Papers by heidarali shayanfar
Stochastic multi‐stage joint expansion planning of transmission system and energy hubs in the presence of correlated uncertainties
Iet Renewable Power Generation, May 27, 2023
Deployment of Energy Hubs (EHs) across the power grid can alleviate the Transmission System (TS) ... more Deployment of Energy Hubs (EHs) across the power grid can alleviate the Transmission System (TS) capacity and substitute the conventional fossil fuel‐based thermal units. Therefore, this paper presents a tri‐level multi‐stage Joint Expansion Planning of the Transmission system and EHs (JEPT&EHs). In this approach, the Cholesky decomposition technique combined with the Nataf transformation is applied to make the uncertain input parameters correlated. Then, the k‐means data‐clustering method is employed to reduce the initial correlated samples. In the first level, the Transmission System Operator (TSO) optimizes the planning and scheduling strategies associated with the TS capacity requirements and operation costs of the conventional generators. In the second level, the financers specify the expansion of the EHs based on the Locational Marginal Prices (LMPs). In the third level, the Direct Current Optimal Power Flow (DCOPF) is determined to update the LMPs by the Independent System Operator (ISO). The optimization problem is an Equilibrium Problem with Equilibrium Constraints (EPEC) since there are multiple financers across the TS. The proposed model is implemented on the IEEE standard 30 bus TS to present the effectiveness of the EHs' deployment and the impact of the correlations in the total costs of the TSO and financers.
International Transactions on Electrical Energy Systems, Jun 29, 2022
is paper considers the problem of tracking the global maximum power point (GMPP) in partially sha... more is paper considers the problem of tracking the global maximum power point (GMPP) in partially shaded conditions (PSCs) as a multiobjective optimization problem and solves it using a novel multiobjective optimization algorithm on the basis of Bayesian optimization formulation. Bayesian optimization is a metamodel-based global optimization method that is able to balance exploration and exploitation. e Pareto solutions are obtained by using a multiobjective Bayesian optimization algorithm. Also, a new acquisition function is proposed to improve the diversity and convergence of the Pareto solutions. Two objective functions are introduced to remove the large tracking errors and oscillations of the operating point around the GMPP. e suggested method is implemented online for GMPP tracking so that the suggested method monitors any change in environmental conditions and generates the optimal duty cycle for the DC-DC converter for the GMPP tracking (GMPPT) by the PV array. Several multipeak PSC scenarios are implemented and simulated to show efficiency of the suggested approach. e MATLAB/ SIMULINK is employed to implement a photovoltaic (PV) system comprising a PV array, a boost converter, and the proposed multiobjective Bayesian optimization algorithm (MOBOA). e simulation results show a very satisfactory performance of the MOBOA in terms of transient state and steady-state oscillations and tracking speed.
Physical Communication, Aug 1, 2020
This is a PDF file of an article that has undergone enhancements after acceptance, such as the ad... more This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
Changing the regulations for regulating the changes: From distribution system operator (DSO) to electricity distribution stakeholders’ organization (EDSO)
Energy & Environment, Feb 1, 2022
Followed by the extensive activation of demand side entities, the anti-competitive and monopolist... more Followed by the extensive activation of demand side entities, the anti-competitive and monopolistic aspects of distribution system operator (DSO) is becoming more apparent. The business model of the DSO and its regulations are not capable enough to fully leverage the capacity of emerging technologies and responsive prosumers. This paper criticized the challenges/deficits revolving around the conventional DSO model and proposes an interactive platform based on the sharing economy business model at the network level. The electricity distribution stakeholders’ organization (EDSO) as the substitute of DSO in active distribution networks is developed based on the collaborative governance decision-making model. The EDSO has the privilege to legislate on the platform operation and its main policy is to preserve the public interest as well as the integrity of electric distribution system. The superiority of proposed operation model is its non-monopolistic and non-profit nature which materializes the perfect competition of active customers and guaranties their maximum utilization.
Power quality compensation in smart grids with a single phase UPQC-DG
Modern electrical energy networks as smart grids use green energy sources such as wind and solar ... more Modern electrical energy networks as smart grids use green energy sources such as wind and solar power. One of the impacts of smart grids on distribution systems is power quality compensation. This paper describes a novel structure for single phase UPQC-DG (Unified Power Quality conditioner-Distributed Generation) for DC output DG systems which can be used in smart grids. The proposed configuration can be used not only for compensation of power quality problems but also for supplying of load power partly. In the proposed configuration, a DG system with low voltage output has been connected to the DC side of UPQC. This converter has been composed of one full-bridge inverter, one three winding high frequency transformer and two cycloconverters to achieve a desired output signals with low voltage DG systems. High frequency transformer steps up voltage of the primary side, reduces the converter volume and also provides an electrical isolation between input DG and main grid. Another capability of the proposed configuration is elimination of UPQC DC link capacitor and the bulky power frequency transformer. State space equations for modes of the proposed converter are presented for dynamic analysis and providing proper control based on phase shift with nonlinear control. The nonlinear controller is based on Input-Output feedback Linearization to achieving some prescribed behavior of the proposed UPQC-DG in mitigation of power quality problems. The performance of the proposed system was analyzed via simulation with PSCAD/EMTDC analysis program software. The results are presented to confirm the validity of the proposed approach.
Fabrication and Characterization of Flexible PZT Fiber and Composite
Ferroelectrics, 2012
ABSTRACT Straight lead zirconate titanate (PZT) fibers with round cross sections were fabricated ... more ABSTRACT Straight lead zirconate titanate (PZT) fibers with round cross sections were fabricated by extrusion with boric acid and polyvinyl alcohol (PVA) condensation. The sintered fibers showed more tetragonality than the bulk. The dielectric constant of the electrode area perpendicular to the PZT fibers (Z1) was higher than the electrode area parallel to the PZT fibers (R1). Single PZT fiber exhibited higher remanent/saturation polarization and coercive field than the bulk and composite. The piezoelectric constant d33 of the Z1 composite was 300 pC/N for the 75 vol% PZT fibers. The Z1 composite had flexibility and high dielectric and ferroelectric properties, and exhibited promise in conformable and large-area applications.
Stochastic expansion planning of transmission system and energy hubs in the presence of correlated uncertain variables
Iet Generation Transmission & Distribution, Dec 23, 2022
Transactions on Emerging Telecommunications Technologies, May 4, 2018
Accurate estimation and correction of channel distortions and carrier frequency offset (CFO) are ... more Accurate estimation and correction of channel distortions and carrier frequency offset (CFO) are of a great importance in any multicarrier communication system. Hence, in this paper, we propose data-aided CFO and channel estimation techniques for both multiuser uplink and downlink of the generalized frequency division multiple access (GFDMA). Our proposed solutions jointly estimate the CFO and channel responses based on the maximum-likelihood criterion. To simplify the implementation of the proposed estimation algorithms, we suggest a preamble composed of two similar Zadoff-Chu training sequences in a generalized frequency division multiplexing block. It is worth mentioning that our proposed technique can estimate both integer and fractional CFO values without any limitation on the acquisition range of CFO. In the uplink phase, each user aligns its carrier frequency with the base station using the estimated CFO in the downlink. However, the CFO estimates may get outdated for the uplink transmission. Thus, residual CFOs may still remain in the received signal at the base station. While being trivial in the downlink, CFO correction is a challenging task in the uplink. Thus, we also propose a joint CFO correction and channel equalization technique for the uplink of GFDMA systems. Finally, we evaluate our proposed estimation and correction algorithms in terms of estimation mean square error and bit error rate performance through simulations.
Risk‐averse scheduling of an energy hub in the presence of correlated uncertain variables considering time of use and real‐time pricing‐based demand response programs
Energy Science & Engineering, Mar 11, 2022
In this paper, a risk‐based probabilistic short‐term scheduling of a smart energy hub (SEH) is pr... more In this paper, a risk‐based probabilistic short‐term scheduling of a smart energy hub (SEH) is presented considering the uncertain variables and the correlation between them. Neglecting the uncertainty of renewable energy sources (RESs), demands and market prices can make the obtained results unusable. In addition, correlations among uncertain variables may have similar importance on final solutions. To have a more realistic view, the stochastic nature of solar irradiation, wind generation, energy demands, and electrical/thermal/gas market prices are taken into consideration through uncertainty modeling. For this purpose, a probabilistic scenario‐based approach is implemented. The Monte Carlo simulation technique is employed to generate an adequate number of scenarios and the Cholesky decomposition technique combined with Nataf transformation is used to make the samples correlated. In addition, the k‐means data clustering technique is used to reduce the initial number of scenarios to the most representative 10 scenarios. The addressed SEH comprises photovoltaic panels/a wind turbine/a combined heat and power generation unit/a fuel‐cells power plant (FCPP)/a thermal/hydrogen storage system and plug‐in electric vehicles (PEVs). This study aims to optimize the economic aspects while reducing the pollution emissions of the SEH and controlling the risk level of SEH operation. To enhance the flexibility of the SEH in the management of supplying demands with lower costs, the thermal demand response program (DRP) is considered beside the electrical DRP. Two kinds of time of use (TOU) and real‐time pricing (RTP) DRPs are used for electrical and thermal loads. The conditional value at risk technique is taken into account to control the deviations of the SEH operation and emission costs. Simulation results show a reasonable reduction in operation and emission costs along with the risk level of the energy hub with the proposed approach. The operation emission, and risk costs are reduced by 37.39%, 32.11%, and 33.16%, respectively, with integrating PEVs, FCPP, and RTP‐DRPs. Moreover, integration of PEVs, FCPP along with TOU‐based DRPs contribute to reduce the operation emission, and risk costs by 10.47%, 9.03%, and 11.64%, respectively.
Carrier frequency offset (CFO) caused by the misalignment of the transmitter and receiver local o... more Carrier frequency offset (CFO) caused by the misalignment of the transmitter and receiver local oscillators can adversely affect the performance of any multicarrier system if not accurately estimated and corrected. Thus, in this paper, we propose a CFO and channel estimation technique based on the maximum-likelihood (ML) criterion for generalized frequency division multiplexing (GFDM). Our proposed CFO estimator does not have any limitation on the CFO acquisition range while providing an accurate estimate. We propose a preamble block containing two frequency domain ZC (Zadoff-Chu) sequences for training which leads to a low complexity implementation of the CFO estimator. Compared with the existing solution in the literature with the largest CFO estimation range and precision, our technique brings around two orders of magnitude complexity reduction without any performance penalty. We also evaluate the performance of our proposed technique through numerical simulations while showing its superiority to the existing literature.
Power Quality Compensation as Well as Power Flow Control Using of Unified Power Quality Conditioner
This paper proposed a new control approach for power quality compensation using Unified Power Qua... more This paper proposed a new control approach for power quality compensation using Unified Power Quality Conditioner (UPQC). This approach has capability of power flow control as well as power quality compensation, too. In the UPQC control, Series Active Filter (SAF) is controlled by dqo approach for voltage sag, swell, unbalance, interruption and harmonic compensation. Also, Parallel Active Filter (PAF) is
Fast DC Offset Removal for Accurate Phasor Estimation using Half-Cycle Data Window
DOAJ (DOAJ: Directory of Open Access Journals), Jul 1, 2022
Background and Objectives: Current and voltage signals' distortion caused by the fault in... more Background and Objectives: Current and voltage signals' distortion caused by the fault in the power system has negative effects upon the operation of the protective devices. One of the influencing factors is the existence of the exponential DC which can significantly distort the signals and lead to a possible malfunction of the protective devices, especially distance and overcurrent relays. The main problem is the lack of clarity about this component due to the dependence of its time constant and initial amplitude to the configuration of the electrical grid, location and resistance of faulty point. This makes it hard to extract the main frequency phasors of the voltage and current. Methods: Considering the importance of a fast clearance of the fault, this paper offers a method for an effective and fast removal of the decaying-DC that employs a data window with a length that is equal to the half cycle of the main frequency, while the conventional methods mostly use data from one cycle or even more. The proposed method is based upon the extraction of the decaying-DC component's parameters. Results: The efficiency of this method is compared to the conventional Fourier algorithm of Half-Cycle (HCFA) and the mimic filter plus the HCFA. Conclusion: The outcomes display that the proposed method presents a better efficiency from the point of view of the speed and the accuracy of convergence to the final results.
Applied Energy, Dec 1, 2020
A new comprehensive multi-objective phasor measurement unit placement was proposed. • Genetic alg... more A new comprehensive multi-objective phasor measurement unit placement was proposed. • Genetic algorithm and dynamic programming in measurement placement were compared. • The effect of measurements, network splitting, and zonal interaction was considered. • The quality of state estimation in the clustered distribution network was enhanced.
Risk-constrained probabilistic optimal scheduling of FCPP-CHP based energy hub considering demand-side resources
International Journal of Hydrogen Energy, Jun 1, 2020
Abstract Renewable energy sources (RES) with sharing a large percentage of future energy generati... more Abstract Renewable energy sources (RES) with sharing a large percentage of future energy generation capacities play an essential role in the decarbonization of the future electricity and thermal networks as well as transportation sectors. However, the uncertainties in their outputs make some difficulties in making operational decisions. Hydrogen energy plays a considerable role in this concept. Besides, energy hubs (EHs) provide an efficient and reliable framework for gathering multi-type energy carriers.This paper optimally schedules the operating of the EH and decreases the emission cost, considering the electrical and thermal demand response (DR) program in a probabilistic environment. Besides plug-in electric vehicles (PEVs) and a complete model of hydrogen-based renewable energy sources are presented in the EH. Taking into account uncertainties of electrical/thermal energy markets real-time prices, customers' energy demand, and energy production of RESs into account, various scenarios are generated using the Monte Carlo simulation technique. Next, an efficient method is used to reduce the number of the scenario to make the optimization problem computable and fast. In order to reduce the risk of encountering high operating costs, the conditional value at risk (CVaR) technique is used to manage the associated risk. Simulation results show the efficiency of the proposed method in decreasing the operational cost and managing the risk of encountering unfavorable states.
Energy, Oct 1, 2018
In this paper, the energy management of a microgrid including wind turbine, PhotoVoltaic (PV) mod... more In this paper, the energy management of a microgrid including wind turbine, PhotoVoltaic (PV) modules, Combined Heat and Power (CHP) systems, fuel cells, power only units, heat only unit, Plug-in Electric Vehicles (PEVs), and thermal energy storage resources for supplying electrical and thermal loads is presented. For achieving a better management on demand side, both price-based and incentive-based Demand Response Programs (DRPs) have been used and their impacts on reducing the operational cost of microgrid in both grid-connected and island modes have been investigated. Also, the uncertainty of price, load, wind speed and solar radiation are taken into account in order to obtain more realistic results. By discretization of Probability Distribution Function (PDF) of each uncertain parameter, a set of scenarios is generated. Then, using a scenario reduction method based on mixed-integer linear optimization, the set of reduced scenarios is obtained. Two-stage stochastic programming approach is used to minimize the operational cost in microgrid energy management. The proposed method for microgrid energy management has been evaluated in three modes: grid-connected, grid-connected with DRPs, and island mode with DRPs.
IEEE Transactions on Industrial Informatics, Jul 1, 2018
This paper presents the computation of optimal DC sources and switching angles using the Generali... more This paper presents the computation of optimal DC sources and switching angles using the Generalized Pattern Search (GPS) optimization method for harmonic elimination in a cascaded MultiLevel Inverter (MLI). The goal is to solve nonlinear equations for eliminating low-order harmonics and reaching desired fundamental component. For case study 5 and 7-level inverter are chosen. The 7-level inverter with equal DC sources and 5 and 7-level inverter with an optimal DC source are applied to eliminate 5th and 7th harmonics. To obtain this goal, MATLAB software is used. Considering simulation results, cost and simpler implementation, 5-level inverter with an optimized DC source is more effective in all modulation indexes in comparison with 7-level inverter. Also, results demonstrate the superiority of GPS over Genetic Algorithm (GA) in attaining accurate global minima. For better evaluation of optimizing more DC sources and GPS performance in comparison with GA, 7level inverter with two optimal DC sources is applied to eliminate 5th, 7th, 11th, and 13th harmonics. Finally, to validate the accuracy of the 5-level inverter with an optimal DC source and GPS performance, the experimental results are provided for a 5level cascaded H-bridge inverter.
The optimization of demand response programs in smart grids
Energy Policy, Jul 1, 2016
The potential to schedule portion of the electricity demand in smart energy systems is clear as a... more The potential to schedule portion of the electricity demand in smart energy systems is clear as a significant opportunity to enhance the efficiency of the grids. Demand response is one of the new developments in the field of electricity which is meant to engage consumers in improving the energy consumption pattern. We used Teaching & Learning based Optimization (TLBO) and Shuffled Frog Leaping (SFL) algorithms to propose an optimization model for consumption scheduling in smart grid when payment costs of different periods are reduced. This study conducted on four types residential consumers obtained in the summer for some residential houses located in the centre of Tehran city in Iran: first with time of use pricing, second with real-time pricing, third one with critical peak pricing, and the last consumer had no tariff for pricing. The results demonstrate that the adoption of demand response programs can reduce total payment costs and determine a more efficient use of optimization techniques.
Coordinated multi‐stage expansion planning of transmission system and integrated electrical, heating, and cooling distribution systems
Iet Renewable Power Generation, Oct 17, 2022
A tri‐level approach for coordinated transmission and distribution system expansion planning considering deployment of energy hubs
Iet Generation Transmission & Distribution, Aug 19, 2022
Low-Complexity CFO Estimation for FBMC-Based Massive MIMO systems
In this paper, we propose a joint carrier frequency offset (CFO) and channel estimation scheme fo... more In this paper, we propose a joint carrier frequency offset (CFO) and channel estimation scheme for multiuser filter bank multicarrier (FBMC) in the uplink of massive multiple-input multiple-output (MIMO) systems. Due to the large number of antennas at the base station (BS), CFO estimator can impose a substantial amount of computational burden to the system and its performance depends on the type of the training sequence being deployed. To address this issue, we propose a low-complexity CFO estimation technique using Hadamard matrix for training sequences. The proposed technique can estimate both integer and fractional CFO values without any limitation on the CFO acquisition range. Our solution is performed after combining the received signals from different antennas at the BS. Finally, we evaluate the efficacy of our proposed algorithm through numerical results.
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Papers by heidarali shayanfar