Secondary Load Frequency Control of Time-Delay Stand-Alone Microgrids With Electric Vehicles

Khooban, Mohammad‐Hassan

doi:10.1109/tie.2017.2784385

Cited by 179 publications

(63 citation statements)

References 21 publications

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“…By combining Equations (1) and (2), and discretizing, the more computationally efficient discrete WT (DWT) can be obtained and is expressed as:…”

Section: Wavelet Transforms (Wt)mentioning

confidence: 99%

“…In competitive and liberalized markets with prominent renewable integration, the natural renewable stochasticity is echoed in all market players' decisions, bringing additional challenges in the way of achieving a sustainable, profitable, and reliable operation of the electricity structure [1]. Moreover, the microgeneration together with the natural evolution of renewable energy technologies is leading to a paradigm shift of the electricity sector [2].…”

Section: Introductionmentioning

confidence: 99%

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Hybrid Forecasting Model for Short-Term Electricity Market Prices with Renewable Integration

et al. 2018

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In recent years, there have been notable commitments and obligations by the electricity sector for more sustainable generation and delivery processes to reduce the environmental footprint. However, there is still a long way to go to achieve necessary sustainability goals while ensuring standards of robustness and the quality of power grids. One of the main challenges hindering this progress are uncertainties and stochasticity associated with the electricity sector and especially renewable generation. In this paradigm shift, forecasting tools are indispensable, and their utilization can significantly improve system operation and minimize costs associated with all related activities. Thus, forecasting tools have an essential key role in all decision-making stages. In this work, a hybrid probabilistic forecasting model (HPFM) was developed for short-term electricity market prices (EMP) combining wavelet transforms (WT), hybrid particle swarm optimization (DEEPSO), adaptive neuro-fuzzy inference system (ANFIS), and Monte Carlo simulation (MCS). The proposed hybrid probabilistic forecasting model (HPFM) was tested and validated with real data from the Spanish and Pennsylvania-New Jersey-Maryland (PJM) markets. The proposed model exhibited favorable results and performance in comparison with previously published work considering electricity market prices (EMP) data, which is notable.

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“…By combining Equations (1) and (2), and discretizing, the more computationally efficient discrete WT (DWT) can be obtained and is expressed as:…”

Section: Wavelet Transforms (Wt)mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Hybrid Forecasting Model for Short-Term Electricity Market Prices with Renewable Integration

et al. 2018

View full text Add to dashboard Cite

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“…Zhang and Domínguez-García [28] and Pathak et al [29] discussed the influence of time delay to AGC performance, respectively. Some other scholars think of the time delays as a system constraint in AGC process [11,[30][31][32]. But the analyses of delays' characteristics and the discussion of delays' processing method are not sufficient in these research studies.…”

Section: Introductionmentioning

confidence: 98%

A Distributed AGC Method considering Two-Channel Random Delays and Their Difference between Interconnected Power Systems

Zhao

Lin

et al. 2019

Journal of Electrical and Computer Engineering

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With the emergence of the concept of smart grid, the networked automatic generation control (AGC) method has been more and more important for secondary frequency control due to its characteristics such as openness and flexibility. However, the networked AGC system also presents some defects such as time delays and packet dropouts. The existence of time delays makes the traditional AGC strategies more challenging. A novel AGC method is proposed in this paper to mitigate the negative effects of time delays. Firstly, a multiarea power system model is built under the consideration of two-channel time delays: from controller to actuator and from sensor to controller. More practically, the difference of delays between areas is also exhibited in the model. Thus, from the predictive characteristics of model predictive control (MPC), a method of selection with optimization is presented to obtain the appropriate control variable when delays exist. Furthermore, three cases, (a) no processing for delay, (b) control sequence selection, (c) control sequence selection with optimization, are analyzed. The frequency and area control error (ACE) performance are evaluated with step load perturbation and random load perturbation. The simulation results indicate that the system controlled by the proposed method has desired dynamic performances. Consequently, the feasibility and effectiveness of the proposed method are verified.

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“…In HPWH, the power consumption of the appliance can be controlled during water heating through appropriate control signals of the control centre. Frequency control using EVs is well addressed in the literature for primary control [9,10] and secondary control [11][12][13] of power systems. Meanwhile, there is a lack of study of the HPWH contribution to LFC in power systems.…”

Section: Introductionmentioning

confidence: 99%

Model Predictive-Based Secondary Frequency Control Considering Heat Pump Water Heaters

2019

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The extensive development of renewable energies in power systems causes several problems due to intermittent output power generation. To tackle the challenge, demand response contribution to ancillary service is currently well recognized under the smart grid infrastructure. The application of the heat pump water heater (HPWH) as a controllable load in primary frequency control is well presented in the literature; however, the motivation of this paper is to use HPWHs for secondary frequency control. To this end, a model predictive control (MPC) method for a two-area power system incorporating HPWHs to contribute to secondary frequency control is proposed in this paper. A detailed model of HPWH is employed as a controllable load to control the power consumption during water heating. The MPC method predicts the future control signals using a quadratic programming-based optimization. It uses the system model, past inputs and outputs, as well as system control signals to predict the next signals. The effective performance of the proposed method for the two-area power system with HPWH is demonstrated for different scenarios of load changes, intermittent renewable power generation and parameter variations as the sensitivity analysis.

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Secondary Load Frequency Control of Time-Delay Stand-Alone Microgrids With Electric Vehicles

Cited by 179 publications

References 21 publications

Hybrid Forecasting Model for Short-Term Electricity Market Prices with Renewable Integration

Hybrid Forecasting Model for Short-Term Electricity Market Prices with Renewable Integration

A Distributed AGC Method considering Two-Channel Random Delays and Their Difference between Interconnected Power Systems

Model Predictive-Based Secondary Frequency Control Considering Heat Pump Water Heaters

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