Review of trends and targets of complex systems for power system optimization

Optimization systems (OSs) allow operators of electrical power systems (PS) to optimally operate PSs and to also create optimal PS development plans. The inclusion of OSs in the PS is a big trend nowadays, and the demand for PS optimization tools and PS-OSs experts is growing. The aim of this review is to define the current dynamics and trends in PS optimization research and to present several papers that clearly and comprehensively describe PS OSs with characteristics corresponding to the identified current main trends in this research area. The current dynamics and trends of the research area were defined on the basis of the results of an analysis of the database of 255 PS-OS-presenting papers published from December 2015 to July 2019. Eleven main characteristics of the current PS OSs were identified. The results of the statistical analyses give four characteristics of PS OSs which are currently the most frequently presented in research papers: OSs for minimizing the price of electricity/OSs reducing PS operation costs, OSs for optimizing the operation of renewable energy sources, OSs for regulating the power consumption during the optimization process, and OSs for regulating the energy storage systems operation during the optimization process. Finally, individual identified characteristics of the current PS OSs are briefly described. In the analysis, all PS OSs presented in the observed time period were analyzed regardless of the part of the PS for which the operation was optimized by the PS OS, the voltage level of the optimized PS part, or the optimization goal of the PS OS.Web of Science135art. no. 107

Nonlinear finite element analysis of reinforced concrete beams strengthened with textile fine grained mortar

Nowadays, there was an increasing need of repairing and upgrading the reinforced concrete (RC) structure due to the deterioration of the structure. The fibre reinforced polymer (FRP) was commonly used for structural retrofitting purposes. However, owing to the debonding of the FRP from the concrete substrate and high cost of epoxy, it was gradually replaced with textile fine grained mortar (TFGM) nowadays. The TFGM system has been widely used in the construction field nowadays to repair the structure. Our study focus on the strain performances of the concrete surface, steel reinforcement and the textile itself. There were many proven experimental results showing that the TFGM was more effective than the other strengthening method such as FRP plate method. The experimental work done by previous researcher on investigation of strain performances of the concrete surface, steel reinforcement and the textile itself which consists of eleven (11) RC beams with dimension 150 x 200 x 2500 mm. The RC beams were strengthened with FGM and TFGM with 4 layers. The investigation continued with the finite element (FE) strain performance analysis with using Advanced Tool for Engineering Nonlinear Analysis (ATENA) software. The strain of the concrete surface, steel reinforcement and the textile were measured at a mid-point of RC beam. Then, the results of the finite element analysis software ATENA compared against the experimental results. The strain performances of the concrete and steel reinforcement improved noticeably when the number of layers of textile reinforcement used increased

The effect of data preprocessing on the performance of artificial neural networks techniques for classification problems

The artificial neural network (ANN) has recently been applied in many areas, such as medical, biology, financial, economy, engineering and so on. It is known as an excellent classifier of nonlinear input and output numerical data. Improving training efficiency of ANN based algorithm is an active area of research and numerous papers have been reviewed in the literature. The performance of Multi-layer Perceptron (MLP) trained with back-propagation artificial neural network (BP-ANN) method is highly influenced by the size of the data-sets and the data-preprocessing techniques used. This work analyzes the advantages of using pre-processing datasets using different techniques in order to improve the ANN convergence. Specifically Min-Max, Z-Score and Decimal Scaling Normalization preprocessing techniques were evaluated. The simulation results showed that the computational efficiency of ANN training process is highly enhanced when coupled with different preprocessing techniques

Optimal Sizing of Voltage Control Devices for Distribution Circuit with Intermittent Load

We consider joint control of a switchable capacitor and a D-STATCOM for voltage regulation in a distribution circuit with intermittent load. The control problem is formulated as a two-timescale optimal power flow problem with chance constraints, which minimizes power loss while limiting the probability of voltage violations due to fast changes in load. The control problem forms the basis of an optimization problem which determines the sizes of the control devices by minimizing sum of the expected power loss cost and the capital cost. We develop computationally efficient heuristics to solve the optimal sizing problem and implement real-time control. Numerical experiments on a circuit with high-performance computing (HPC) load show that the proposed sizing and control schemes significantly improve the reliability of voltage regulation on the expense of only a moderate increase in cost.Comment: 10 pages, 7 figures, submitted to HICSS'1

Proposed shunt rounding technique for large-scale security constrained loss minimization

The official published version can be obtained from the link below - Copyright @ 2010 IEEE.Optimal reactive power flow applications often model large numbers of discrete shunt devices as continuous variables, which are rounded to their nearest discrete value at the final iteration. This can degrade optimality. This paper presents novel methods based on probabilistic and adaptive threshold approaches that can extend existing security constrained optimal reactive power flow methods to effectively solve large-scale network problems involving discrete shunt devices. Loss reduction solutions from the proposed techniques were compared to solutions from the mixed integer nonlinear mathematical programming algorithm (MINLP) using modified IEEE standard networks up to 118 buses. The proposed techniques were also applied to practical large-scale network models of Great Britain. The results show that the proposed techniques can achieve improved loss minimization solutions when compared to the standard rounding method.This work was supported in part by the National Grid and in part by the EPSRC. Paper no. TPWRS-00653-2009

AC OPF in Radial Distribution Networks - Parts I,II

The optimal power-flow problem (OPF) has played a key role in the planning and operation of power systems. Due to the non-linear nature of the AC power-flow equations, the OPF problem is known to be non-convex, therefore hard to solve. Most proposed methods for solving the OPF rely on approximations that render the problem convex, but that may yield inexact solutions. Recently, Farivar and Low proposed a method that is claimed to be exact for radial distribution systems, despite no apparent approximations. In our work, we show that it is, in fact, not exact. On one hand, there is a misinterpretation of the physical network model related to the ampacity constraint of the lines' current flows. On the other hand, the proof of the exactness of the proposed relaxation requires unrealistic assumptions related to the unboundedness of specific control variables. We also show that the extension of this approach to account for exact line models might provide physically infeasible solutions. Recently, several contributions have proposed OPF algorithms that rely on the use of the alternating-direction method of multipliers (ADMM). However, as we show in this work, there are cases for which the ADMM-based solution of the non-relaxed OPF problem fails to converge. To overcome the aforementioned limitations, we propose an algorithm for the solution of a non-approximated, non-convex OPF problem in radial distribution systems that is based on the method of multipliers, and on a primal decomposition of the OPF. This work is divided in two parts. In Part I, we specifically discuss the limitations of BFM and ADMM to solve the OPF problem. In Part II, we provide a centralized version and a distributed asynchronous version of the proposed OPF algorithm and we evaluate its performances using both small-scale electrical networks, as well as a modified IEEE 13-node test feeder