles with electric vehicles. The promotion and adoption of electric vehicles can effectively alleviate these problems, but the planning of electric vehicle charging facilities needs to be resolved as soon as possible. The state-of-the-art mode and power model of public charging equipment proposed in this paper can solve the problem of positioning charging equipment in large-scale transmission networks and research on related charging materials and location planning and energy model design methods that are beneficial to the future development.

Research and Suggestions on Some Key Issues in Electric Vehicle Charging Infrastructure Planning

Today, the problems of power consumption and environmental pollution caused by road traffic are very serious. The promotion and adoption of electric vehicles can effectively alleviate these problems, but the planning of electric vehicle charging facilities needs to be resolved as soon as possible. This article aims to study the design of charging infrastructure based on the background of big data. The case analysis confirmed the importance of the billing company's design model and proposed an effective solution process. Taking M city as an example, combining the charging data obtained by simulation, the charging kits in the city center and the design area, and the effective solutions to the actual situation, the sensitivity analysis of the selection of slow charging equipment is carried out. Mode model between the two ion functions and the radio function of the charging station. The case analysis results show that a total of 10 60kW fast charging facilities need to be built in this industrial zone. The state-of-the-art mode and power model of public charging equipment proposed in this paper can solve the problem of positioning charging equipment in large-scale transmission networks.

Rural electrification in protected areas: A spatial assessment of solar photovoltaic suitability using the fuzzy best worst method

The need for energy in rural and remote areas is increasing, and it is exacerbated in developing countries. The wellbeing of communities and citizens depends on access to clean electricity to improve quality of life. An uninterrupted supply of electricity is one of the sustainable development goals (SDGs) that has highlighted the needs and challenges in remote areas. The complexity of designing strategies and solutions is further augmented for villages located in protected areas, national parks, and wildlife refuges, the conservation of which is fundamental to achieving climate, environmental, and ecologic objectives. Fossil fuel-based electricity generation and large-scale transmission networks pose a potential threat to the achievement of SDGs in such areas. This research investigated the use of solar photovoltaic (PV) technology as a renewable energy source (RES) that can cover energy needs of rural areas in a continuous, secure, and sustainable manner. In this study, the feasibility of using solar energy to electrify remote settlements located in protected areas of Iran (Khorasan-e-Razavi) was evaluated using a multi-criteria, GIS-based methodology. A set of criteria was selected to evaluate the suitability of solar PV, including solar irradiance and duration, aspect, temperature, precipitation, and humidity as well as proximity to faults, roads, and rivers. Using the best worth method (BWM), the relative weight of the selected criteria was calculated. The results showed that almost 2% of the region's area is very highly suitable and another 23.5% is highly suitable. This 25% represents an area of 1500 km2 and includes 63 villages. Evaluation of census data showed that available building areas can cover the villages' residential demand using rooftop PV systems. Nonetheless, local and national government support is necessary to develop an effective strategy that results in successful implementation.

Enhancement of voltage stability in an interconnected network using unified power flow controller

In this paper, the optimal placement of Unified Power Flow Controllers (UPFC) in a large-scale transmission network in order to improve the loadability margin was considered. In other to achieve this aim, the Line Stability Factor (LQP) as a technique for the optimal location of UPFC in the IEEE 14-bus network and 56-bus Nigerian national grid was adopted. The power injection model for the UPFC was employed to secure improvements in the loading margin of the IEEE 14-bus network and 56-bus Nigerian national grid system. Continuation power flow was used to assess the effect of UPFC on the loadability margin. Steady-state simulations using Power System Analysis Toolbox (PSAT) on MATLAB was applied to determine the effectiveness of placing UPFC between bus 13 and bus 14 in the IEEE 14-bus network and between bus 44 (Ikot-Ekpene) and bus 56 (Odukpani) in the 56-bus Nigerian national grid system. The results showed that the loadability margin increased by 8.52 % after UPFC was optimally placed in the IEEE 14-bus network and increased by 195.5 % after UPFC was optimally placed in the 56-bus Nigerian national grid system. Thus, these enhance the voltage stability of both network and utilizing the network efficiently.

A Complex Variable Perturbed Gauss-Newton Method for Tracking Mode State Estimation

The recent power systems literature has witnessed an intensified interest in state estimation methods that can handle a vast array of measurements from large-scale networks while maintaining performance that is commensurate with real-time requirements. When measurements are from the Supervisory Control and Data Acquisition (SCADA) system and Phasor Measurement Units (PMUs), an elegant formulation of the weighted least squares problem can be cast in complex variables and solved via the Gauss-Newton (GN) method. This paper presents a Perturbed Gauss-Newton (PGN) method in complex variables that is suitable for real-time tracking of the network's state vector. The proposed PGN method is built around an entirely linear measurement model expressed in function of the complex phasor voltages, and its iterative solution scheme requires one factorization of the coefficient matrix followed by repeated forward/backward substitutions. The complex variable PGN method for state estimation can be therefore seen as the counterpart of the classical implicit bus impedance method for power flow. The paper reports numerical results of the PGN method on large-scale transmission networks having up to 9241 nodes and contrasts the proposed method with the equality constrained GN method in complex variables and a recent two-stage estimator also operating in the complex domain.

Application of a new fast analytical approach for post-contingency state estimation of “N-1” transmission line outage in online vulnerability assessment of large-scale transmission networks with wind power resources

In this paper, a new analytical method is presented for calculation of the “N-1″ transmission line outage post-contingency states of the power system, without any needs to iterate the calculation process, which makes the method fast enough for online vulnerability assessment under N-1 Transmission line outages for large-scale transmission networks with wind power resources. The proposed method is based on the proposed pretending line outage principle and a pre-contingency Taylor Series Approximation. Moreover, an adaptive technique is proposed for selection of the number of critical lines. First, various test systems including IEEE 9-, 39-, 57-, 118-, 300-, and 2746-bus are used for investigation of the performance of the proposed method in terms of accuracy and computational time. Moreover, the ability of the proposed method in solving the Online Vulnerability Assessment under the uncertainty of the operating condition, caused by wind power resources and load demand forecast error, is investigated in IEEE 118-bus and IEEE 300-bus test systems. Finally, the simulation results are presented to verify that the proposed approach has sufficient speed and accuracy to be used in online operational vulnerability assessments.

Comparison of time-varying phasor and dq0 dynamic models for large transmission networks

In recent years, with increasing penetration of small distributed generators and fast power electronics based devices, the assumption of quasi-static phasors is becoming increasingly inaccurate. In order to describe fast dynamic behavior and rapid amplitude and phase variations, more accurate dynamic models based on the dq0 transformation are used. To better understand the differences between these two models, in this work we compare their relative accuracy when applied to large-scale transmission networks. In this light, the present work describes the two types of models using similar terminology, which is based on dq0 quantities. Based on this result, we show that quasi-static models may be obtained from dq0 models at low frequencies, and that there exists a frequency range in which quasi-static model approximates the dq0 model well. The obtained results allow to estimate the frequency after which the quasi-static model cannot accurately describe the system dynamics, and dq0 models should be used instead.

Price Regulation and Pipeline Transmission Capacity

A considerable literature has extolled the virtues of transitioning away from rate-of-return regulation for infrastructure-intensive industries. I find that for a large-scale transmission network like the U.S. natural gas pipeline system, transmission capacity under rate-of-return regulation may be suppressed relative to that which occurs under a more flexible price cap regime. My results have specific implications for the U.S. natural gas market, as well as more general implications for the regulation of transmission network infrastructure, which emanate from the well-known effects of congestion on the economic efficiency of markets served by such networks.

Planning for Big Things in Brazil

This paper discusses the planning and building of large-scale transmission networks in competitive hydrothermal systems. The business model for transmission expansion in Brazil relies on a combination of planning and competition. The model is felt to be successful both in terms of ensuring expansion and attracting private investments and is being considered by other Latin American countries, mainly Central America and the Andean market. Due to new transmission facilities the interchange capacity limits in between regional systems have increased, avoiding congestion risks, enhancing the system security margins, and giving more transmission capacity to accommodate the needed power flows to optimize the hydrothermal dispatch. Regulatory risks have also been low, since regulations in place are almost consolidated and considered stable by market players. However, some challenges remain to be tackled, essentially concerning the strong coupling between generation and transmissiori planning and transmission tariff allocation. Additionally, it must be mentioned that improvement of the regulatory framework for the transmission and distribution frontier is a topic that is being currently focused on by the regulator. Clearly, setting the rules for system reinforcement in this interface area has been proved to be highly relevant in not jeopardizing the reliability of load supply.

Distributed self-healing network and its optimum spare-capacity assignment algorithm

Rapid self-healing under link failure in high-capacity optical fiber is a basic issue in broadband networks. Failure restoration schemes are being studied which reroute failed paths using the control of path reconfiguration function of the Digital Cross Connect System (DCS). Distributed control schemes based on a flooding algorithm have been proposed to meet real-time requirements for large-scale transmission networks, but problems arise, such as message congestion at nodes and internode synchronization. The performance of the self-healing algorithm depends not only on the algorithm itself but also on physical network topology and spare capacity. In this paper, we propose a distributed restoration algorithm using a flooding technique and a centralized spare-capacity assignment algorithm minimizing total spare capacity in a network while meeting a given survivability objective. The failure restoration time, restoration ratio, and spare capacity cost of these algorithms will be evaluated by computer simulation.