Power systems
Hamed Shadfar; Hamid Reza Izadfar
Abstract
One of the main components of a power transformer is the transformer insulation system, namely, transformer insulation oil and transformer insulation paper. Any failure can cause the transformer to fail temporarily or permanently. As a result, regular and non-destructive monitoring of transformers is ...
Read More
One of the main components of a power transformer is the transformer insulation system, namely, transformer insulation oil and transformer insulation paper. Any failure can cause the transformer to fail temporarily or permanently. As a result, regular and non-destructive monitoring of transformers is of particular importance for early detection and prediction of any faults. Frequency response analysis (FRA) is known as a high-accuracy, fast, economical, and non-destructive method for diagnosing the condition of a transformer, which can be used independently or as a complementary method to ensure the results of other diagnostic tests and based on the operational conditions of the transformer, it can be implemented in two methods, online and offline. This paper provides an in-depth discussion of measuring and interpreting FRA results and the ability of this method to detect and locate power transformer faults, especially insulation faults, which have been given less attention in the past. The information confirmed in this survey is expected to provide an important roadmap for future research in monitoring the condition of transformer insulation systems
Power systems
Reza Ghanizadeh; Hamed Azadrou
Abstract
Bearing-less induction motors (BLIMs) are suitable candidates for high-speed applications but suffer from low torque density and complex control issues due to the interaction of torque and levitation forces. To address these challenges, this paper presents a new control strategy that combines vector ...
Read More
Bearing-less induction motors (BLIMs) are suitable candidates for high-speed applications but suffer from low torque density and complex control issues due to the interaction of torque and levitation forces. To address these challenges, this paper presents a new control strategy that combines vector control and direct torque control (DTC) for torque management, alongside a novel force control method based on finite element analysis (FEA). The proposed approach minimizes interference between torque and force magnetic fields by employing a parallel winding structure and distinct control units for torque and force. Simulation results demonstrate that the proposed method significantly reduces torque ripple and improves steady-state performance compared to conventional vector control and DTC. Furthermore, the force control unit outperforms a dual field-oriented control (FOC) method in regulating rotor position, offering better suspension force control and faster stabilization. This work contributes to the development of more efficient control strategies for BLIMs, enhancing their performance in industrial applications.
Power systems
Milad Niaz Azari; Iraj Ahmadi; Hossein Aboulqasemi
Abstract
In this paper, the loss of excitation fault (LOE) as one of the most common fault in synchronous generator is analyzed and the methods for detecting this fault are investigated. Then, the performance of the power system equipped with STATCOM is simulated in the Matlab / Simulink software and the effects ...
Read More
In this paper, the loss of excitation fault (LOE) as one of the most common fault in synchronous generator is analyzed and the methods for detecting this fault are investigated. Then, the performance of the power system equipped with STATCOM is simulated in the Matlab / Simulink software and the effects of the generator performance on the resistor and its derivatives in the generator terminal are analyzed. A new method for LOE detection based on derivative of resistance is proposed. To illustrate the efficiency of this method various sizes and conditions for generator load are considered. The simulation results show that the amount of resistance time derivative in all cases, whether with or without STATCOM, behaves the same as a new criterion for detecting the LOE of an effective and useful method that is faster and more accurate than conventional methods. Simulation results in different amount and type of the loads shows the validity of the proposed method.
Power systems
Meysam Feili; Mohammad Taghi Aameli
Abstract
The prominent role of natural gas networks in mitigating the intermittency of renewable energy resources has highlighted the importance of integrated operation between electricity and gas grids. Additionally, energy storage systems, such as batteries and hydrogen, play a crucial role in power balancing ...
Read More
The prominent role of natural gas networks in mitigating the intermittency of renewable energy resources has highlighted the importance of integrated operation between electricity and gas grids. Additionally, energy storage systems, such as batteries and hydrogen, play a crucial role in power balancing and energy management. Previous research on the synergy between electricity and natural gas systems has primarily focused on the operational constraints of each grid. Only a few studies have explored market-driven models, such as peer-to-peer (P2P) energy trading, for the integrated operation of these networks. Furthermore, the limited studies that have implemented the peer-to-peer (P2P) market model for the integrated operation of power and natural gas grids have been conducted in two distinct phases: scheduling and trading. This paper introduces a stochastic P2P market-based optimization model for the coupled operation of natural gas and electricity grids, considering smart grid technologies such as power-to-gas (P2G) storage, batteries, and demand response (DR). Also, the presented framework incorporates alternating current (AC) power flow, natural gas steady-state model, and the power grid usage fee through the electrical distance model. The simulation results indicate that the proposed method significantly decreases total operating costs, reduces power losses, improves network component synergy, and enhances the performance of both networks.
Power systems
Gholamreza Memarzadeh; Farshid Keynia; Faezeh Amirteimoury; Rasoul Memarzadeh; Hossein Noori
Abstract
In recent years, there has been a significant increase in the utilization of renewable resources for electricity generation. Consequently, accurate short-term forecasting of renewable power production has become crucial for power system operations. However, Renewable Power Production Forecasting (RPPF) ...
Read More
In recent years, there has been a significant increase in the utilization of renewable resources for electricity generation. Consequently, accurate short-term forecasting of renewable power production has become crucial for power system operations. However, Renewable Power Production Forecasting (RPPF) presents unique challenges due to the intermittent and uncertain nature of renewable energy sources. This paper proposes a novel approach to short-term RPPF. The proposed model integrates various techniques, including Long Short-Term Memory (LSTM), Gated Recurrent Unit (GRU), Autoregressive Integrated Moving Average (ARIMA), Multi-Layer Perceptron (MLP), and Adaptive Neuro-Fuzzy Inference System (ANFIS). The aim is to enhance the accuracy and predictive performance of renewable power production forecasts. The suggested hybrid model employs the Modified Relief-Mutual Information (MRMI) feature selection technique to identify the most influential input data for prediction. Subsequently, the combined model generates a 24-hour ahead RPP prediction using a weighted output approach. By capitalizing on the strengths of each individual model, the combined method mitigates their weaknesses, thereby improving the overall efficiency of the forecasting process. The accuracy and performance of the proposed method are evaluated through two case studies involving solar farm power generation at the Mahan, Iran and Rafsanjan, Iran sites. The results demonstrate the effectiveness of the hybrid model in enhancing the accuracy of short-term RPPF. By combining multiple forecasting methods and utilizing the MRMI feature selection technique, the proposed method significantly improves prediction accuracy.
Power systems
Ali Riki; Mahmoud Oukati Sadegh; Omid Narouei
Abstract
The concept of an energy hub (EH) has been utilized to address the issue of performing concurrent operations of various energy generation and transmission infrastructures. One of the primary concerns for investors is the efficient utilization of EH to effectively manage energy carriers, particularly ...
Read More
The concept of an energy hub (EH) has been utilized to address the issue of performing concurrent operations of various energy generation and transmission infrastructures. One of the primary concerns for investors is the efficient utilization of EH to effectively manage energy carriers, particularly in transactions with the upstream grid. In this paper the proposed smart energy hubs (SEH) manage dispatchable generation, i.e. Combined Cooling, Heat, and power (CCHP), and non-dispatchable generation, i.e. Photovoltaic (PV). SEHs consider Ice Storage Conditioner (ISC) as well as Thermal Energy Storage System (TESS) as the Energy Storage System (ESS). To mitigate dependence on gas and electricity utility companies, a peer-to-peer (P2P) energy sharing strategy has been executed. The implementation of demand response (DR) is directed toward shiftable electrical loads. The thermodynamic model of heating and cooling loads is developed with flexibility as integrated demand response (IDR) based on the desired temperature. The objective of optimization is to minimize operation and environmental costs.. The flexibility constraint serves in particular to enhance the flexibility of the interrelationships between MG and the upstream network. The suggested model incorporates the probabilistic nature of PV generation as well as the electrical, thermal, and cooling demands in various scenarios. The proposed model is a Mix Integer Non-Linear Problem (MINLP), which was solved using SCIP solver in GAMS software. Implementation of the proposed framework on the typical EHs shows the impact of P2P transactive energy and flexibility constraint performance on elements such as operation costs, emissions and flexibility of the system.
Power systems
Saeed Javadi; Ali Hesami Naghshbandy
Abstract
Correct information about a power system’s dynamic variables is important and necessary for protection and control issues. Today's power systems, which differ from past systems, face new challenges due to converter-based resources. A solution to these challenges is dynamic state estimation in short ...
Read More
Correct information about a power system’s dynamic variables is important and necessary for protection and control issues. Today's power systems, which differ from past systems, face new challenges due to converter-based resources. A solution to these challenges is dynamic state estimation in short time intervals, such as the time domain. This paper simulates a standard 68-bus system in the presence of converter-based resources with a high penetration percentage in DIgSILENT software and compares the performance of four Bayesian filters in estimating the dynamic variables of the synchronous generators of the system using values in the time domain with each other. The four types of filters used include extended Kalman filter, unscented Kalman filter, ensemble Kalman filter, and particle filter.The MATLAB software suite was used for the comparison of the performance of the four filter types in different scenarios, including the presence of measurement and processing noise, extreme noise, network fault, data missing, state estimation time by each filter, and the comparison of time domain method with other methods such as phasor domain. Finally, the advantages and disadvantages of each were identified.
Power systems
Fatemeh Keramati; Hamid Reza Mohammadi
Abstract
Concerning the increasing application of plug-in electric vehicles (PEVs), planning PEV fast-charging stations (PEVF-CS) has become an important research topic. Regarding the reactive power compensation capability, the optimal planning of PEVF-CS reduces voltage deviation and power loss in the distribution ...
Read More
Concerning the increasing application of plug-in electric vehicles (PEVs), planning PEV fast-charging stations (PEVF-CS) has become an important research topic. Regarding the reactive power compensation capability, the optimal planning of PEVF-CS reduces voltage deviation and power loss in the distribution network. Also, one of the basic requirements for expanding electric transportation is the optimal placement of accessible PEVF-CSs, considering the geographic information data. Therefore, the optimal placement of PEVF-CS requires attention to different geographical criteria and power distribution network constraints. In this sense, this paper aims to propose an approach that integrates the Geographic Information System (GIS) technique, Multi-Criteria Decision-Making (MCDM) method, and Mixed-Integer Nonlinear Programming to find the optimal location of a PEVF-CS in Kabul city. The first stage is decision analysis based on the GIS technique and the MCDM approach. The second stage is suitability analysis of the power distribution network constraints to improve power quality. This paper considers ten different suitability criteria, and the Technique for Order Preference Similarity to Ideal Solution (TOPSIS) is applied to rank the different candidate locations. The analysis identified Junction 4 as the optimal choice and demonstrated a significant 3.6% reduction in power loss during peak hours, decreasing from 1071 kW to 1032 kW. These results demonstrate the effectiveness of our approach in optimizing PEVF-CS placement to enhance power quality and reduce the power loss.
Power systems
Farhad Amiri; Mohammad Hassan Moradi
Abstract
: In the context of frequency stability in a two-area microgrid, it is crucial to address the fluctuations in frequency caused by load disturbances. To achieve this, an effective load-frequency control (LFC) system, which serves as the secondary control, must be implemented. However, the presence of ...
Read More
: In the context of frequency stability in a two-area microgrid, it is crucial to address the fluctuations in frequency caused by load disturbances. To achieve this, an effective load-frequency control (LFC) system, which serves as the secondary control, must be implemented. However, the presence of renewable energy sources such as wind turbines and photovoltaic systems adds complexity to the operation of the LFC system due to their inherent uncertainty. To enhance the performance of the LFC system in the two-area microgrid, this paper proposes a reduction in the number of controllers employed, aiming for a less complex structure. Specifically, Model Predictive Control (MPC) is utilized for LFC, and the weight parameters of the MPC controller are determined using Craziness-based Particle Swarm Optimization (CRPSO). The proposed method is compared with alternative approaches, including PID controller optimized with Social Spider Optimization (SSO), Fractional Order Fuzzy PI (FOFPI), and conventional MPC. The effectiveness of the proposed method is evaluated in various scenarios, considering load variations and the presence of distributed microgrid generation resources. The results demonstrate that the proposed method outperforms the other controllers in terms of speed of response, reduction of overshoot and undershoot, and overall complexity. Importantly, the proposed method significantly improves the frequency stability of the two-area microgrid. The simulation and analysis are conducted using MATLAB software, providing a comprehensive understanding of the system dynamics and the performance of the proposed controller.
Power systems
Sasan Pirouzi; Mahmoud Zadehbagheri; Rohollah Rashidi
Abstract
In this article, the robust scheduling of the distribution network is presented considering electric vehicles, distributed generation, and energy storage, in which the energy management of the mentioned elements is considered, and also only one scenario is needed. The proposed deterministic problem is ...
Read More
In this article, the robust scheduling of the distribution network is presented considering electric vehicles, distributed generation, and energy storage, in which the energy management of the mentioned elements is considered, and also only one scenario is needed. The proposed deterministic problem is an optimization problem whose objective function is equal to minimizing energy cost. Also, the limitations of the problem are equal to the power flow equations of the network, the limitations of the technical indicators of the network such as the voltage of the buses and the passing power of the lines, the operation equations of electric vehicles, energy storages, and distributed generation. It is worth mentioning that the mentioned problem is non-linear. In the following, to achieve the global optimal point with a high solution speed, the linear model of the mentioned problem is presented with a very low calculation error. In this research, the uncertainty parameters of the problem are equal to active and reactive loads, energy prices, parameters of electric vehicles, and renewable productions. Finally, to simplify the decision-making of the distribution network operator, a robust model of the mentioned problem was presented. Finally, the proposed problem is applied to the IEEE standard 33-bus radial distribution network using GAMS optimization software, and then the capabilities of the proposed design are evaluated.
Power systems
Morteza Behbahanipour; Seyed Fariborz Zarei; Mohammadhadi Shateri
Abstract
This paper proposes an impedance-based approach for locating short-circuit faults in active distribution networks (DNs). This topic is a crucial task for operators, especially in grids with inverter-based distributed generators (IBDGs). Various methods have been proposed in this research area, including ...
Read More
This paper proposes an impedance-based approach for locating short-circuit faults in active distribution networks (DNs). This topic is a crucial task for operators, especially in grids with inverter-based distributed generators (IBDGs). Various methods have been proposed in this research area, including traveling waves, impedance-based methods, and artificial intelligence (AI) techniques. Among them, the impedance-based scheme provides a simple and efficient feature that could be used in AI-based techniques. In this paper, an enhanced fault localization method based on impedance estimation is introduced. This method comprises two main components: (i) fault distance determination and (ii) faulty section identification. When developing the proposed method, the modeling of inverter-based resources under symmetrical and asymmetrical faults is considered, which includes the impact and behavior of such sources in the proposed approach. Unlike conventional impedance-based methods, the proposed approach does not require network information such as structure, lines, load data, or voltage and current measurements along the feeder at multiple points. The proposed method can be utilized as a feature in AI-based techniques, significantly enhancing accuracy and reducing the complexity of such techniques. To validate the efficacy of the proposed approach, various series of time-domain case studies are performed, in addition to mathematical proofs. The results demonstrate the effectiveness of the proposed scheme in accurately locating faults with varying resistances at different positions in the presence of inverter-based distributed generators.
Power systems
Ramezan Havangi; Fatemeh Karimi
Abstract
Battery Management System (BMS) including measurements errors that causes decrease in the quality of calculated State of the Charge (SOC). It will limit the accurate estimation of the SOC that is a critical challenge in some of the engineering fields such as medical science, robotics, ...
Read More
Battery Management System (BMS) including measurements errors that causes decrease in the quality of calculated State of the Charge (SOC). It will limit the accurate estimation of the SOC that is a critical challenge in some of the engineering fields such as medical science, robotics, navigation and industrial applications. These facts implies on the significance of SOC estimation from battery measurements that is the matter of the literature through the recent years. Due to the dependency of the EKF to the system model, the change in the battery parameters and noise information cause losing performance in the SOC estimation over the time. In this paper, we assume that the battery parameters including internal resistance and capacitor and also the noise information are varying over the time. To solve that, two separate on-line identification algorithms for parameters and noise information are introduced. In more details, a Recursive Least Square (RLS) algorithm is used to identify the resistance and capacitor values. Moreover, the process and measurement noise covariance are estimated based on iterative noise information identification algorithm. Then all of the updated values are used in the EKF algorithm. This paper aims to address the issue of uncertainty in SOC estimation by proposing two algorithms. The first algorithm focuses on identifying deterministic uncertainty, which refers to uncertainty in model parameters. To address the challenge of uncertain model parameters, RLS is introduced.
Power systems
Saeed Abazari
Abstract
This study examines stability improvement of the power system which includes Double Feed Induction Generators (DFIGs) and Static Series Synchronous Compensator (SSSC). The proposed nonlinear controller is designed based on the terminal sliding mode control theory. A sliding mode observer is also developed ...
Read More
This study examines stability improvement of the power system which includes Double Feed Induction Generators (DFIGs) and Static Series Synchronous Compensator (SSSC). The proposed nonlinear controller is designed based on the terminal sliding mode control theory. A sliding mode observer is also developed to remove the need to access the information of all the state variables. The final closed-loop of the power system modeling is robust against parameter variations and uncertainties. The limitations of the control signals in the process of controller design are also considered. The application of such a method increases the stability margins and results in higher robustness degrees. A comparison with other nonlinear approaches such as back-stepping and feedback linearization approaches is carried out. The results show the faster and more reliable convergence rate of the power system-controlled trajectories to reach back to the equilibrium point after occurring a sudden fault. The results are obtained by performing a simulation on the standard 39-Bus, 10 machines NEW ENGLAND power system.
Power systems
Amir Ghaedi; Reza Sedaghati; Mehrdad Mahmoudian; Shahriyar Bazyari
Abstract
Due to the problems associated with overhead lines, underground XLPE cables are increasingly being used in power systems. The main cause of deterioration in these cables is insulation failure, primarily arising from the partial discharge phenomenon. One of the main challenges in online PD detection is ...
Read More
Due to the problems associated with overhead lines, underground XLPE cables are increasingly being used in power systems. The main cause of deterioration in these cables is insulation failure, primarily arising from the partial discharge phenomenon. One of the main challenges in online PD detection is the presence of various noises in the environment that must be eliminated. In recent years, various types of noise with different distributions, such as impulse noises generated by power electronic devices, have been introduced into the power system. Therefore, denoising techniques should be employed to filter out the noises and interferences present in the detected PD signal. Due to the non-stationary nature of PDs, this paper suggests using the wavelet transform method, which covers both the time and frequency domains, to remove various noises from PDs. Consequently, to determine the suitable mother wavelet transform, threshold, and number of decompositions, the characteristics of PD signals occurring in the cables are investigated through experimental tests. Additionally, because different noises exist in substations, the background noise at the measurement site is recorded as a reference noise to be used in the application of the wavelet-based noise removal process. This method is examined on a sample cable, and the results are discussed. Moreover, using the suggested method, the detection of PD signals in several 20 kV substations in Iran is carried out through the use of high-frequency current transformers connected to shield wires, oscilloscopes with high-frequency bandwidth, and MATLAB software.
Power systems
Mehdi Shafiee; Abbas-Ali Zamani; Mehdi Sajadinia
Abstract
In power systems planning, economic load dispatch considering the uncertainty of renewable energy sources is one of the most important challenges that researchers have been concerned about. Complex operational constraints, non-convex cost functions of power generation, and some uncertainties make it ...
Read More
In power systems planning, economic load dispatch considering the uncertainty of renewable energy sources is one of the most important challenges that researchers have been concerned about. Complex operational constraints, non-convex cost functions of power generation, and some uncertainties make it difficult to solve this problem through conventional optimization techniques. In this article, an improved dynamic differential annealed optimization (IDDAO) meta-heuristic algorithm, which is an improved version of the dynamic differential annealed optimization (DDAO) algorithm has been introduced. This algorithm has been used to solve the economic emission load dispatch (EELD) problem in power systems that include wind farms, and the performance of the proposed technique was evaluated in the IEEE 40-unit and 6-unit standard test systems. The results obtained from numerical simulations demonstrate the profound accuracy and convergence speed of the proposed IDDAO algorithm compared to conventional optimization algorithms including, PSO, GSA, and DDAO, while independent runs indicate the robustness and stability of the proposed algorithm.
Power systems
Navid Reza Abjadi
Abstract
Due to the growth of renewable energies and the need for sustainable electrical energy, AC microgrids (MGs) have been the subject of intense research. Medium voltage MGs will soon have a special place in the power industry. This paper uses a new and effective control scheme for islanded inverter-based ...
Read More
Due to the growth of renewable energies and the need for sustainable electrical energy, AC microgrids (MGs) have been the subject of intense research. Medium voltage MGs will soon have a special place in the power industry. This paper uses a new and effective control scheme for islanded inverter-based medium voltage MGs using the master-slave (MS) technique. The controllers only need local measurements. The designed controls are based on adaptive input-output feedback linearization control (AIOFLC). These controls have a high-performance response; and are robust against some uncertainties and disturbances. The use of the designed control scheme makes the output voltage of distributed generation (DG) sources have negligible harmonics. Besides, the generated voltage and active/reactive powers track their references effectively. The model of the inverter-based DGs is considered in a stationary reference frame, and there is no need for any coordinate frame transformation. The control method presented in this paper can be used for MGs with any number of inverter-based DGs and parallel inverters. The effectiveness of the proposed control scheme is evaluated by simulation in SIMULINK/MATLAB environment and compared with that of feedback linearization control (FLC) and conventional sliding mode control (CSMC).
Power systems
Elham Samavati; Hamid Reza Mohammadi
Abstract
Multifunctional features of grid-connected inverters can be used for harmonic compensation of local load voltage and grid-injected current. But, in high-power grid-connected inverters, there is a challenge due to low switching frequency. On the other hand, simultaneous compensation of local load voltage ...
Read More
Multifunctional features of grid-connected inverters can be used for harmonic compensation of local load voltage and grid-injected current. But, in high-power grid-connected inverters, there is a challenge due to low switching frequency. On the other hand, simultaneous compensation of local load voltage and grid-injected current harmonics is an important issue in grid-connected inverters. Using a Unified Power Quality Conditioner (UPQC) at the Point of Common Coupling (PPC), an improved active harmonic compensation method is proposed which is appropriate for high-power low-frequency grid-connected inverters. The UPQC operates as a combination of a negative shunt virtual admittance and a negative series virtual impedance at the PCC. It suppresses the disturbances caused by local load variation and grid impedance change. Using a low-power, high-frequency UPQC, local load voltage and grid-injected current harmonics up to higher-order components are simultaneously compensated despite grid impedance changes and nonlinear local load variations. The control system is designed according to the impedance-based stability criterion to ensure the system's stability. The theoretical results are validated using different case study simulations in MATLAB/Simulink software.
Power systems
Mohammad Hassan Moradi; Meysam - Mokari; mohammad abedini
Abstract
In this paper, a novel method for a multi-objective and risk-based optimal reactive power dispatch is proposed. The method includes two main objective functions: technical and economic. The technical objective involves minimizing the risks of voltage instability, voltage deviation, and flow violation, ...
Read More
In this paper, a novel method for a multi-objective and risk-based optimal reactive power dispatch is proposed. The method includes two main objective functions: technical and economic. The technical objective involves minimizing the risks of voltage instability, voltage deviation, and flow violation, and the economic objective involves minimizing the costs of reactive power generation, active power losses, load shedding, and active power rescheduling. Using these functions and assigning different weighting factors for each sub-objective, the risk of the events or uncertainties to customers or the grid can be managed. In addition, moment matching is used to discretize and create scenarios from continues probability distribution functions of wind speed and electrical energy uncertainties. As the number of uncertain variables increases, so does the number of scenarios and the simulation time. Therefore, the fast-forward selection algorithm is applied to reduce the number of scenarios. To reduce the computational complexity and the number of topological scenarios, a new contingency filtering method based on high-risky events is proposed. A modified multi-objective PSO algorithm based on a hybrid PSO with sine-cosine acceleration coefficients is proposed to find the Pareto front of solutions. The method is implemented on the modified IEEE 30-bus test system. To demonstrate the effectiveness of the proposed method, the results are compared with previously published literature. The results show that risk-based scheduling increases system reliability and cost-effectiveness compared to traditional scheduling.
Power systems
Farhad Zishan; Ehsan Akbari; Abdul Reza Sheikholeslami; Nima shafaghatian
Abstract
This paper contributes to the design, modeling, and planning of a distributed generation (DG) network with wind and solar by means of the particle swarm algorithm (PSO) algorithm in the IEEE 33-bus network, aiming to minimize The results indicate an adequate performance in a variety of environments, ...
Read More
This paper contributes to the design, modeling, and planning of a distributed generation (DG) network with wind and solar by means of the particle swarm algorithm (PSO) algorithm in the IEEE 33-bus network, aiming to minimize The results indicate an adequate performance in a variety of environments, and the presence of distributed wind/solar energy generators decreases network stress by feeding loads locally. These systems (wind and solar) can be used in remote areas without power networks, or even in areas where there is a tendency to use renewable energy despite the presence of a power network. They can also supply the output load for most of the day and night. Probability distribution functions are used, and the outputs are expressed as probability density distribution functions instead of absolute numbers. In addition, there is a high degree of uncertainty regarding the state of the system, which is an associated renewable energy source within the power system elements. By means of MATLAB software, the proposed method is implemented in order to ensure effectiveness and validate the results.
Power systems
Mohammadmehdi Sedaghatzadehhaghighi; Mohsen Gitizadeh; saeed hasanvand
Abstract
Demand response programs (DRPs) are considered a promising solution to address the variability and uncertainty of renewable generations. Heat pumps (HPs) as responsive loads are prone to participate in DRPs. HPs participation in DRPs will lead to changes in the buildings’ temperature and, correspondingly, ...
Read More
Demand response programs (DRPs) are considered a promising solution to address the variability and uncertainty of renewable generations. Heat pumps (HPs) as responsive loads are prone to participate in DRPs. HPs participation in DRPs will lead to changes in the buildings’ temperature and, correspondingly, the occupants’ thermal comfort (OTC). If these programs are not planned wisely, HPs owners’ tendency to participate in DRPs will reduce, and power system operators will be deprived of the DRPs benefits. This work proposes a new ASHRAE55-based framework to guarantee the OTC. Information gap decision theory (IGDT) is also used to address the uncertainty of renewable generation. Then, an objective function is defined to simultaneously optimize the power consumption of HPs and the uncertainty of wind turbine generators. To find the optimal solution, the standard and adaptive fuzzy PSO algorithms are used. For determining the participation of HPs in the DRPs, there is a conventional scenario in which the temperature of each residence should be limited to the range defined by the occupant(s). The simulation results verify the superiority of the proposed scenario over the conventional one.
Power systems
Hassan Abniki; Mostafa Hajati Samsi; Behrooz Taheri; Seyed Amir Hosseini
Abstract
Power transmission lines are vital components of today's power systems. These power lines transmit the electricity produced in power plants in high volume and with very low losses to distant areas so that it can be reached to consumer through distribution networks. In fact, these lines are the intermediary ...
Read More
Power transmission lines are vital components of today's power systems. These power lines transmit the electricity produced in power plants in high volume and with very low losses to distant areas so that it can be reached to consumer through distribution networks. In fact, these lines are the intermediary between major energy producers and distribution networks. Accordingly, these transmission lines are of a great importance and must be protected appropriately with a suitable protection system. Distance relays are widely used to protect these lines due to their convenient coordination characteristics and simplicity. High impedance fault (HIF) can be a critical challenge for distance relays due to their low current amplitude and similarity to conventional events in power systems such as capacitive bank switching. For this reason, in this paper a new approach is presented based on the instantaneous frequency variations obtained from the current RMS in order to detect the high impedance fault. This method detects high impedance faults via calculating a Detection index (DI) and considering a threshold value. The proposed method has been tested using DIgSILENT and MATLAB software in an IEEE standard 39-bus network. The presented results evidently demonstrate that the proposed method is suitable for detecting HIF and Low impedance fault (LIF). In addition, this method has a proper performance during capacitor bank switching and can well distinguish between HIF and capacitive bank switching. Moreover, the presented method is resistant to noise and also is capable to detect the faulty phase.
Power systems
Mahnaz Rezaei; Mohammad Tolou Askari; Meysam Amirahmadi; Vahid Ghods
Abstract
Since the presence of an energy hub (EH) leads to change the expansion planning problem of electrical power system. Therefore, in this study, the nature of optimal generation and transmission expansion planning in the presence of EH is studied. Also, the effect of applying the proposed hub with and without ...
Read More
Since the presence of an energy hub (EH) leads to change the expansion planning problem of electrical power system. Therefore, in this study, the nature of optimal generation and transmission expansion planning in the presence of EH is studied. Also, the effect of applying the proposed hub with and without considering energy storages (ESs) as well as the short and long-term corrective actions to reduce the losses and costs are investigated. In addition, demand response and line transmission switching are considered as effective approaches to improve resilience in the proposed dynamic multi-level model. This nonlinear problem is solved sequentially considering the random approach and using differential evolution algorithm (DEA) and the symphony orchestra search algorithm (SOSA). In this paper, the proposed objective functions are studied in five-level and the results show the efficiency of this model in solving the planning problem. The findings show that the proposed planning model decreased capital costs of transmission switches as much as 26%, the capital cost of the transmission as much as 2.29%, the congestion cost as much as 1.8%, The capital cost of generation units as much as 3.75%, the payment capacity paid to generation units as much as 1.8%. Also, the expected profit of the generation units has increased as much as 3.75%. To show the competence of the proposed algorithms, the 400-kV test system with 52 buses in Iran is simulated in MATLAB environment.
Power systems
Morteza Jadidoleslam; Morteza Ghaseminejad
Abstract
Wind power has been considered a future alternative to fossil energy resources. However, due to its stochastic nature, the integration of wind power plants (WPPs) into power systems poses some reliability problems such as a mismatch between load profile and efficient wind power generation. This issue ...
Read More
Wind power has been considered a future alternative to fossil energy resources. However, due to its stochastic nature, the integration of wind power plants (WPPs) into power systems poses some reliability problems such as a mismatch between load profile and efficient wind power generation. This issue can be alleviated by considering the correlation between hourly load and wind speed variations in the planning phase. To this end, a reliability-based wind power planning procedure is proposed and formulated as a stochastic programming problem. The objective function is the minimization of total costs, including capital investment, operating and maintenance, and customer energy not served costs. A new hybrid method that combines features of the load-duration curve and the K-means clustering algorithm is proposed to model the uncertainty of the input data. A shuffled frog-leaping algorithm is used to solve the proposed model. The simulation results indicate that the amount of adaptation between hours with high loads and those with high wind speeds markedly affects the selection of wind sites as optimal locations for WPP installation. Considering this issue can also improve power system reliability in the presence of WPPs.
Power systems
Saeed Abazari; Zabihollah Faramarzi
Abstract
This study is concerned with the design of multi-input Dynamic Surface Control (DSC) to dynamic stability improvement of power systems which include both Doubly Feed Induction Generator (DFIG) and Static Synchronous Series Compensator (SSSC). The presented control method has a multi-input feature which ...
Read More
This study is concerned with the design of multi-input Dynamic Surface Control (DSC) to dynamic stability improvement of power systems which include both Doubly Feed Induction Generator (DFIG) and Static Synchronous Series Compensator (SSSC). The presented control method has a multi-input feature which acts on synchronous generators. To improve dynamic stability, the control law is developed by applying a suitable Lyapunov function. The coefficients of the proposed controller are determined by use of metaheuristic optimization algorithms. This optimal control law leads to a significantly improved performance in comparison with linear control. A particular low-pass filter is also introduced and applied to cancel the effects of additional undesired terms in the design method, leading to a simplified control form compared to the other available approaches in the literature. Implementing an adaptive parameter estimation scheme will result in the robustness of the proposed method. The effectiveness of the presented approach is investigated on a standard 39-Bus power system which includes DFIG and SSSC.
Power systems
Amir Hossein Ataee-Kachoee; Hamed Hashemi Dezaki; Abbas Ketabi
Abstract
The deployment of microgrids (MGs) and smart grids to maximize the benefits from distributed generations (DGs) has increased. Although the MG framework and concept improve system flexibility and reliability, new challenges corresponding to the MG protection system appear compared to conventional passive ...
Read More
The deployment of microgrids (MGs) and smart grids to maximize the benefits from distributed generations (DGs) has increased. Although the MG framework and concept improve system flexibility and reliability, new challenges corresponding to the MG protection system appear compared to conventional passive distribution networks. The adaptive protection schemes, which have been reported to consider various topologies in MG protection, need communication infrastructure. Also, the failure of telecommunication systems and cyber-attacks has drawn attention to unrelated protection schemes using local measurements, taking into account different topologies and related selectivity constraints. The literature shows a research gap in the development of local measurement-based protection schemes considering different operating modes and network configurations due to the unavailability of upstream substations, DGs, and other MGs sub-systems such as lines. This research attempts to fill this research gap by proposing a new protection scheme using dual setting directional overcurrent relays (DS-DOCRs) based on N-1 contingency topologies. The introduced method is applied to the distribution portion of the IEEE 30-bus test system. The Genetic Algorithm (GA) has been selected as the optimization algorithm, which is implemented in MATLAB, and the power system analyses are done in DIgSILENT. The test results show the advantages of the proposed method compared to the existing designs, only considering the limited operation modes. The test results indicate that mis-coordination for the N-1 contingency-based topologies does not appear using the proposed method.
