This paper presents a multi-stage planning framework for analysis of stochastic distributed energy resources (DERs) comprising of solar, wind, and battery storage. The existing models do not consider penetration level analysis in conjunction with sizing, placement, and economic assessment. The main objective of this research is to embed all these dimensions of system planning in one structure. The first stage involves reliability constrained component sizing.  The second stage pertains to placement of DERs based on loss minimization and voltage profile. The third stage is the main thrust of this work which provides exhaustive economic evaluation and cost-benefit analysis. The novelty of this work lies in the consideration of penetration level in backdrop of all three stages. The proposed formulation is implemented on a 33-Bus radial distribution feeder located in Jaisalmer, Rajasthan, India. Four penetration levels viz. 10, 20, 40, and 60 percent have been investigated and analyzed under different planning scenarios. The results facilitate the determination of optimum penetration level.

Optimal power flow is an essential tool in the study of power systems. Distributed generation sources increase network uncertainties due to their random behavior, so the optimal power flow is no longer responsive and the probabilistic optimal power flow must be used. This paper presents a probabilistic optimal power flow algorithm using the Taguchi method based on orthogonal arrays and genetic algorithms. This method can apply correlations and is validated by simulation experiments in the IEEE 30-bus network. The test results of this method are compared with the Monte Carlo simulation results and the two-point estimation method. The purpose of this paper is to reduce the losses of the entire IEEE 30-bus network. The accuracy and efficiency of the proposed Taguchi correlation method and the genetic algorithm are confirmed by comparison with the Monte Carlo simulation and the two-point estimation method. Finally, with this method, we see a reduction of 5.5 MW of losses.

In recent years, DC microgrid has attracted considerable attention of the research community because of the wide usage of DC power-based appliances. However, the acceptance of DC microgrid by power utilities is still limited due to the issues associated with the development of a reliable protection scheme. The high magnitude of DC fault current, its rapid rate of rising and absence of zero crossing hinders achieving reliable protection in DC microgrid. Further, the intermittency associated with the non-conventional distributed generators demands adaptiveness under varying weather conditions. In this paper, the above-mentioned issues are addressed by developing a bagging tree-based protection approach for a multi-terminal DC microgrid. The proposed scheme addresses the intermittency associated with renewable sources. It performs the functions of mode detection, fault detection/classification, and faulty section identification using local information of current and voltage signals only. The same avoids the communication network related drawbacks like data loss and latency.

In the last decade, there has been a lot of focus on sustainable development in the electrical power industry to meet the growing energy demand. This has led to an increase in the integration of renewable energy sources (RES). In addition to being abundantly available, the RES offers advantages such as low environmental impact and increased social development of rural communities which are imperative for a sustainable society.  However, the selection of a particular generating resource or resource mix (RM) for an autonomous micro-grid is a complex problem that involves multiple conflicting factors. In this paper, a planning strategy for selecting an appropriate RM has been proposed. Seven RMs comprising different combinations of four generation/storage technologies such as solar photovoltaic array (SPVA), wind turbine (WT), diesel generator (DG) and battery storage (BS) have been considered. The planning is initiated with the determination of optimal component sizing for all seven RMs. The RMs are then analyzed with respect to four primary sustainability parameters i.e. economic, social, technical and environmental. The analysis is further enhanced by investigation of 13 sub-parameters as well. Thereafter, prioritization of RMs is carried out using two MCDM methods Best worst method (BWM) and PROMETHEE II. Finally, to assert the importance of weight assignment on RM ranking, sensitivity analysis is performed. In order to impart the practical aspect to analysis, the planning formulation is applied to a case study of the Thar desert, India. The results suggest that a combination of SPVA and BS provides the most optimum RM solution.

This work proposes a high step-up interleaved dc/dc topology utilizing a VM (voltage multiplier) cell suitable for PV applications. The VM cells D/C (Diode/Cap.) are cascaded among the phases to approach a high voltage gain. Besides, the voltage converting ratio of the presented structure can be improved by extending the VM cells and it also leads to drop in the normalized voltage stress throughout the switches and some diodes. Therefore, by utilizing a semiconductor (Switch/Diode) with a lower rating leads to a decline in system losses. Also, the efficiency of the suggested topology will be considerable and the overall cost can be decreased. To elaborate on the main benefits of the proposed topology, a comparison has been made across other literature regarding the efficiency, peak voltage throughout the semiconductors and voltage ratio of the converter. To prove the accuracy principle of operation of the suggested converter, two prototypes (for n=1, 2 stages) were built and tested at 350 W and 453 W with an operating frequency of about 40 kHz performed.

In distribution networks, failure to smooth the load curve leads to voltage drop and power quality loss. In this regard, electric vehicle batteries can be used to smooth the load curve. However, to persuade vehicle owners to share their vehicle batteries, we must also consider the owners' profits. A challenging problem is that existing methods do not take into account the vehicle owner demands including initial and final states of charge and arrival and departure times of vehicles. Another problem is that battery capacity of each vehicle varies depending on the type of vehicle; which leads to uncertainties in the charging and discharging dynamics of batteries. In this paper, we propose a modified mean-field method so that the load curve is smoothed, vehicle owner demands are met, and different capacities of electric vehicle batteries are considered. The simulation results show the effectiveness of the proposed method.

The progressive application of non-linear loads in distribution systems (DS) increases current harmonics flow in DS's apparatuses, especially distribution transformers (DTs). Since DTs' operating temperature rises due to the harmonics flow, their loading should be reduced such that the hot spot temperature (HST) is preserved under its permissible value. This means that DTs' available capacity is influenced by load harmonic content. In this paper, a novel formulation for DTs' failure rate in the presence of harmonics is presented as a function of load harmonic contents. Using the suggested equivalent failure rate, DTs' available capacity in harmonic polluted DS is mathematically formulated. Additionally, the presence of the harmonic increases the HST, leading to DTs' aging acceleration. Therefore, the impact of harmonic components on DTs' aging is arithmetically modeled. To evaluate the efficacy of the suggested reliability model, it is applied to three distinct DTs having respectively industrial, commercial, and residential loads. The obtained results indicate that the available capacity of DTs with the same rated capacity would be different regarding to their load harmonic contents. On the other hand, it is comprehended from the achieved results that the aging acceleration factor (Faa) of the DTs increases owing to their load harmonic contents.

Owing to the portability and flexibility of mobile energy storage systems (MESSs), they seem to be a promising solution to improve the resilience of the distribution system (DS). So, this paper presents a rolling optimization mechanism for dispatching MESSs and other resources in microgrids in case of a natural disaster occurrence. The proposed mechanism aims to minimize the total system cost based on the updated information of the status of the DS and transportation network (TN). In addition, the characteristics of the protection system in DS (i.e., relays with fixed protection settings), the constraints related to the protection coordination are examined under pre- and post-event conditions. The coordinated scheduling at each time step is formulated as a two-stage stochastic mixed-integer linear program (MILP) with temporal-spatial and operation constraints. The proposed model is carried out on the Sioux Falls TN and the IEEE 33-bus test system. The results demonstrate the effectiveness of MESS mobility in enhancing DS resilience due to the coordination of mobile and stationary resources.

An intelligent strategy for the protection of AC microgrids is presented in this paper. This method was halving to an initial signal processing step and a machine learning-based forecasting step. The initial stage investigates currents and voltages with a window-based approach based on the dynamic decomposition method (DDM) and then involves the norms of the signals to the resultant DDM data. The results of the currents and voltages norms are applied as features for a topology data analysis algorithm for fault type classifying in the AC microgrid for fault location purposes. The Algorithm was tested on a microgrid that operates with precision equal to 100% in fault classification and a mean error lower than 20 m when forecasting the fault location. The proposed method robustly operates in sampling frequency, fault resistance variation, and noisy and high impedance fault conditions.

This paper proposes two new soft-switching transformerless converters with high voltage conversion ratio. These proposed converters achieve soft-switching each with a single auxiliary resonant cell. The merit of these converters is reduced switching losses with lesser number of devices. The main switching devices are turned off with zero current switching (ZCS). Apart from the soft-switching feature, the voltage conversion ratio is increased in comparison with the existing topologies. The operating principles and the simulation results on 12V/200V/500W converter system are presented in this paper.

State estimation is used in power systems to estimate grid variables based on meter measurements. Unfortunately, power grids are vulnerable to cyber-attacks. Reducing cyber-attacks against state estimation is necessary to ensure power system safe and reliable operation. False data injection (FDI) is a type of cyber-attack that tampers with measurements. This paper proposes network reconfiguration as a strategy to decrease FDI attacks on distribution system state estimation. It is well-known that network reconfiguration is a common approach in distribution systems to improve the system’s operation. In this paper, a modified switch opening and exchange (MSOE) method is used to reconfigure the network. The proposed method is tested on the IEEE 33-bus system. It is shown that network reconfiguration decreases the power measurements manipulation under false data injection attacks. Also, the resilient configuration of the distribution system is achieved, and the best particular configuration for reducing FDI attacks on each bus is obtained.

The idea of a microgrid is created by utilizing more diverse ac or dc distributed generation (DG) sources along with an energy storage system (ESS) and loads. The most efficient and reliable selection of ac and dc microgrids is a hybrid ac/dc microgrid. The hybrid microgrid largely overcomes the shortcomings of standalone ac or dc microgrids. A bidirectional interlinking converter (BIC) is utilized in the interface for controlling power flow between subgrids. In order to improve voltage and frequency regulation with effective power sharing, the BIC based on the proposed control scheme is implemented for power flow between ac and dc sub-grid in Islanding mode. The control scheme is modified based on conventional droop control with voltage and frequency variation in order to improve bus voltage and frequency regulation with effective power sharing for intermittent sources. The operation of the islanded hybrid ac/dc microgrid is performed with solar, wind, and energy storage system under variable generation and load conditions. In order to make robustness of the system, there are considered different cases for generation and load scenarios. In the transient state, the overshoot and settling time of frequency and voltage are improved, as well as the frequency and voltage regulations are found within the permissible limit in the steady state. Furthermore, the corresponding variations are shown in tabular form in the simulation result. The actual data of solar irradiance and wind speed have been taken from the National Renewable Energy Laboratory. The performance of the system is verified in MATLAB/Simulink environment.

In modern infrastructure, the demand for DC power-based appliances is rapidly increasing, and this phenomenon has created a positive impact on the acceptance of the DC microgrid. However, due to numerous issues such as the absence of zero crossing, bidirectional behaviour of sources, and different magnitudes of fault current during grid connected and islanded modes of operation, protecting DC microgrid remains a difficult task. Apart from these challenges, intermittent conditions are also a major challenge. Under such type scenarios, shadow conditions in the solar based DERs will reduce the desired output of the solar panels simultaneously in wind based DERs will be affected due to the low pressure of air. In this type of circumstances threshold setting based overcurrent relays may fail to sense the operational dynamics of the system. Therefore, in this manuscript, an ensemble of decision tree-based protection scheme is proposed to provide immunity against the stochastic conditions under the varying natures of the fault resistance. A total of 7150 test cases have been considered for validation of the protection scheme and all modules have been tested.