Implementing Time-of-Use Demand Response Program in microgrid considering energy storage unit participation and different capacities of installed wind power

Penetration of wind units in Microgrid (MG) imposes remarkable challenges on MG operation. Demand Response Programs (DRPs) and Energy Storage Units are used by MG operators to address these challenges. This paper analyzes the effect of running the Time-of-Use Demand Response Program (TOU-DRP) on an isolated MG by considering different capacities of installed wind power with/without energy storage unit. The energy storage unit is deployed to cover the stochastic nature of wind generation unit. TOU-DRP is modeled based on price elasticity and customer benefit function in an isolated MG. Different levels of customers’ participation in TOU-DRP has also been studied and its effects on operation cost, unserved energy, and wind power spillage are investigated comprehensively. To verify the proposed model’s efficiency, the study is implemented on an 11-bus MG over a 24-h period for twelve detailed case studies. The case study results confirmed the effectiveness of the proposed model in running DRP and providing MG operator a general overview for optimal operation

Utilizing Sequential Action Control Method in GaN-Based High-Speed Drive for BLDC Motor

This paper presents a hybrid model–based control algorithm that combines Model Predictive Control (MPC) and Sequential Action Control (SAC) deployed in a high-speed drive for Brushless DC (BLDC) motor by using a DC-DC converter with Gallium Nitride (GaN) switches. GaN FETs are selected because of their higher speed and lower power loss as compared with traditional Si switches. In the proposed framework, SAC processes the initial values of the control variables as well as their time of application and their duration in MPC loop. After receiving the underlying estimation of future contribution from SAC, MPC consolidates it with current input and predicts future control values by using the system state space model. This hybrid control conserves control effort and reduces sensitivity to initial conditions. In this way, converter’s output voltage is controlled to produce the reference speed at the motor output. National Instrument PXIe-6356 module is utilized as the interface between software and hardware that is a multi-function, LabVIEW-compatible data acquisition device. The viability of the proposed hybrid optimization for the high-speed drive is confirmed numerically by utilizing MATLAB/Simulink and approved experimentally using a Gallium Nitride (GaN) half-bridge DC-DC converter

Correlation of solar power prediction considering the nominal operating cell temperature under partial shading effect

The steadily rising efficiency together with the accuracy of prediction in solar photovoltaic (PV) energy requires a deterministic reliability in the realistic PV characteristic’s prediction subject to climatic changes. This empirical-based research validates IEC 61853 and improves output power prediction of a solar PV module with considering nominal operating cell temperature (NOCT) using online infrared thermal camera at short range outside. The impact of NOCT consideration is investigated, in which the error can be as high as 10.4¿°C in comparison to non-NOCT. The objective is minimizing the power prediction error for the PV module, the significant parameters of the maximum power point tracking (MPPT) controller are used to evaluate the changes followed by the climatic-related parameters under partial shading condition. A set of non-parametric correlations are calculated using Spearman’s ¿ and Kendall t rank statistical methods to avoid experimental measurement difficulties and cost for an advanced output power prediction. Finally, the differences on the heat distribution of each cell, and its impact in the annual power prediction have been numerically and experimentally verified.Peer ReviewedPostprint (author's final draft

Correlation of solar power prediction considering the nominal operating cell temperature under partial shading effect

The steadily rising efficiency together with the accuracy of prediction in solar photovoltaic (PV) energy requires a deterministic reliability in the realistic PV characteristic’s prediction subject to climatic changes. This empirical-based research validates IEC 61853 and improves output power prediction of a solar PV module with considering nominal operating cell temperature (NOCT) using online infrared thermal camera at short range outside. The impact of NOCT consideration is investigated, in which the error can be as high as 10.4¿°C in comparison to non-NOCT. The objective is minimizing the power prediction error for the PV module, the significant parameters of the maximum power point tracking (MPPT) controller are used to evaluate the changes followed by the climatic-related parameters under partial shading condition. A set of non-parametric correlations are calculated using Spearman’s ¿ and Kendall t rank statistical methods to avoid experimental measurement difficulties and cost for an advanced output power prediction. Finally, the differences on the heat distribution of each cell, and its impact in the annual power prediction have been numerically and experimentally verified.Peer Reviewe