Research Articles
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 ...
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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.
Research Articles
Industrial Electronics
Hossein Gholizadeh; Sara Hasanpour
Abstract
In this paper, a new transformerless high step-up DC/DC converter with low input current ripple for renewable energy generation systems. This introduced circuit is based on a conventional quadratic boost converter with a CUK circuit. Therefore, the advantages of Cuk and quadratic boost converters such ...
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In this paper, a new transformerless high step-up DC/DC converter with low input current ripple for renewable energy generation systems. This introduced circuit is based on a conventional quadratic boost converter with a CUK circuit. Therefore, the advantages of Cuk and quadratic boost converters such as continuity of the input and output currents have been maintained. In this suggested topology, switched capacitor and switched inductor techniques are also considered to obtain high voltage gains. The series connection of an inductor with the load causes the converter to have no right half plane zeros (RHPZ) in the transfer function; Thus, the proposed structure is able to provide fast dynamic behavior under the load variation than the other typical counterparts. The other advanced features of the introduced topology are its ultra-high voltage gain, continuous input current with low ripple, low voltage stress, and common ground between the input source and output load. The voltage conversion ratio of the suggested topology for both ideal and non-ideal modes has been provided. The operating principle, steady-state analysis along with comparison study of the proposed converter are discussed in detail. Finally, to confirm the theoretical analysis, a 80 W (20 V/ 160 V) hardware prototype is established.
Research Articles
Control
Valiollah Ghaffari
Abstract
Employing discrete-time techniques, the min-time control of continuous-time dynamical systems is mainly studied through an analytical framework. To this aim, the exact discrete-time model of the linear time-invariant systems is specified through a zero-order hold. The optimal solution could be directly ...
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Employing discrete-time techniques, the min-time control of continuous-time dynamical systems is mainly studied through an analytical framework. To this aim, the exact discrete-time model of the linear time-invariant systems is specified through a zero-order hold. The optimal solution could be directly determined from some necessary conditions. However, the structure of the optimum control sequences is derived by utilizing the well-known Pontryagin principle. Employing the state transition matrix, the states of the control system are computed at the switching times. The switching times of the control signal would be found from a set of nonlinear algebraic equations. Accordingly, the transformation of the system’s states, from a known initial point to a specific value, would be accomplished in the minimum possible time. Applying the proposed scheme, the exact (integer) values of the switching times and the final time are numerically determined from the solution of an algebraic equation. Several discrete-time and continuous-time examples are discussed and simulated to show the feasibility and effectiveness of the suggested procedure in the dynamical systems. The simulation results confirm the method’s advantages over the existing ones.
Research Articles
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) ...
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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.
Research Articles
Optimization
Faezeh Gholipour Zarandi; Masoud Rashidinejad; Amir Abdollahi; Ali Yazhari Kermani
Abstract
The proliferation of renewable energy sources, with their inherent uncertainty in smart microgrids, necessitates the use of flexible resources to maintain grid stability. However, implementing these flexibility-based approaches can have a multidimensional impact, including economic, technical, social, ...
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The proliferation of renewable energy sources, with their inherent uncertainty in smart microgrids, necessitates the use of flexible resources to maintain grid stability. However, implementing these flexibility-based approaches can have a multidimensional impact, including economic, technical, social, and environmental considerations. This study investigates these effects, with a particular focus on how flexibility provision influences battery aging, which is a critical aspect since batteries are the primary source of flexibility in microgrids. Here, a Lexicographic approach is used to optimize the multi-objective operation problem by minimizing costs while maximizing flexibility. Batteries act as the main source of flexibility and compensate for the uncertainty associated with solar energy production; therefore, it is important to investigate the battery's aging upon flexibility provision. The analysis shows a trade-off between flexibility and economic efficiency. Hence, from an economic point of view, increasing reliance on batteries and micro turbine production to improve flexibility leads to higher operating costs. From a social perspective, the proposed approach increases microgrid reliability by minimizing the cost of energy not supplied. Considering the technical aspect, the results indicate that increasing the use of batteries in order to increase microgrids' flexibility accelerates their aging, hence decreasing their corresponding state of health. Further, the simulation results show that flexibility comes with an environmental cost. Therefore, increasing reliance on micro turbine production and the possibility of purchasing energy from sources with more emissions to provide the required flexibility can lead to an increase in the cost of pollution.
Research Articles
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 ...
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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.
Research Articles
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 ...
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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.
Research Articles
Industrial Electronics
Mahdi Elmi; Mohamad Reza Banaei; Hadi Afsharirad
Abstract
The objective of this paper is to propose, study and analyze a non-isolated high step-up SEPIC-based DC-DC converter for photovoltaic applications. The proposed structure is based on the SEPIC converter and utilizes a two-winding coupled inductor along with an improved voltage multiplier cell in order ...
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The objective of this paper is to propose, study and analyze a non-isolated high step-up SEPIC-based DC-DC converter for photovoltaic applications. The proposed structure is based on the SEPIC converter and utilizes a two-winding coupled inductor along with an improved voltage multiplier cell in order to enhance the output voltage level. Moreover, a passive voltage clamp is used to reduce the voltage stress on the main switch and recover the energy stored in the leakage inductance of the coupled inductor. Hence, an active switch with low RDS-ON could be employed. Meanwhile, due to soft switching condition at turn-off instant of diodes, their reverse-recovery problems are solved. Furthermore, the presented converter has the merits such as continuous input current, high efficiency and low cost and size which make it a promising solution for photovoltaic applications. At the end, the converter is compared to different types of DC-DC converters to show its advantages over the converters designed before. In order to verify the performance of the converter, a 200-W laboratory prototype is implemented and experimental results are taken and depicted. Results prove the feasibility and functionality of the presented converter for photovoltaic systems.
