This study investigated the important elements of emulated inertia control for grid-connected inverter-based power supply sources and identified the issues to be addressed for its integration into the electric power transmission and distribution system. For the first time, we categorized the emulated inertial control algorithms into five types based on three different aspects. Five emulated inertia control algorithms were simulated in order to compare their effectiveness in suppressing frequency fluctuations. In addition, a representative emulated inertia control algorithm based on the voltage-controlled method and another based on the current-controlled method were distinguished. The two emulated inertia control algorithms were implemented and demonstrated using the experimental hardware of a 5 [kVA] inverter-based power supply.
In this paper, a method is introduced for probabilistic power flow calculations based on arbitrary polynomial chaos. For the polynomial chaos, orthogonal polynomial sets are used to represent the uncertainties of renewable power generation, and these orthogonal polynomials are generated from actual data. The aforementioned method is applied to probabilistic power flow calculations, and its applicability is confirmed in application to an actual transmission network. The calculation time and accuracy achieved using the arbitrary polynomial-chaos method are compared with those achieved using the popular Monte Carlo method. The results show that the calculation speed is 246-680 times greater than that with the direct Monte Carlo method, while the accuracy is almost same.
Abstract This paper introduces an arbitrary polynomial chaos expansion method for performing probabilistic power flow analysis in power systems. The proposed method is used for uncertainty analysis, expressing the uncertainty of a system as random variables with an arbitrary output distribution based on orthogonal polynomial expansion. This method is advantageous because of its calculation speed and accuracy. This study expresses probabilistic power flow in a power system with many uncertain power sources using linear combination polynomial expansion. The orthogonal polynomial system employed is generated by moment analysis from renewable energy output data, with the polynomial coefficients derived from a collocation method. Simulation of probabilistic power flow using the proposed method is applied to a 29-bus transmission network model including three renewable energies, and the calculation speed and accuracy are evaluated by changing the expansion order of the polynomial. In addition, the influence on the polynomial coefficient is assessed when the system topology is changed due to a line fault. Therefore, since the arbitrary polynomial chaos expansion method can represent complex networks by linear combination of orthogonal polynomial sets, calculation based on it is several hundred times faster than the conventional Monte Carlo method. The results demonstrate that the proposed method is very useful for analyzing the probabilistic power distribution and that third-order expansion is practically appropriate.
This study clarified the important elements of emulated inertia control for grid-connected inverter-based power supply sources and identified the issues to be addressed for its integration into the system. A classification framework was constructed and the emulated inertia control algorithms were classified into four types. Next, a simulation study was performed on five emulated inertia control algorithms in order to compare their effectiveness in suppressing frequency fluctuations. An emulated inertia control algorithm based on the voltage-controlled method and one based on the current-controlled method were selected from each classification type. Selected emulated inertia control algorithms were implemented on the experimental hardware of a 5 kVA inverter-based power supply, after which an experimental test was performed.
SUMMARY Chubu Electric Power Co., Ltd.’s hybrid power system simulator consists of analog models and hybrid models. The power system facilities are downsized as an analog model, while the synchronous generators and the loads are modeled as an actual current source model through the amplifier and the digital model. In recent years, there is a growing interest in analyzing power system dynamic phenomena caused by a high penetration of distributed generations. Therefore, the multifunctional generator model that can simulate distributed generation has been developed.
This paper is concerned with branch and bound technique for the global solution of bilinear matrix inequality (BMI) problem. In this paper, more strict estimation method of lower bound of objective function and new bounding operation are proposed. The effectiveness of proposed method is confirmed in computational experiments.
CEPCO's hybrid power system simulator consists of analogue models and hybrid models. The power system facilities are downsized as an analogue model, while the synchronous generators and the loads are modeled as an actual current source model through the amplifier and the digital model. In recent years, there is a growing interest in analyzing power system dynamic phenomena caused by a high penetration of distributed generations. Therefore, the multifunctional generator model which can simulate distributed generation has been developed.
This paper presents a FPGA-based analog-digital hybrid real-time simulator (HRTS)with a new state space representation method. In the proposed method, electro-magnetic transient models with switches are represented by parallel ordinary differential equation (ODE)based on a block-diagonal decomposition of matrix. This paper also proposes a new update rule of state space form in order to accurately calculate with limited resources. The proposed method can be implemented with low costs of computation, and enables accurate computation with a less size fixed point of Field-Programmable Gate Array (FPGA). We implemented a doubly fed induction generator (DFIG)based wind turbine model on the FPGA using the proposed method and connected it to the analog simulator via a current source. By comparing with MATLAB/Simulink references, the effectiveness of the proposed method is illustrated.
