Search

With the emergence of smart grids, accurate very short-term load forecasting (VSTLF) has become a crucial tool for competitive energy markets. The number of behind-the-meter photovoltaic solar panels, which usually are not monitored are increasing. This could reduce the load visibility and also affects the VSTLF accuracy. While most of the research works focus on demand forecasting of large areas, the performance of VSTLF methods for the future scenario of high solar power penetration in the microgrid environment is unclear. This paper investigates the impact of high solar power integration on the forecasting accuracy of machine learning VSTLF models for microgrids. The performance of Neural Network, Support Vector Regression are evaluated for high penetration scenario and no solar penetration. The accuracy of these models is examined for three different forecasting horizons through various comparative experiments for two real-world microgrid datasets. According to simulation results, using the most relevant variables is highly recommended. Furthermore, the results demonstrate that machine-learning methods can tackle the nonlinear characteristics of net load forecasting as well as total load forecasting. These simulations show that high penetration of solar power generation could not significantly affect the accuracy of machine learning VSTLF if most relevant variables are selected and applied as model inputs. [ABSTRACT FROM AUTHOR]

This paper presents a fault detection and faulty area identification algorithm in double-circuit transmission lines (DCTLs) compensated by the generalized unified power flow controller (GUPFC) for the first time. The topology of the GUPFC-compensated DCTL is threatened by three types of faults: single-circuit faults, inter-circuit faults, and grounded double-circuit cross-country faults. In the first step, the suggested scheme can determine the time of fault in this type of topology using a very fast method that is based on the analysis of a current index called the current jump index. In the second step, the fault type and area are identified with the help of two other indices, i.e., voltage difference index and current difference index. The test network presented in this paper, which includes a DCTL and a GUPFC, along with the proposed algorithm, is implemented in the MATLAB software package. The results of the simulation and sensitivity analysis of the algorithm confirm the correct performance of the algorithm. [ABSTRACT FROM AUTHOR]

The rapid growth and development of manufacturing technology for controlling processors and high-power semiconductor devices has led to the enhancement of flexible AC transmission system (FACTS) controllers, thus improving the performance of power systems. The generalized unified power flow controller (GUPFC) is today introduced as the most advanced generation of the FACTS family, which is based on voltage source converter (VSC). It can, hence, control all the five parameters of a power system given above. The paper, for the first time, presents the accurate modeling of different parts of the control system and power electronics of the 72-pulse VSC-based GUPFC in detail to satisfy operation constraints and improve power quality in terms of harmonic level reduction. There is no need to use active or passive filters in the proposed model for reducing harmonic level of the GUPFC. In this regard, the calculation of four main parameters, namely D_alpha, alpha, angular speed, and sigma, as inputs of the pulse-firing system for the 72-pulse VSC is performed dynamically and optimally to meet all expected constraints in terms of operation, power quality, and harmonic reduction of a network with a GUPFC. The presented modeling is implemented on a 230 kV GUPFC-compensated double-circuit transmission line in MATLAB/Simulink environment, and the desired results of the presence of the 72-pulse VSC-based GUPFC are shown to meet the desired constraints of operators. [ABSTRACT FROM AUTHOR]