Scientia Iranica
Volume:29 Issue: 3, May & Jun 2022

Solar photovoltaic (PV) systems with back-up battery energy storage system (BESS) mitigate power system related issues like ever-increasing load demand, power loss, voltage deviation and need for power system up-gradation as integration of electric vehicles (EVs) increases load while charging. This paper investigates the improvements of the system parameters like voltage, power loss and loading capabilities of IEEE-69 bus radial distribution system (RDS) with PV/BESS-powered EV charging stations (CSs). The RDS is divided into different zones depending on the total no. of EVs, EV charging time andavailable CS service time. One CS is assigned to each zone. An energy management strategy is developed to direct the power flow among the CS, PV panel, BESS, and the utility grid according to time of use of electricity price. The BESS is allowed to sell excess energy stored to the utility grid during peak hours. Multi-course teaching learning based multi-objective optimization (MCTLBO) is used to optimize the size of PV/BESS system and the locations of CSs in each zone in order to minimize both the annual CS operating cost and the system active power loss. The results validate the use of optimal PV/BESS to power CS for techno-economic improvement of the system.

 This paper proposes a fundamental approach for radiation pattern correction of the mutually coupled circular dipole antenna array (CDAA) using parametric assimilation technique. The effect of mutual coupling is an indispensable part of any practical design issue of the antenna array. Many analytical and numerical techniques have been put forward in the past few decades for the calculation, compensation and reduction of mutual coupling effect. This paper shows an accurate method for mutual coupling correction by using a recently proposed technique called parametric assimilation technique, where the values of mutual impedance are calculated and assimilated with the values of the desired radiation pattern. The proposed technique is cost-effective, less complicated and easy to implement while achieves better performance for mutually coupled circular dipole antenna array synthesis. Grey Wolf Optimization (GWO) algorithm is a state-of-the-art stochastic algorithm applied here to find the optimal values of the current excitation weights and the inter-element spacing between each element of the CDAA for the desired, uncorrected and corrected far-field radiation pattern synthesis. PSO and DE optimization-based statistical results are also reported to compare the results obtained by using GWO algorithm to confirm the outstanding performance of GWO algorithm based design.

This study is focused on assessing the effect of energy storage system (ESS) presence on security improvement of power systems hosting remarkable renewable energy resources. To this end, ESS presence is suitably included in security-constrained optimal power flow (SCOPF) model; the required technical amendments are hence considered. To launch a realistic model, ramping constraints of thermal units are also taken into account which limit the generators from completely responding to power shortfalls. Considering a high penetration level of renewable generations, different scenarios of outages in transmission lines and generators are simulated to measure the line outage distribution factor (LODF) and power transfer distribution factor (PTDF). also, in order to illustrate the economic impact of wind power generation curtailment and load shedding, two penalty parameters VWC and VOLL are considered in the model. Two test systems, including a PJM 5-bus system and an IEEE 24-bus RTS, are put under numerical studies to assess the possible impact of ESS on security improvement of the investigated systems. The obtained results are discussed in depth.

We introduce a novel Regularized Kernel Projection Pursuit Regression method which is a two-step nonlinearity encoding algorithm tailored for such very low dimensional problems as fatigue detection. This way, the data nonlinearity can be investigated from two different perspectives, first by transforming the data into a high dimensional intermediate space and then by using their spline estimations to the output variables which allows for a hierarchical unfolding of data. Experimental results on the SEED database shows an average RMSE value of 0.1080% and 0.1054% respectively for the temporal and posterior areas of the brain. Our method is also validated by conducting some experiments on Parkinson's disease prediction which further demonstrate the efficiency of our method for low-dimensional regression problems.Traditional off-the-shelf regression methods like SVR, KSVR, and GLM methods all require their link functions to be previously selected which limits their effectiveness for encoding the nonlinearity of a highly complex low dimensional data set. Moreover, conventional PPR does not deal with the very low dimensionality of data. This paper proposes a novel regression algorithm to address the encoding problem of a highly complex low dimensional data, which is usually encountered in bio-neurological prediction tasks like EEG based driving fatigue detection.

The penetration of distributed generation (DG) units in the radial distribution network (RDN) introduces complexity in active power loss allocation (LA) as it leads to reverse current in the network. This current makes power system bidirectional and brings difficulties in the decomposition of cross-terms of power loss equation. To overcome such complications, this paper proposes a new branch oriented LA technique which eliminates the impact of mutual-term mathematically from loss formulation without any assumptions and approximations. It establishes a direct relationship between the subsequent load currents of a branch and its two end voltages in terms of the complex power available at its load ends. The proposed LA scheme is found to be fair as regard to the topology of the RDN. Further, the implementation of DGs may increase/decrease power loss of a system. In order to provide the exact amount of loss reduction benefit to the DG owners (DGOs), a new DG remuneration strategy is developed in this paper which assigns either rewards/penalties to the DGOs after analysing their actual impact towards system loss reduction. The effectiveness of the proposed LA method is investigated against various established LA techniques using two different test systems i.e., 17-bus and 33-bus RDNs.

Wind turbines (WTs) with Permanent magnet synchronous generator (PMSG) are mostly integrated in power systems as popular energy conversion systems. From the machine-side converter (MSC) structure point of view, there are two types of PMSG-WTs: PMSG-WT with voltage source converter (VSC) as the MSC, and PMSG-WT with boost converter-diode rectifier as the MSC. The focus in this paper is on the control modification and dynamic and transient behavior improvement of PMSG-WTs with boost converter-diode rectifier. In this way, inner control loop of the boost converter current and outer control loop of generator speed are developed and extracted. Next, the boost converter control loop is modified by adding two auxiliary control signals, known as auxiliary damping signal and auxiliary compensation signal. The auxiliary damping signal modifies the boost converter current and provides a damping torque for inhibition of WT torsional oscillations. On the other hand, the auxiliary compensation signal, as the second auxiliary signal, limits the dc-link overvoltage during the voltage dip and amends the WT low voltage ride through capability. By modifying the wind turbine control through second auxiliary signal, the size, cost and rated energy of the required dc chopper resistance decrease considerably.

Locational Marginal Pricing (LMP) is arguably the most effective and commonly employed mechanism to provide the most reliable economic signal to market participants. Meanwhile, nodal prices depend on active power losses and transmission congestion which may be affected by harmonics pollution. In the conventional method, power system and loads are assumed linear and nodal prices are obtained by results of optimal power flow (OPF) at the power frequency. Harmonics lead to skin effect and increasing loss. Further, harmonic flowing in branches in a power network occupies transmission capacity. For providing more accurate signals to market participants and achieving more accurate nodal prices, harmonic effects on LMP are investigated and a framework is developed for LMP calculation in a harmonic polluted power system. In this framework, skin effect, losses, and congestion which can be arisen by harmonic pollution are modelled in optimal power flow (OPF) and are considered in LMP calculation. The proposed concept is implemented with 9-bus and 30-bus test systems while nodal price changes are also indicated.

Energy efficiency programs as an energy source with multiple advantages (low cost, more reliable and better clean) are considered as one of the most effective solutions to meet future energy needs. In this paper, energy efficiency programs are modelled as virtual sources of power generation to investigate their impacts on expanding transmission network and reactive power planning. A multi-stage model based on AC power flow has been used to indicate the possibility of postponing the investment actions as the investment deferral in transmission expansion problems. Two groups of regulatory support schemes are considered as investor income to promote participation in energy efficiency programs, namely purchasing certified emission reductions and shared saving model. In addition, two standard case studies (Garver & 46-bus Brazilian) are evaluated to demonstrate the promising potential of the proposed model in handling the planning problems of practical power systems. The simulation results show the effectiveness of the proposed model to solve such planning problems in the presence of energy efficiency programs.

Directional overcurrent relays (DOCRs) are the essential protective devices in distribution networks which are usually set without considering any contingencies. However, the current challenge in power systems is the existence of uncertainty and its unfavorable consequences. It sometimes appears that some elements simultaneously fail which makes other parts to be overloaded to the extent that it leads to cascading outages. Therefore, DOCRs may have mal-operation which ends in unwanted trips when there is no fault, or they may not operate in the case the fault is located within their reach point. In such cases, the coordination setting will need complex programming with many related non-linear inequality constraints. In this paper, a novel hybrid method is proposed based on multi-objective optimization including new objective functions by using the genetic algorithm (GA). Also, the cascading outages are considered in the presented method based on network data analysis. This approach is performed on distribution part of the IEEE 14-bus meshed system, and a real industrial radial feeder named TOSEE, located in Iran. The simulations have been implemented in MATLAB and PowerFactory-DIgSILENT software packages in different models, and the results are evaluated.

This paper proposes modelling and optimization of a new reluctance axial flux magnetic gear (RAMG) with stationary outer rotor and advantages of lower permanent magnet usage. Due to the less use of the PMs, this structure has a higher economic interest, more reliability, and very simple and robust structure than its conventional ones. Gear ratio and operating principles are extracted and verificated using 3-D finite element method (FEM) simulations. Finally, a parametric optimization is done based on effective dimensions in design procedure with maximum torque density objective function. The magnetic flux distributions of optimized RAMG are calculated by 3-D FEM, as well as static and dynamic magnetic torques are derived correspondingly.