Applications In Power Networks Research Articles

A Hybrid Approach for Time-Varying Harmonic and Interharmonic Detection Using Synchrosqueezing Wavelet Transform

With widespread non-linear loads and the increasing penetration of distributed generations in the power system, harmonic pollution has become a great concern. The causes of harmonic pollution not only include the integer harmonics, but also interharmonics, which exacerbate the complexity of harmonic analysis. In addition, the output variability of highly non-linear loads and renewables such as electric arc furnaces and photovoltaic solar or wind generation may lead to weakly time-varying harmonics and interharmonics in both frequency and magnitude. These features present challenges for accurate assessment of associated power-quality (PQ) disturbances. To tackle such increasing time-varying PQ problems, a hybrid detection method using synchrosqueezing wavelet transform (SSWT) is proposed. The proposed method first obtains the proper parameter values for the mother wavelet according to numerical computations. The wavelet transform-based synchrosqueezing and a clustering method are applied to determine each frequency component of the waveform under assessment. The time-domain waveform and the associated magnitude of each frequency component is then reconstructed by the inverse SSWT operation. The novelty of the proposed method is that it can decompose the measured waveform containing both harmonics and interharmonics into intrinsic mode functions without the need for fundamental frequency detection. Compared to other time–frequency analysis methods, SSWT has better anti-noise and higher resolution of time–frequency curves; even the measured signal has close frequency components. Simulation results and actual measurement validations show that the proposed method is effective and relatively accurate in time-varying harmonic and interharmonic detection and is suitable for applications in power networks and microgrids that have high penetration of renewables or non-linear loads causing time-varying voltage or current waveforms.

Influence of field-dependent critical current on harmonic AC loss analysis in HTS coils for superconducting transformers supplying non-linear loads

There are two main obstacles in front of the development of high temperature superconducting (HTS) technology for electric power network applications; tape price and cooling cost. In order to reduce cooling cost, it is vital to evaluate AC transport current loss of the tapes precisely and then reduce it by some design innovative approaches. In addition, AC transport current loss in HTS material is a critical design variable for large-scale power network applications such as HTS transformers, superconducting fault current limiters, and power cables, since they are continuously carrying the network/load current during their operating life. In existing power networks, harmonic production sources are commonly used and thus, currents are distorted. Therefore, the effect of nonsinusoidal current on the critical apparatus in the network such as transformer must be studied. In this paper, AC transport current loss of a single-turn 2G YBCO HTS coil was modeled and numerically calculated under nonsinusoidal transport current using finite element method. Furthermore, influence of dependency of critical current density to magnetic field on the AC transport current loss of HTS coil when carries distorted currents was considered. It was observed that nonsinusoidal current causes excessive losses in HTS coil. On the other hand, a case study on an HTS transformer supplying non-linear load was considered to study the loss increment as well as heat load change. It was observed that current harmonics increases the AC loss, and heat load of transformer and decreases the efficiency, consequently.

Scheduled-Asynchronous Distributed Algorithm for Optimal Power Flow

Optimal power flow (OPF) problems are nonconvex and large-scale optimization problems with important applications in power networks. This paper proposes the scheduled-asynchronous algorithm to solve a distributed semidefinite programming formulation of the OPF problem. In this formulation, every agent seeks to solve a local optimization with its own cost function, physical constraints on its nodal power injection, voltage, and power flow of the lines it is connected to, and decision constraints on variables shared with neighbors to ensure consistency of the obtained solution. In the scheduled-asynchronous algorithm, every pair of connected nodes in the electrical network update their local variables in an alternating fashion. This strategy is asynchronous, in the sense that no clock synchronization is required, and relies on an orientation of the electrical network that prescribes the precise ordering of node updates. We establish the asymptotic convergence properties to the primal-dual optimizer when the orientation is acyclic. Given the dependence of the convergence rate on the network orientation, we also develop a distributed graph coloring algorithm that finds an orientation with diameter at most five for electrical networks. Simulations illustrate our results on various IEEE bus test cases.

Hierarchical distributed ADMM for predictive control with applications in power networks

In this paper, we investigate optimal control and operation of a network of linear, physically decoupled systems with a coupling in the objective function. To deal with the corresponding distributed control problem, we propose a new Model Predictive Control (MPC) scheme based on the Alternating Direction Method of Multipliers (ADMM). In particular, we thoroughly investigate the flexibility of the proposed hierarchical distributed MPC algorithm with respect to both its plug-and-play capability and changes in the (local) system dynamics and objective functions at runtime. Moreover, we show linear scalability in the number of subsystems. The efficacy of the distributed optimization algorithm embedded in MPC is illustrated on three battery scheduling problems arising from the predictive control of residential microgrid electricity networks.

Recent Advances in the Quest for a New Insulation Gas with a Low Impact on the Environment to Replace Sulfur Hexafluoride (SF6) Gas in High-Voltage Power Network Applications

The growing environmental challenge of electrical energy systems has prompted a substantial increase in renewable energy generation. Such generation systems allow for significant reduction of CO2 emissions compared with a traditional fossil fuel plant. Furthermore, several improvements in power systems network configuration and operation combined with new technologies have enabled reduction of losses and energy demand, thus contributing to reduction of CO2 emissions. Another environmental threat identified in electrical networks is the leaking of insulating sulfur hexafluoride (SF6) gas used in electrical gas insulated substations (GIS) and equipment. Because of its Global Warming Potential (GWP) of nearly 24,000 and its long life in the atmosphere (over 3000 years), SF6 gas was recognized as a greenhouse gas at the 1997 COP3; since then its use and emissions in the atmosphere have been regulated by international treaties. It is expected that as soon as an alternative insulating gas is found, SF6 use in high-voltage (HV) equipment will be banned. This paper presents an overview of the key research advances made in recent years in the quest to find eco-friendly gases to replace SF6. The review reports the main properties of candidate gases that are being investigated; in particular, natural gases (dry air, N2 or CO2) and polyfluorinated gases especially Trifluoroiodomethane (CF3I), Perfluorinated Ketones, Octafluorotetra-hydrofuran, Hydrofluoroolefin (HFOs), and Fluoronitriles are presented and their strengths and weaknesses are discussed with an emphasis on their dielectric properties (especially their dielectric strength), GWP, and boiling point with respect to the minimum operating temperature for HV power network applications.

Modelling electrochemical energy storage devices in insular power network applications supported on real data

This paper addresses different techniques for modelling electrochemical energy storage (ES) devices in insular power network applications supported on real data. The first contribution is a comprehensive performance study between a set of competing electrochemical energy storage technologies: Lithium-ion (Li-ion), Nickel–Cadmium (NiCd), Nickel–Metal Hydride (NiMH) and Lead Acid (PbA) batteries. As a second contribution, several key engineering parameters with regards to the PbA battery-based storage solution are examined, such as cell charge distribution, cell string configuration and battery capacity fade. Finally, as a third contribution, an ES system operating criterion is discussed and proposed to manage the inherent rapid aging of the batteries due to their cycling activity. The simulation results are supported on real data from two non-interconnected power grids, namely Crete (Greece) and São Miguel (Portugal) Islands, for demonstration and validation purposes.