Journal of Operation and Automation in Power Engineering
Volume:11 Issue: 4, Winter 2023

Nowadays, in order to improve the dynamic performance of power networks and frequency control, LFC system is used in power plants. The presence of photovoltaic (PV) and wind turbine (WT) sources causes momentary changes in production and complicates the network frequency control process. In this paper, the random programming method with the Latin hypercube sampling pattern (LHS) is used to model the uncertainties of generating PV and PW sources. Also, to reduce the impact of the uncertainty of PV and PW sources on the frequency fluctuation, superconducting magnetic energy storage (SMES) has been used. Due to the fast dynamic response and favorable inertia characteristic of SMES, the performance of LFC and the stability of the system have been ameliorated. The simulation results in MATLAB software show that by step changes in the system load to the value of 0.1 pu, in the presence of SMES storage, the maximum overshoot value and the settling time of the system frequency are 16 percent and 3.2 seconds less, respectively.

In High Voltage Direct Current Transmission (HVDC) system, converter transformer is an integral part of the system. Generally, core loss, copper loss and stray losses occur in the transformer.  In which stray losses are produced in the transformers metallic parts such as transformer tank which can be 10\% to 15\% of the total loss. Experimentally, stray losses are difficult to measure. So, it is essential to use numerical modelling to predict the stray loss. The secondary winding of the converter transformer is directly linked to the rectifier or inverter. As a result, the converter transformer winding's current is non-sinusoidal. Due to non-sinusoidal current, losses are more in converter transformer than in~the power transformer. This article analyses the stray loss reduction techniques by applying wall shunt on the transformer tank surface. These stray losses are estimated for different wall shunt thickness values by varying the thickness of wall shunt using parametric analysis in 3-D finite-element analysis (FEA). Two types of wall shunts is used:-horizontal and vertical. In which horizontal wall shunt results are compared with the vertical wall shunt for non-sinusoidal and sinusoidal current excitation, where sinusoidal excitation is a fundamental component of non-sinusoidal excitation. For a case study, 315 MVA converter transformer is used to estimate stray losses on this transformer. The results obtained by the numerical method are also compared with the analytical method. Result shows that the stray losses are decreased with an increase in wall shunt thickness. Also, these losses are less for sinusoidal excitation than the non-sinusoidal excitation.

A sampling method is proposed related to-system state transition based Monte Carlo simulation (SSTMCS) for the adequacy assessment in the radial distribution system (RDS) in the presence of distributed generation (DG) termed as a composite distribution system (CDS). This method evaluates well-being indices such as probabilities, frequency, and duration indices in healthy, marginal, and risky states. A deterministic criterion is used for adequacy assessment. Samples are generated using a load flow program for RDS used in SSTMCS. The loss sensitivity factor is utilized for the positioning of DGs in RDS. DG capacity and load at buses are considered continuous random variables. Different cases are addressed to demonstrate the impact of varying DG capacities on well-being indices. Moreover, the results are compared with the state enumeration method (SEM). IEEE-33 bus RDS is considered for this study.

The Switched Reluctance Motors (SRMs) not only are low cost for industry applications, but ‎also they could work in various conditions with high reliability and efficiency. However, usage ‎of these motors in high speeds applications under discrete mode causes decreasing the ‎efficiency. In this paper, a new optimized control method based on the various Torque Sharing ‎Functions (TSFs) and optimization algorithms is proposed for Minimum Torque Ripple Point ‎Tracking (MTRPT) of a 4-phase SRM with 6/8 poles. In this method, turn-on and commutation angles are controlled based on the lookup table. The proposed method could adjust the rapid variations of the current in the starting mode of SRM. To show the robustness of the proposed approach, a real case study is considered, the control method is applied in an Electric Vehicle (EV) mechanism, and its performance is assessed in various motion states such as acceleration, breakage, and steady-state. Also, the position sensor for the studied EV is ‎neglected, which could reduce the extra costs. There are two various scenarios considered for solving the problem. First, the turn-off and turn-on angles are controlled, and the commutation angle is fixed. The results show the ‎robustness of the proposed method with about 90 \% diminishing the torque ripple, compared to ‎when all mentioned angles are fixed. In the second step, based on a lookup table, instead of using ‎complex analytical methods, the turn-on angle is controlled. Therefore, a variable turn-on ‎angle ‎proportional to the applied speed is applied to the commutation control system of SRM. Besides, ‎a lookup table is created to restrain the reduction of the turn-off angle. The simulation results are ‎compared to other previous methods, and the worth of the proposed method is shown.‎

In this paper, a new single-phase single-stage high step-up boost inverter appropriate for photovoltaic systems is proposed. In the proposed inverter, the duty cycle of one of the switches is adjusted to control the output voltage and increase the gain. In this structure, the dynamic model is adopted as an appropriate model to describe the low-frequency behavior of converters and extract the equations. Moreover, in this topology, a common ground is used between the input and output which can remove leakage current in different applications, including grid-connected applications. The proposed inverter is simulated using MATLAB/SIMULINK, and the experimental results are presented to verify the theoretical analysis.

Nowadays, the use of electric vehicles (EVs), in the form of distributed generation, as an appropriate solution is considered to replace combustion vehicles by reducing fuel consumption and supplying needed power. In this regard, the incorporation of EVs charging stations (EVCSs) in the power network can affect the distribution networks in different ways. On the other hand, the location of EVCS in distribution networks changes operational parameters includes electrical losses, and voltage deviations. Also, the probabilistic and uncertain behaviour of the loads and their daily changes can play a significant role on power distribution networks. To this end, in this paper, first, the modelling of the EVCSs affected by the behaviour of the EVs’ owner in a power distribution network is discussed. Then, the optimal location and size of EVCSs to reduce their negative effects on the network, including network losses (active and reactive) and voltage deviations are addressed in the presence of uncertain loads. The probabilistic model is investigated based on using the Monte Carlo simulation (MCS) method. The simulation results in MATLAB software environment show a 10% increase in active and reactive power losses in most hours of the day, due to increased power flow, when EVCSs are located in the optimal placement. The power losses at 24:00-7:00. when the EVs load is very low, are reduced due to decreased power flow across the lines. The results also show that if the EVCSs are not optimally located, the voltage deviation will increase by an average of 30% over a day, while by optimal placement of EVCSs, the voltage deviation increases to a maximum of 8% of the nominal value.

Nowadays, the centralized power system is changing to a distributed system, and various energy management systems are being installed for efficient functioning. Load side management is a vital aspect of the energy management of the power network. As residential demand is growing at a high rate, domestic customers play a crucial role in the successful implementation of demand response (DR) programs. This paper considers a single customer having a home energy management system (HEMS) for thermostatic and non-thermostatic characteristics-based appliances, photovoltaic panels, an electric vehicle, and a battery energy storage system. The effect of various DR strategies has been discussed. A mixed-integer linear programming-based model of a HEMS is modulated and solved to minimize the electricity consumption cost by employing a real-time price-based DR program using dynamic power import limits. An incentive-based DR program is considered for reducing the energy demand and maintaining the energy balance during peak hours, and peak pricing-based dynamic power import limiting DR programs are included for load shaping. The effect of load shaping on the peak to average ratio is also discussed in different scenarios. Finally, the total electricity price is calculated and analyzed by considering other test cases based on the inclusion/rejection of the mentioned DR programs.

The autonomous microgrid can incur a stability issue due to the low inertia offered by power electronics-based distributed generating sources of the microgrid. Due to the fast dynamics of inverters and the intermittent nature of renewables, the first phase of abrupt load change might not be shared evenly by DGs, and the system's stability deteriorates substantially. Hence the stability of the microgrid can greatly influenced by the load dynamics because of the inertialess generating sources. This paper presents a stability analysis of microgrid considering passive, active, and dynamic loads fed by inverter-based DGs. The small-signal analysis demonstrates the effect of inverter parameters and load factors. The dominance of states in oscillatory mode is examined by participation analysis. The results show that passive load does not introduce low-frequency mode, whereas rectifier interfaced active load (RIAL) introduces low-frequency mode due to DC voltage controller. The induction motor (IM) load introduces less damped eigenvalues in the microgrid and profoundly affects the real power-sharing of the system. The time-domain results verify the results obtained through eigenvalue analysis.