Distributed Generation unit and Capacitor Placement for Loss, Voltage profile and ATC Optimization

Distributed Generation (DG) and capacitors placement and also the tap setting of ULTC transformers can be used individually to improve the voltage profile and loss reduction. In this article the Genetic Algorithm (GA) is applied to optimize the multi-objective function for of DG and capacitor placement with tap setting of ULTC. The objective function consists the loss reduction, voltage improvement and increasing the available transfer capability (ATC) of the distribution network. To show the effectiveness of the proposed method, it is applied to IEEE 41 bus radial distribution network. The results show that this method has a better effect on improving the objective functions.DOI:http://dx.doi.org/10.11591/ijece.v2i6.74

Modeling FACTS Devices in Power System State Estimation

In this paper is modeled different types of control devices including various kinds of FACTS devices based on power system states. Also, the impact of each device on the amount of injection active or reactive powers as well as active and reactive power flow will be investigated. Based on the type of these devices which can be in parallel, in series or in series–shunt in power systems, proposed models is considered differently. Accordingly, case studies will be performed for three different types of control devices installed in series, in shunt and in series-shunt fashions. State estimation results based on Weighted Least Square not only confirm the proposed models’ effectiveness in accurately state estimating of the system and measurement values but also shows that the estimated values can be obtained from the states of the control devices.Keywords: State Estimation; FACTS Devises; Measurement Function; WLS EstimatorDOI:http://dx.doi.org/10.11591/ijece.v2i1.13

Improving Bad Data Detection in State Estimation of Power Systems

In state estimation of power systems, it is possible that measurements include bad data, influencing on state estimations of power system. Several intelligent methods have been proposed to detect bad data which should be trained in various network situations but they are almost impractical because of abound situations of actual network. Some mathematical methods such as Chi-Square Distribution Test, Largest Normalized Residual Test and Hypotheses Testing Identification as the detectors of bad data have been presented, too. Sometimes these mathematical methods are not able to detect bad data. This paper proposes a method which can improve the detection of bad data in mentioned mathematical methods. Case studies have been done with different given errors on measurements of IEEE 14-bus system, and it was shown that this method is effective to improve the bad data detection.DOI:http://dx.doi.org/10.11591/ijece.v1i2.133 Keywords: Bad Data; Chi-Square Distribution; Largest Normalized Residual; Hypotheses Testing Identificatio

A Novel Hybrid Framework for Co-Optimization of Power and Natural Gas Networks Integrated With Emerging Technologies

In a power system with high penetration of renewable power sources, gas-fired units can be considered as a back-up option to improve the balance between generation and consumption in short-term scheduling. Therefore, closer coordination between power and natural gas systems is anticipated. This article presents a novel hybrid information gap decision theory (IGDT)-stochastic cooptimization problem for integrating electricity and natural gas networks to minimize total operation cost with the penetration of wind energy. The proposed model considers not only the uncertainties regarding electrical load demand and wind power output, but also the uncertainties of gas load demands for the residential consumers. The uncertainties of electric load and wind power are handled through a scenario-based approach, and residential gas load uncertainty is handled via IGDT approach with no need for the probability density function. The introduced hybrid model enables the system operator to consider the advantages of both approaches simultaneously. The impact of gas load uncertainty associated with the residential consumers is more significant on the power dispatch of gas-fired plants and power system operation cost since residential gas load demands are prior than gas load demands of gas-fired units. The proposed framework is a bilevel problem that can be reduced to a one-level problem. Also, it can be solved by the implementation of a simple concept without the need for Karush–Kuhn–Tucker conditions. Moreover, emerging flexible energy sources such as the power to gas technology and demand response program are considered in the proposed model for increasing the wind power dispatch, decreasing the total operation cost of the integrated network as well as reducing the effect of system uncertainties on the total operating cost. Numerical results indicate the applicability and effectiveness of the proposed model under different working conditions

Risk-Aware Stochastic Scheduling of Hybrid Integrated Energy Systems with 100% Renewables

Recently, ambitious endeavors have been carried out to facilitate the transition from traditional grids to hybrid interconnected energy networks in the form of grid modernization. Align to such efforts, this article aims at developing a novel framework for satisfying techno-economic-environmental goals in the grid modernization process. To this end, a detailed examination is conducted for the optimal exploitation of energy hubs (EHs) equipped with 100% renewables to pursue the environmental goal alongside intending technical and economic constraints. The energy conversion technology is adopted to enable the power-to-gas system for establishing multi-energy interactions among electricity and gas networks. Fully benefiting from renewable units has exposed the system to uncertain fluctuations that necessitate the modeling of uncertainties to achieve near-reality results. Hence, risk-averse and seeker strategies are developed based on robustness and opportunistic modes of the information gap decision theory (IGDT) method to deal with stochastic fluctuations of uncertain parameters. The integrated electricity and gas test system is considered to analyze the applicability of the proposed framework in modeling efficient multi-energy interactions. Given the obtained results, 43.68% more energy cost is reached for EHs when they adopted a robust strategy against uncertainties under the risk-averse strategy. Moreover, the proposed framework procured a rational decision-making model for balancing multi-energy in the hybrid energy grid with 100% renewables

An Analytical Framework for Evaluating the Impact of Distribution-Level LVRT Response on Transmission System Security

Low voltage ride through (LVRT) is a solution to increase the tolerance of distributed energy resources (DERs) against the voltage sags. However, the possibility of DERs trip according to the present grid codes exists. Such trips are essential for transmission systems with connected DER-penetrated distribution networks (DPDNs). This paper investigates an analytical framework to see the impact of distribution-level LVRT response on transmission system security. LVRT response stands for the total amount of lost DER capacity due to the inability to meet the LVRT requirement during the voltage sag. This generation loss in the distribution sector can expose the transmission network to lines overloading after fault clearance. The proposed novel approach is based on a source contingency analysis that lets TSOs conduct an LVRT-oriented security assessment. A mathematical function is defined as the LVRT response function of DPDNs. This function gives the lost DER capacity in response to the transmission level transient faults and is constructed by distribution system operators (DSOs). The TSO can use these functions to assess the loading security of transmission lines in post-clearance conditions. In this analytical framework, LVRT-oriented security is evaluated by calculating the risk of lines overloading under a large number of random faults.The proposed approach is implemented in two test power systems with a considerable DER penetration level to obtain the risk of line overloading due to the LVRT response in distribution networks.©2022 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.fi=vertaisarvioitu|en=peerReviewed