Recent Development in Electricity Price Forecasting Based on Computational Intelligence Techniques in Deregulated Power Market

The development of artificial intelligence (AI) based techniques for electricity price forecasting (EPF) provides essential information to electricity market participants and managers because of its greater handling capability of complex input and output relationships. Therefore, this research investigates and analyzes the performance of different optimization methods in the training phase of artificial neural network (ANN) and adaptive neuro-fuzzy inference system (ANFIS) for the accuracy enhancement of EPF. In this work, a multi-objective optimization-based feature selection technique with the capability of eliminating non-linear and interacting features is implemented to create an efficient day-ahead price forecasting. In the beginning, the multi-objective binary backtracking search algorithm (MOBBSA)-based feature selection technique is used to examine various combinations of input variables to choose the suitable feature subsets, which minimizes, simultaneously, both the number of features and the estimation error. In the later phase, the selected features are transferred into the machine learning-based techniques to map the input variables to the output in order to forecast the electricity price. Furthermore, to increase the forecasting accuracy, a backtracking search algorithm (BSA) is applied as an efficient evolutionary search algorithm in the learning procedure of the ANFIS approach. The performance of the forecasting methods for the Queensland power market in the year 2018, which is well-known as the most competitive market in the world, is investigated and compared to show the superiority of the proposed methods over other selected methods.© 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).fi=vertaisarvioitu|en=peerReviewed

Optimal multiplier load flow method using concavity theory

This paper utilises concavity properties in the optimal multiplier load flow method (OMLFM) to find the most suitable low voltage solution (LVS) for the systems having multiple LVS at the maximum loading point. In the previous method, the calculation of the optimal multiplier is based on only one remaining low voltage solution at the vicinity of voltage collapse point. However, this does not provide the best convergence for multi-low voltage solutions at the maximum loading point. Therefore, in this paper, concavity properties of the cost function in OMLFM are presented as the indicator to find the most suitable optimal multiplier in order to determine the most suitable low voltage solutions at the maximum loading point. The proposed method uses polar coordinate system instead of the rectangular coordinate system, which simplifies the task further and by keeping PV type buses. The polar coordinate in this method is based on the second order load flow equation in order to reduce the calculation time. The proposed method has been validated by the results obtained from the tests on the IEEE 57, 118 and 300-bus systems for well-conditioned systems and at the maximum loading point

Quadratic Discriminant Index for Optimal Multiplier Load Flow Method in ill conditioned system

In ill conditioned power systems, the classical Optimal Multiplier Load Flow Method (OMLFM) can only calculate Low Voltage Solutions (LVS) at the vicinity of the maximum loading point (MLP). It cannot determine the boundary zone between solvable and unsolvable cases of load flow equations solution. Considering this limitation, this paper proposed the Quadratic Discriminant Index (QDI) based on the properties of quadratic form of load flow equations to enhance OMLFM to find LVS at the MLP in polar coordinate form. These properties can describe all straight lines through two distinct state variables solution as Multiple Load Flow Solutions (MLFS) in OMLFM. The trajectory of these lines approaches MLP in term of loading factor. Furthermore, in this process, MLP in well, ill and unsolvable operation zones can also be determined. The test results of a single-machine system and IEEE 14, 57 and 118-bus test systems demonstrate the validity of the proposed method

Improved Step Size Newton Raphson Method using quadratic equations properties in ill-conditioned power system

The Step Size of the Newton Raphson Method (SSNRM) is based on the optimal multiplier that is used to determine the Multiple Load Flow Solutions (MLFS) for an ill-conditioned power system. However, the SSNRM is incapable of determining the desirable Low Voltage Solution (LVS) from the MLFS at the Maximum Loading Point (MLP), due to the fact that when the load demand increases, the LVSs moves closer to each other at the MLP. Commonly, the smallest optimal multiplier was used to calculate the LVS at the MLP under this condition. However, this paper proves the fact that using the smallest optimal multiplier to determine the most suitable LVS for the systems having multiple solutions at the MLP will not guarantee a favourable outcome. Therefore, this paper investigates the application of the properties of scalar quadratic equations (PSQE) that enhances the function of the SSNRM at the MLP. Thus, an indicator, based on PSQE, is introduced in this work, which amends the existing SSNRM for the purpose of finding the desirable LVS at the MLP. The closest optimal multiplier to the proposed indicator is selected in order to determine the desirable LVS from all possible solutions at the MLP. The proposed method has been tested on a three-bus and IEEE 30-bus systems at the MLP for verification purposes. Additionally, the continuation power flow method is also utilized in order to compare it to the proposed method for the IEEE 30-bus system at the MLP

Determination of the striking distance of a lightning rod using finite element analysis

The problems related to electromagnetic waves transmitted by lightning strikes can be studied through physical lightning models based on laboratory results. The main concern of these models is determining the striking distance between the leader tip and the lightning rod during lightning occurrences. The striking distance is a significant factor in designing the lightning protection system. However, models using finite element analysis (FEA) for this purpose are less likely to be found in the literature. Therefore, in this work, a geometry model of a lightning rod and leader was developed using available FEA software. The model was used to determine the striking distance for different lightning rod heights. The results obtained were compared with those of previous research using different methods to validate the models developed using FEA software. From the comparison, the striking distance obtained from the FEA software as a function of lightning rod height was in good agreement compared to other methods from previous research. The use of FEA software also enables the effect of different tip radii of curvature and shapes of the lightning rod on striking distance to be studied, which can further enhance our understanding of the relationship between striking distance and different rod parameters

Development and application of superhydrophobic outdoor insulation: A review

The aim of this article is to present a review of the development and application of superhydrophobic insulation for outdoor high-voltage applications. The methods of preparing insulation exhibiting superhydrophobic properties to mitigate the pollution problem under high voltages in the outdoors are explored. In addition, the existing evaluation techniques at the material development stage are reviewed and potential new modifications are discussed. The self-cleaning and anti-icing properties, the electrical performance, and prospects of superhydrophobic insulators are also addressed. Although superhydrophobic insulators may show promising behavior in small-scale laboratory conditions that do not use electrical stress, the effect of surface micro–nano structure responsible for the superhydrophobicity on the performance under the actual outdoor and weathering conditions under voltage remains to be fully understood and verified. Therefore, there is a need to verify the feasibility of superhydrophobic insulators for outdoor high-voltage applications with a solid evaluation protocol, while using material screening methods in the laboratory, and with reference to field experience