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Prof. Dr. Srete Nikolovski
Faculty of electrical engineering, computer science and information technology

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Research Keywords & Expertise

0 Arc Flash
0 Reliability Analysis
0 Power System Harmonics
0 Power System Analysis and Simulation
0 Active Distribution Networks

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Protection coordination
Reliability Analysis
Arc Flash
Active Distribution Networks

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Short Biography

Dr Srete Nikolovski, work from 1978-1991 in Electrical maintenance department of Kombinat Borovo. In 1989 he received his MSc degree from the Faculty of Electrical Engineering in Belgrade. In 1990 he started at the FTF in Osijek On 1993 he earned PhD degree from the FER, University of Zagreb. He was appointed assistanat prof. in 1996 and associate prof. in 2000, full prof. in 2005 and tenured full professor in 2010 at Faculty of Electrical Engineering, Computer science and information technology Osijek. In 2019 was elected as Scientific advisor in Tenure from AZVO agency. His main interest are: Power system reliability, protection, modeling and integration of DG in distribution networks, arc-flash risk assessment. He made 68 projects for industry and grid companies and more then 300 papers in Journals and conferences.Senior IEEE membe

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Journal article
Published: 01 June 2021 in Energies
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Direct current microgrids are attaining attractiveness due to their simpler configuration and high-energy efficiency. Power transmission losses are also reduced since distributed energy resources (DERs) are located near the load. DERs such as solar panels and fuel cells produce the DC supply; hence, the system is more stable and reliable. DC microgrid has a higher power efficiency than AC microgrid. Energy storage systems that are easier to integrate may provide additional benefits. In this paper, the DC micro-grid consists of solar photovoltaic and fuel cell for power generation, proposes a hybrid energy storage system that includes a supercapacitor and lithium–ion battery for the better improvement of power capability in the energy storage system. The main objective of this research work has been done for the enhanced settling point and voltage stability with the help of different maximum power point tracking (MPPT) methods. Different control techniques such as fuzzy logic controller, neural network, and particle swarm optimization are used to evaluate PV and FC through DC–DC boost converters for this enhanced settling point. When the test results are perceived, it is evidently attained that the fuzzy MPPT method provides an increase in the tracking capability of maximum power point and at the same time reduces steady-state oscillations. In addition, the time to capture the maximum power point is 0.035 s. It is about nearly two times faster than neural network controllers and eighteen times faster than for PSO, and it has also been discovered that the preferred approach is faster compared to other control methods.

ACS Style

Subramanian Vasantharaj; Vairavasundaram Indragandhi; Vairavasundaram Subramaniyaswamy; Yuvaraja Teekaraman; Ramya Kuppusamy; Srete Nikolovski. Efficient Control of DC Microgrid with Hybrid PV—Fuel Cell and Energy Storage Systems. Energies 2021, 14, 3234 .

AMA Style

Subramanian Vasantharaj, Vairavasundaram Indragandhi, Vairavasundaram Subramaniyaswamy, Yuvaraja Teekaraman, Ramya Kuppusamy, Srete Nikolovski. Efficient Control of DC Microgrid with Hybrid PV—Fuel Cell and Energy Storage Systems. Energies. 2021; 14 (11):3234.

Chicago/Turabian Style

Subramanian Vasantharaj; Vairavasundaram Indragandhi; Vairavasundaram Subramaniyaswamy; Yuvaraja Teekaraman; Ramya Kuppusamy; Srete Nikolovski. 2021. "Efficient Control of DC Microgrid with Hybrid PV—Fuel Cell and Energy Storage Systems." Energies 14, no. 11: 3234.

Journal article
Published: 19 March 2021 in Energies
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The role of renewable energy sources in the power grid is increasing tremendously. However, power electronic converters are used to incorporate RES into the grid without inertia. This article recommends an improved emulated inertia control approach focused on the frequency deviation and rate of change of frequency to enhance the inertia of a power system. The required inertial power calculated from emulated inertia control is delivered through hybrid energy storage systems equipped with a proper hybrid energy storage system control. The fast-varying power calculated from emulated inertia control is linked to super-capacitor. Simultaneously, the battery handles the slow varying power by regulating the DC bus voltage proportionate to the frequency variations. Further, the stability of the emulated inertia control and hybrid energy storage system controller is validated by Bode plots. The simulation results verified the correctness of the proposed emulated inertia control and hybrid energy storage system control. The real-time simulation results with the help of OPAL-RT are presented to validate the proposed method’s feasibility.

ACS Style

Ratnam Sarojini; Palanisamy Kaliannan; Yuvaraja Teekaraman; Srete Nikolovski; Hamid Baghaee. An Enhanced Emulated Inertia Control for Grid-Connected PV Systems with HESS in a Weak Grid. Energies 2021, 14, 1721 .

AMA Style

Ratnam Sarojini, Palanisamy Kaliannan, Yuvaraja Teekaraman, Srete Nikolovski, Hamid Baghaee. An Enhanced Emulated Inertia Control for Grid-Connected PV Systems with HESS in a Weak Grid. Energies. 2021; 14 (6):1721.

Chicago/Turabian Style

Ratnam Sarojini; Palanisamy Kaliannan; Yuvaraja Teekaraman; Srete Nikolovski; Hamid Baghaee. 2021. "An Enhanced Emulated Inertia Control for Grid-Connected PV Systems with HESS in a Weak Grid." Energies 14, no. 6: 1721.

Journal article
Published: 02 August 2020 in Energies
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This article focuses on addressing the data aggregation faults caused by the Phasor Measuring Unit (PMU) by installing Wireless Sensor Networks (WSN) in the grid. All data that is monitored by PMU should be sent to the base station for further action. But the data that is sent from PMU does not reach the main server properly in many situations. To avoid this situation, a sensor-based technology has been introduced in the proposed method for sensing the values that are monitored by PMU. Also, the basic parameters that are necessary for determining optimal solutions like energy consumption, distance and cost have been calculated for wireless sensors, whereas, for PMU optimal placements with cost analysis have been restrained. For analyzing and improving the accuracy of the proposed method, an effective Binary Logistic Regression (BLR) algorithm has been integrated with an objective function. The sensor will report all measured PMU values to an Online Monitoring System (OMS). To examine the effectiveness of the proposed method, the examined values are visualized in MATLAB and results prove that the proposed method using BLR is more effective than existing methods in terms of all parametric values and the much improved results have been obtained at a rate of 81.2%.

ACS Style

Hariprasath Manoharan; Yuvaraja Teekaraman; Irina Kirpichnikova; Ramya Kuppusamy; Srete Nikolovski; Hamid Reza Baghaee. Smart Grid Monitoring by Wireless Sensors Using Binary Logistic Regression. Energies 2020, 13, 3974 .

AMA Style

Hariprasath Manoharan, Yuvaraja Teekaraman, Irina Kirpichnikova, Ramya Kuppusamy, Srete Nikolovski, Hamid Reza Baghaee. Smart Grid Monitoring by Wireless Sensors Using Binary Logistic Regression. Energies. 2020; 13 (15):3974.

Chicago/Turabian Style

Hariprasath Manoharan; Yuvaraja Teekaraman; Irina Kirpichnikova; Ramya Kuppusamy; Srete Nikolovski; Hamid Reza Baghaee. 2020. "Smart Grid Monitoring by Wireless Sensors Using Binary Logistic Regression." Energies 13, no. 15: 3974.

Journal article
Published: 09 March 2020 in Energies
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A main focus in microgrids is the power quality issue. The used renewable sources fluctuate and this fluctuation has to be suppressed by designing a control variable to nullify the circulating current caused by voltage fluctuations and deviations. The switching losses across power electronic switches, harmonics, and circulating current are the issues that we discuss in this article. The proposed intelligent controller is an interface between a voltage-sourced converter and a utility grid that affords default switching patterns with less switching loss, less current harmonic content, and overcurrent protection, and is capable of handling the nonlinearities and uncertainties in the grid system. The interfaced controller needs to be synchronized to a utility grid to ensure that the grid–lattice network can be fine-tuned in order to inject/absorb the prominent complex reactive energy to/from the utility grid so as to maintain the variable power factor at unity, which, in turn, will improve the system’s overall efficiency for all connected nonlinear loads. The intelligent controller for stabilizing a smart grid is developed by implementing a fuzzy-built advance control configuration to achieve a faster dynamic response and a more suitable direct current link performance. The innovation in this study is the design of fuzzy-based space vector pulse width modulation controller that exploits the hysteresis current control and current compensation in a grid-connected voltage source converter. By using the proposed scheme, a current compensation strategy is proposed along with an advanced modulation controller to utilize the DC link voltage of a voltage source converter. To demonstrate the effectiveness of the proposed control scheme, offline digital time-domain simulations were carried out in MATLAB/Simulink, and the simulated results were verified using the experimental setup to prove the effectiveness, authenticity, and accuracy of the proposed method.

ACS Style

Yuvaraja Teekaraman; Ramya Kuppusamy; Hamid Reza Baghaee; Marko Vukobratović; Zoran Balkić; Srete Nikolovski. Current Compensation in Grid-Connected VSCs using Advanced Fuzzy Logic-based Fluffy-Built SVPWM Switching. Energies 2020, 13, 1259 .

AMA Style

Yuvaraja Teekaraman, Ramya Kuppusamy, Hamid Reza Baghaee, Marko Vukobratović, Zoran Balkić, Srete Nikolovski. Current Compensation in Grid-Connected VSCs using Advanced Fuzzy Logic-based Fluffy-Built SVPWM Switching. Energies. 2020; 13 (5):1259.

Chicago/Turabian Style

Yuvaraja Teekaraman; Ramya Kuppusamy; Hamid Reza Baghaee; Marko Vukobratović; Zoran Balkić; Srete Nikolovski. 2020. "Current Compensation in Grid-Connected VSCs using Advanced Fuzzy Logic-based Fluffy-Built SVPWM Switching." Energies 13, no. 5: 1259.

Journal article
Published: 28 November 2019 in Energies
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With the ever-growing power demand, the energy efficiency in commercial and residential buildings is a matter of great concern. Also, strategic energy auditing (SEA) and demand-side management (DSM) are cost-effective means to identify the requirements of power components and their operation in the energy management system. In a commercial or residential building, the major components are light sources and heating, ventilation, and air conditioning. The number of these components to be installed depends upon the technical and environmental standards. In this scenario, energy auditing (EA) allows identifying the methods, scope, and time for energy management, and it helps the costumers to manage their energy consumption wisely to reduce electricity bills. In the literature, most of the traditional strategies employed specific system techniques and algorithms, whereas, in recent years, load shifting-based DSM techniques were used under different operating scenarios. Considering these facts, the energy data in a year were collected under three different seasonal changes, i.e., severe cold, moderate, and severe heat for the variation in load demand under different environmental conditions. In this work, the energy data under three conditions were averaged, and the DSM schemes were developed for the operation of power components before energy auditing and after energy auditing. Moreover, the performance of the proposed DSM techniques was compared with the practical results in both scenarios, and, from the results, it was observed that the energy consumption reduced significantly in the proposed DSM approach.

ACS Style

Pawan Kumar; Gagandeep Singh Brar; Surjit Singh; Srete Nikolovski; Hamid Reza Baghaee; Zoran Balkić. Perspectives and Intensification of Energy Efficiency in Commercial and Residential Buildings Using Strategic Auditing and Demand-Side Management. Energies 2019, 12, 4539 .

AMA Style

Pawan Kumar, Gagandeep Singh Brar, Surjit Singh, Srete Nikolovski, Hamid Reza Baghaee, Zoran Balkić. Perspectives and Intensification of Energy Efficiency in Commercial and Residential Buildings Using Strategic Auditing and Demand-Side Management. Energies. 2019; 12 (23):4539.

Chicago/Turabian Style

Pawan Kumar; Gagandeep Singh Brar; Surjit Singh; Srete Nikolovski; Hamid Reza Baghaee; Zoran Balkić. 2019. "Perspectives and Intensification of Energy Efficiency in Commercial and Residential Buildings Using Strategic Auditing and Demand-Side Management." Energies 12, no. 23: 4539.

Journal article
Published: 10 November 2019 in Energies
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This paper presents an intelligent electronic device (IED) utilized for automatic meter readings (AMR) scheme using “Open-Source” software. This IED is utilized to measure a low-voltage intelligent electronic device) system with a boundless number of sensors, and it is accessible on the Internet of Things (IoT). The utilized equipment for this task is Arduino UNO R3 motherboard and fringe sensors, which are used for measurement of the referenced information. The Arduino motherboard is used not only for sole tranquility of equipment but also for serving as wireless fidelity (Wi-Fi) switch for the sensors. The personal computer is utilized to gather information and perform client-side calculations. The server works based on an open-source program written in Java programming language. The underlying objective of the proposed scheme is to make the meter based on the “Do It Yourself” methodology which requires considerably fewer funds. Also, it is conceivable by keeping easy to understand interface, information legitimacy, precision of measured information and convenience for the conclusive client. The information is measured in just about 1 ms which is superb for custom-designed IED. Furthermore, the measured qualities are calculated based on their RMS values to be used for analyzing and further presentation of data.

ACS Style

Dragan Mlakić; Hamid Reza Baghaee; Srete Nikolovski; Marko Vukobratović; Zoran Balkić. Conceptual Design of IoT-Based AMR Systems Based on IEC 61850 Microgrid Communication Configuration Using Open-Source Hardware/Software IED. Energies 2019, 12, 4281 .

AMA Style

Dragan Mlakić, Hamid Reza Baghaee, Srete Nikolovski, Marko Vukobratović, Zoran Balkić. Conceptual Design of IoT-Based AMR Systems Based on IEC 61850 Microgrid Communication Configuration Using Open-Source Hardware/Software IED. Energies. 2019; 12 (22):4281.

Chicago/Turabian Style

Dragan Mlakić; Hamid Reza Baghaee; Srete Nikolovski; Marko Vukobratović; Zoran Balkić. 2019. "Conceptual Design of IoT-Based AMR Systems Based on IEC 61850 Microgrid Communication Configuration Using Open-Source Hardware/Software IED." Energies 12, no. 22: 4281.

Journal article
Published: 22 July 2019 in Energies
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Voltage and frequency regulation is one of the greatest challenges for proper operation subsequent to the isolated microgrid. To validate the satisfactory electric power quality supply to customers, the proposed manuscript tries to enhance the quality of energy provided by DG (Distributed generation) units connected to the subsequent isolated grid. Microgrid and simulation-based control structure including voltage and current control feedback loops is proposed for microgrid inverters to recover voltage and frequency of the system subsequently for any fluctuations in load change. The proportional-integral (PI) controller connected to the voltage controller is an end goal to obtain smooth response in most of the consistent frameworks. The present controller creates the space vector pulse width modulation signals which are given to the three-leg inverter. The objective elements of the multiobjective optimization issue are voltage overshoot and undershoot, rise time, settling time, and integral time absolute error (ITAE). The hybrid Multiobjective Symbiotic Organism Search (MOSOS) calculation is associated for self-tuning of control parameters keeping in mind the end goal to deal with the voltage and frequency. The proposed PI controller, along with the hybrid Multiobjective Symbiotic Organism Search algorithm, provides the solution for the greatest challenge of voltage and frequency regulation in an isolated-microgrid operation.

ACS Style

Yuvaraja Teekaraman; Ramya Kuppusamy; Srete Nikolovski. Solution for Voltage and Frequency Regulation in Standalone Microgrid using Hybrid Multiobjective Symbiotic Organism Search Algorithm. Energies 2019, 12, 2812 .

AMA Style

Yuvaraja Teekaraman, Ramya Kuppusamy, Srete Nikolovski. Solution for Voltage and Frequency Regulation in Standalone Microgrid using Hybrid Multiobjective Symbiotic Organism Search Algorithm. Energies. 2019; 12 (14):2812.

Chicago/Turabian Style

Yuvaraja Teekaraman; Ramya Kuppusamy; Srete Nikolovski. 2019. "Solution for Voltage and Frequency Regulation in Standalone Microgrid using Hybrid Multiobjective Symbiotic Organism Search Algorithm." Energies 12, no. 14: 2812.

Journal article
Published: 22 July 2019 in IEEE Systems Journal
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This paper presents a new approach for determining the impact of lightning strike currents on transmission network elements failures, based on fuzzy logic (FL) and expert systems. The location of lightning strike is determined by means of lightning location system (LLS) and failures in the transmission network, sorted by type of the equipment, are obtained from supervisory control and data acquisition (SCADA) system. The input data set includes two sets. The first set consists of lightning strike locations and current values between the cloud and the ground. The second set consists of current values from SCADA system before and after the fault, protection tripping information, and the state and position of the switches. The proposed FL-based solution is based on a fuzzy decision-making system (DMS), including both data sets in order to provide a power system operator (PSO) with a precise and accurate decision needed in time of emergency. The described model has been tested for functionality and correct results have been obtained, which confirms the membership function (MF) assessment and proves the efficiency and authenticity of the proposed DMS.

ACS Style

Ivica Petrovic; Srete Nikolovski; Hamid Reza Baghaee; Hrvoje Glavas. Determining Impact of Lightning Strike Location on Failures in Transmission Network Elements Using Fuzzy Decision-Making. IEEE Systems Journal 2019, 14, 2665 -2675.

AMA Style

Ivica Petrovic, Srete Nikolovski, Hamid Reza Baghaee, Hrvoje Glavas. Determining Impact of Lightning Strike Location on Failures in Transmission Network Elements Using Fuzzy Decision-Making. IEEE Systems Journal. 2019; 14 (2):2665-2675.

Chicago/Turabian Style

Ivica Petrovic; Srete Nikolovski; Hamid Reza Baghaee; Hrvoje Glavas. 2019. "Determining Impact of Lightning Strike Location on Failures in Transmission Network Elements Using Fuzzy Decision-Making." IEEE Systems Journal 14, no. 2: 2665-2675.

Journal article
Published: 21 June 2019 in IEEE Transactions on Smart Grid
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The cheap and reliable primal energy source for BESS refueling necessitates a special attention for combining RERs with PHEV charging stations in microgrids. Rapid charging is an operation mode of PHEV for drivers which demands fast recharging of BESSs of the electric cars. This charging mode manifests as low impedance short circuit at DC side, making power transient on power grid side. This paper presents a new anti-islanding protection scheme for LV VSC-based microgrids by exploiting SVMs. The proposed anti-islanding protection method exploits powerful classification capability of SVMs. The sensor monitors seven inputs measured at the PCC, namely RMS value of voltage and current (RMSV, RMSI), THD of voltage and current (THDV, THDI), frequency (f), and also active and reactive powers (P, Q). This approach is based on passive monitoring and therefore, it does not affect the PQ. In order to cover as many situations as possible, minimize false tripping and remain selective, training and detection procedures are simply introduced. Based on the presented sampling method and input model, the proposed method is tested under different conditions such as PHEV rapid charging, additional load change and multiple DGs at the same PCC. Simulations based on the model and parameters of a real-life practical PV power plant are performed in MATLAB/Simulink environment, and several tests are executed based on different scenarios and compared with previously-reported techniques, this analysis proved the effectiveness, authenticity, selectivity, accuracy and precision of the proposed method with allowable impact on PQ according to UL1741 standard, and its superiority over other methods.

ACS Style

Hamid Reza Baghaee; Dragan Mlakic; Srete Nikolovski; Tomislav Dragicevic. Anti-Islanding Protection of PV-Based Microgrids Consisting of PHEVs Using SVMs. IEEE Transactions on Smart Grid 2019, 11, 483 -500.

AMA Style

Hamid Reza Baghaee, Dragan Mlakic, Srete Nikolovski, Tomislav Dragicevic. Anti-Islanding Protection of PV-Based Microgrids Consisting of PHEVs Using SVMs. IEEE Transactions on Smart Grid. 2019; 11 (1):483-500.

Chicago/Turabian Style

Hamid Reza Baghaee; Dragan Mlakic; Srete Nikolovski; Tomislav Dragicevic. 2019. "Anti-Islanding Protection of PV-Based Microgrids Consisting of PHEVs Using SVMs." IEEE Transactions on Smart Grid 11, no. 1: 483-500.

Journal article
Published: 14 May 2019 in IEEE Journal of Emerging and Selected Topics in Power Electronics
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Many techniques used and still in usage for solving the problem of islanding detection are intrinsically passive, active, or hybrid of both. Each one of them has its own benefits and drawbacks. In this paper, we propose a method which takes the advantage of a ML-based algorithm, namely SVM, in order to produce the results more efficiently. The results of the simulations based on the model and experimentally-measured parameters of a real-life practical PV plant, gives much better output than the traditional reported methods. During the tests and simulations, an additional problem, namely grid fault emerged, posing new challenges for the proposed method. Occurrences of islanding and grid fault are grouped together with same kernel dimension and no custom hyper plane bordering. Discrimination between islanding and grid fault events is an essential dilemma which is handled by the proposed SVM-based algorithm to achieve more precision in islanding detection and simultaneously, detect the grid faults authentically. NDZs and DT are tested using two dimensions, namely the generated active energy from PV plant (0-110% of Pn), and distribution network voltage levels (± 10% of Un). Simulations based on the model and parameters of a real-life practical PV power plant are performed in MATLAB/Simulink environment and several tests are executed for several scenarios, Finally, comparisons with previously-reported techniques prove the effectiveness, authenticity, selectivity, accuracy and precision of the proposed islanding and grid fault detection strategy with allowable impact on power quality according to UL1741 and its superiority over other methods.

ACS Style

Hamid Reza Baghaee; Dragan Mlakic; Srete Nikolovski; Tomislav Dragicevi Dragicevic. Support Vector Machine-Based Islanding and Grid Fault Detection in Active Distribution Networks. IEEE Journal of Emerging and Selected Topics in Power Electronics 2019, 8, 2385 -2403.

AMA Style

Hamid Reza Baghaee, Dragan Mlakic, Srete Nikolovski, Tomislav Dragicevi Dragicevic. Support Vector Machine-Based Islanding and Grid Fault Detection in Active Distribution Networks. IEEE Journal of Emerging and Selected Topics in Power Electronics. 2019; 8 (3):2385-2403.

Chicago/Turabian Style

Hamid Reza Baghaee; Dragan Mlakic; Srete Nikolovski; Tomislav Dragicevi Dragicevic. 2019. "Support Vector Machine-Based Islanding and Grid Fault Detection in Active Distribution Networks." IEEE Journal of Emerging and Selected Topics in Power Electronics 8, no. 3: 2385-2403.

Journal article
Published: 27 April 2019 in Energies
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Stochastic production from wind power plants imposes additional uncertainty in power system operation. It can cause problems in load and generation balancing in the power system and can also cause congestion in the transmission network. This paper deals with the problems of congestion in the transmission network, which are caused by the production of wind power plants. An optimization model for corrective congestion management is developed. Congestions are relieved by re-dispatching several cascaded hydropower plants. Optimization methodology covers the optimization period of one day divided into the 24 segments for each hour. The developed optimization methodology consists of two optimization stages. The objective of the first optimization stage is to obtain an optimal day-ahead dispatch plan of the hydropower plants that maximizes profit from selling energy to the day-ahead electricity market. If such a dispatch plan, together with the wind power plant production, causes congestion in the transmission network, the second optimization stage is started. The objective of the second optimization stage is the minimization of the re-dispatching of cascaded hydropower plants in order to avoid possible congestion. The concept of chance-constrained programming is used in order to consider uncertain wind power production. The first optimization stage is defined as a mixed-integer linear programming problem and the second optimization stage is defined as a quadratic programming (QP) problem, in combination with chance-constrained programming. The developed optimization model is tested and verified using the model of a real-life power system.

ACS Style

Krešimir Fekete; Srete Nikolovski; Zvonimir Klaić; Ana Androjić. Optimal Re-Dispatching of Cascaded Hydropower Plants Using Quadratic Programming and Chance-Constrained Programming. Energies 2019, 12, 1604 .

AMA Style

Krešimir Fekete, Srete Nikolovski, Zvonimir Klaić, Ana Androjić. Optimal Re-Dispatching of Cascaded Hydropower Plants Using Quadratic Programming and Chance-Constrained Programming. Energies. 2019; 12 (9):1604.

Chicago/Turabian Style

Krešimir Fekete; Srete Nikolovski; Zvonimir Klaić; Ana Androjić. 2019. "Optimal Re-Dispatching of Cascaded Hydropower Plants Using Quadratic Programming and Chance-Constrained Programming." Energies 12, no. 9: 1604.

Journal article
Published: 01 April 2019 in Tehnicki vjesnik - Technical Gazette
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By determining the losses in the power system, the aim is to determine the difference between the theoretical values and the actual losses obtained by measuring, to determine the reason for this difference, and to propose a theoretical...

ACS Style

Ivica Petrović; Filip Mikulić; Zoran Baus; Srete Nikolovski; Dario Galić. A New Approach to Calculating Electrical Energy Losses on Power Lines with a New Improved Three-Mode Method. Tehnicki vjesnik - Technical Gazette 2019, 26, 1506 -1512.

AMA Style

Ivica Petrović, Filip Mikulić, Zoran Baus, Srete Nikolovski, Dario Galić. A New Approach to Calculating Electrical Energy Losses on Power Lines with a New Improved Three-Mode Method. Tehnicki vjesnik - Technical Gazette. 2019; 26 (2):1506-1512.

Chicago/Turabian Style

Ivica Petrović; Filip Mikulić; Zoran Baus; Srete Nikolovski; Dario Galić. 2019. "A New Approach to Calculating Electrical Energy Losses on Power Lines with a New Improved Three-Mode Method." Tehnicki vjesnik - Technical Gazette 26, no. 2: 1506-1512.

Journal article
Published: 31 January 2019 in Computers & Electrical Engineering
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This paper presents the model for finding an optimal joint bid of hydroelectric systems and wind parks on a day-ahead electricity market. The optimization problem is presented as a two-stage model where the goal of the first stage is to maximize the profit according to the main scenario and the obtained production plan is then tested in all other scenarios that can occur in the second stage where the goal is to minimize the profit reduction caused by imbalance penalties or changes in expected day-ahead prices. The optimization procedure is presented as a mixed integer linear optimization problem. The proposed model is applied in a case study in order to present the main model features. Production assembly in the case study is based on real power plants and consists of two cascade hydropower plants and two wind parks.

ACS Style

Goran Knežević; Danijel Topić; Marija Jurić; Srete Nikolovski. Joint market bid of a hydroelectric system and wind parks. Computers & Electrical Engineering 2019, 74, 138 -148.

AMA Style

Goran Knežević, Danijel Topić, Marija Jurić, Srete Nikolovski. Joint market bid of a hydroelectric system and wind parks. Computers & Electrical Engineering. 2019; 74 ():138-148.

Chicago/Turabian Style

Goran Knežević; Danijel Topić; Marija Jurić; Srete Nikolovski. 2019. "Joint market bid of a hydroelectric system and wind parks." Computers & Electrical Engineering 74, no. : 138-148.

Journal article
Published: 11 January 2019 in IEEE Systems Journal
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ACS Style

Srete Nikolovski; Hamid Reza Baghaee; Dragan Mlakic. Islanding Detection of Synchronous Generator-Based DGs using Rate of Change of Reactive Power. IEEE Systems Journal 2019, 13, 4344 -4354.

AMA Style

Srete Nikolovski, Hamid Reza Baghaee, Dragan Mlakic. Islanding Detection of Synchronous Generator-Based DGs using Rate of Change of Reactive Power. IEEE Systems Journal. 2019; 13 (4):4344-4354.

Chicago/Turabian Style

Srete Nikolovski; Hamid Reza Baghaee; Dragan Mlakic. 2019. "Islanding Detection of Synchronous Generator-Based DGs using Rate of Change of Reactive Power." IEEE Systems Journal 13, no. 4: 4344-4354.

Journal article
Published: 27 November 2018 in IEEE Transactions on Smart Grid
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One of the most crucial problems in distribution networks (DNs) is islanding detection. This paper presents a new Gibbs phenomenon-based hybrid method for islanding detection in low voltage (LV) DNs, which is essentially based on a combination of active and passive methods of frequency rate of change at a given moment and measurement of constant total harmonic distortion (THD). The proposed method exploits Gibbs phenomenon occurring at the interpolation of sinusoidal functions. Beside identification of Gibbs phenomenon, root mean square (RMS) of the voltage is tracked in parallel with THDU for firm islanding detection. Finally, to prove the effectiveness of the proposed islanding detection strategy, offline digital time-domain simulation studies have been performed on a test microgrid including voltage-sourced converter (VSC)-based renewable/ distributed energy resources (RERs/DERs) in MATLAB/Simulink environment for different configurations and load conditions and the results have been verified by comparing with previously-reported methods. The results indicate that the proposed method performs fast and precise islanding detection in both low-power and high-power LV microgrids with reasonable impact on power quality (PQ) according to EN 50160 standard. By combining these fields as active and passive techniques, the proposed hybrid method gives non detection zones (NDZs) and detection time (DT) much smaller compared with frequency-and harmonic-based individual islanding detection methods.

ACS Style

Dragan Mlakic; Hamid Reza Baghaee; Srete Nikolovski. Gibbs Phenomenon-Based Hybrid Islanding Detection Strategy for VSC-Based Microgrids Using Frequency Shift, $THD_{U}$ , and $RMS_{U}$. IEEE Transactions on Smart Grid 2018, 10, 5479 -5491.

AMA Style

Dragan Mlakic, Hamid Reza Baghaee, Srete Nikolovski. Gibbs Phenomenon-Based Hybrid Islanding Detection Strategy for VSC-Based Microgrids Using Frequency Shift, $THD_{U}$ , and $RMS_{U}$. IEEE Transactions on Smart Grid. 2018; 10 (5):5479-5491.

Chicago/Turabian Style

Dragan Mlakic; Hamid Reza Baghaee; Srete Nikolovski. 2018. "Gibbs Phenomenon-Based Hybrid Islanding Detection Strategy for VSC-Based Microgrids Using Frequency Shift, $THD_{U}$ , and $RMS_{U}$." IEEE Transactions on Smart Grid 10, no. 5: 5479-5491.

Article
Published: 29 October 2018 in Energies
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One of the most crucial and economically-beneficial tasks for energy customers is peak load curtailment. On account of the fast response of renewable energy resources (RERs) such as photovoltaic (PV) units and battery energy storage system (BESS), this task is closer to be efficiently implemented. Depends on the customer peak load demand and energy characteristics, the feasibility of this strategy may vary. When adaptive neuro-fuzzy inference system (ANFIS) is exploited for forecasting, it can provide many benefits to address the above-mentioned issues and facilitate its easy implementation, with short calculating time and re-trainability. This paper introduces a data-driven forecasting method based on fuzzy logic (FL) for optimized peak load reduction. First, the amount of energy generated by PV is forecasted using ANFIS which conducts output trend, and then, the BESS capacity is calculated according to the forecasted results. The trend of the load power is then decomposed in Cartesian plane into two parts, namely left and right from load peak, for the sake of searching for equal BESS capacity. Network switching sequence over consumption is provided by a fuzzy logic controller (FLC) considering BESS capacity and PV energy output. Finally, to prove the effectiveness of the proposed ANFIS-based peak power shaving/curtailment method, offline digital time-domain simulations have been performed on a test microgrid system using the data gathered from a real-life practical test microgrid system in the MATLAB/Simulink environment and the results have been experimentally verified by testing on a practical microgrid system with real-life data obtained from smart meters and also, compared with several previously-reported methods.

ACS Style

Srete Nikolovski; Hamid Reza Baghaee; Dragan Mlakić. ANFIS-Based Peak Power Shaving/Curtailment in Microgrids Including PV Units and BESSs. Energies 2018, 11, 2953 .

AMA Style

Srete Nikolovski, Hamid Reza Baghaee, Dragan Mlakić. ANFIS-Based Peak Power Shaving/Curtailment in Microgrids Including PV Units and BESSs. Energies. 2018; 11 (11):2953.

Chicago/Turabian Style

Srete Nikolovski; Hamid Reza Baghaee; Dragan Mlakić. 2018. "ANFIS-Based Peak Power Shaving/Curtailment in Microgrids Including PV Units and BESSs." Energies 11, no. 11: 2953.

Preprint
Published: 30 September 2018
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One of the most crucial and economically beneficial tasks for energy customer is peak load curtailment. On account of the fast response of renewable energy resources (RERs) such as photovoltaic (PV) units and battery energy storage system (BESS), this task is closer to be efficiently implemented. Depends on the customer peak load demand and energy characteristics, the feasibility of this strategy may warry. When adaptive neuro-fuzzy inference system (ANFIS) is exploited for forecasting, it can provide many benefits to address the above-mentioned issues and facilitate its easy implementation, with short calculating time and re-trainability. This paper introduces a data driven forecasting method based on fuzzy logic for optimized peak load reduction. First, the amount of energy generated by PV is forecasted using ANFIS which conducts output trend, and then, the BESS capacity is calculated according to the forecasted results. The trend of the load power is then decomposed in Cartesian plane into two parts, left and right from load peak, searching for BESS capacity equal. Network switching sequence over consumption is provided by a fuzzy logic controller (FLC) with respect to BESS capacity and PV energy output. Finally, to prove the effectiveness of the proposed ANFIS-based peak shaving method, offline digital time-domain simulations have been performed on a real-life practical test micro grid system in MATLAB/Simulink environment and the results have been experimentally verified by testing on a practical micro grid system with real-life data obtained from smart meter and also, compared with several previously-reported methods.

ACS Style

Srete Nikolovski; Hamid Reza Baghaee; Dragan Mlakić. A New ANFIS-based Peak Power Curtailment in Microgrids Including PV Units and BESSs. 2018, 1 .

AMA Style

Srete Nikolovski, Hamid Reza Baghaee, Dragan Mlakić. A New ANFIS-based Peak Power Curtailment in Microgrids Including PV Units and BESSs. . 2018; ():1.

Chicago/Turabian Style

Srete Nikolovski; Hamid Reza Baghaee; Dragan Mlakić. 2018. "A New ANFIS-based Peak Power Curtailment in Microgrids Including PV Units and BESSs." , no. : 1.

Journal article
Published: 24 July 2018 in IEEE Transactions on Smart Grid
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This paper presents a new islanding detection strategy for low-voltage (LV) inverter-interfaced microgrids based on adaptive neuro-fuzzy inference system (ANFIS). The proposed islanding detection method exploits the pattern recognition capability of ANFIS and its nonlinear mapping of relation between inputs. The ANFIS monitors seven inputs measured at point of common coupling (PCC), namely root-mean square (RMS) of voltage and current (RMSU and RMSI), total harmonic distortion (THD) of voltage and current (THDU and THDI), frequency (f), and also active and reactive powers (P, Q) that are experimentally obtained based on practical measurement in a real-life microgrid. The proposed method is composed of passive monitoring of the mentioned inputs and therefore, does not influence power quality (PQ); but considerably decreases non detection zones (NDZs). In order to cover as much situations as possible, minimizing false tripping and still remaining selective, type and number of samples are introduced. Here, one of the main goals is reducing NDZ by still keeping PQ in order. Based on the sampled frequency and number of samples, we find that the proposed method has less detection time and better accuracy, compared to the reported methods. Simulations performed in MATLAB/Simulink software environment and several tests performed based on different active load conditions and multiple distributed generation (DG)s, prove the effectiveness, authenticity, selectivity, accuracy and precision of the proposed method with allowable impact on PQ according to UL1741 standard.

ACS Style

Dragan Mlakic; Hamid Reza Baghaee; Srete Nikolovski. A Novel ANFIS-Based Islanding Detection for Inverter-Interfaced Microgrids. IEEE Transactions on Smart Grid 2018, 10, 4411 -4424.

AMA Style

Dragan Mlakic, Hamid Reza Baghaee, Srete Nikolovski. A Novel ANFIS-Based Islanding Detection for Inverter-Interfaced Microgrids. IEEE Transactions on Smart Grid. 2018; 10 (4):4411-4424.

Chicago/Turabian Style

Dragan Mlakic; Hamid Reza Baghaee; Srete Nikolovski. 2018. "A Novel ANFIS-Based Islanding Detection for Inverter-Interfaced Microgrids." IEEE Transactions on Smart Grid 10, no. 4: 4411-4424.

Journal article
Published: 01 April 2018 in International Journal of Electrical and Computer Engineering (IJECE)
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Photovoltaic (PV) modules play an important role in modern distribution networks; however, from the beginning, PV modules have mostly been used in order to produce clean, green energy and to make a profit. Working effectively during the day, PV systems tend to achieve a maximum power point accomplished by inverters with built-in Maximum Power Point Tracking (MPPT) algorithms. This paper presents an Adaptive Neuro-Fuzzy Inference System (ANFIS), as a method for predicting an MPP based on data on solar exposure and the surrounding temperature. The advantages of the proposed method are a fast response, non-invasive sampling, total harmonic distortion reduction, more efficient usage of PV modules and a simple training of the ANFIS algorithm. To demonstrate the effectiveness and accuracy of the ANFIS in relation to the MPPT algorithm, a practical sample case of 10 kW PV system and its measurements are used as a model for simulation. Modelling and simulations are performed using all available components provided by technical data. The results obtained from the simulations point to the more efficient usage of the ANFIS model proposed as an MPPT algorithm for PV modules in comparison to other existing methods.

ACS Style

Dragan Mlakić; Ljubomir Majdandžić; Srete Nikolovski. ANFIS Used as a Maximum Power Point Tracking Algorithm for a Photovoltaic System. International Journal of Electrical and Computer Engineering (IJECE) 2018, 8, 867 -879.

AMA Style

Dragan Mlakić, Ljubomir Majdandžić, Srete Nikolovski. ANFIS Used as a Maximum Power Point Tracking Algorithm for a Photovoltaic System. International Journal of Electrical and Computer Engineering (IJECE). 2018; 8 (2):867-879.

Chicago/Turabian Style

Dragan Mlakić; Ljubomir Majdandžić; Srete Nikolovski. 2018. "ANFIS Used as a Maximum Power Point Tracking Algorithm for a Photovoltaic System." International Journal of Electrical and Computer Engineering (IJECE) 8, no. 2: 867-879.

Journal article
Published: 08 March 2018 in J. of Electrical Engineering
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ACS Style

Dragan Mlakić; Srete Nikolovski; Ljubomir Majdandžić. Deep Learning Method and Infrared Imaging as a Tool for Transformer Faults Detection. J. of Electrical Engineering 2018, 6, 1 .

AMA Style

Dragan Mlakić, Srete Nikolovski, Ljubomir Majdandžić. Deep Learning Method and Infrared Imaging as a Tool for Transformer Faults Detection. J. of Electrical Engineering. 2018; 6 (2):1.

Chicago/Turabian Style

Dragan Mlakić; Srete Nikolovski; Ljubomir Majdandžić. 2018. "Deep Learning Method and Infrared Imaging as a Tool for Transformer Faults Detection." J. of Electrical Engineering 6, no. 2: 1.