Research paper
I. Sepehrirad; R. Ebrahimi; E. Alibeiki; S. Ranjbar
Abstract
Modern power systems deal with different stability concerns due to operation near to their critical margins. Implementing the small energy resources and online islanding schemes perform as a modification scheme for increasing the system overall stability. This paper presents an adaptive approach for ...
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Modern power systems deal with different stability concerns due to operation near to their critical margins. Implementing the small energy resources and online islanding schemes perform as a modification scheme for increasing the system overall stability. This paper presents an adaptive approach for online detection of islanding microgirds in the presence of renewable energy resources consisting of diesel generators. For this issue, based on the concept of thevenin impedance, the microgrid impedance matrix is evaluated. In this case, considering the system angular frequency as an online index within different operating conditions, the islanding operating cases are identified. The proposed scheme uses an online non-model-based index which provides high impedance values in the case of grid-connected operating mode. Through continuous time window, the system impedance derivatives-based matrix is provided which islanding operating scenarios are estimated. In this case, considering a set of analytical evaluations, the required adaptive parameters and corresponding online adjustments are provided. The proposed approach is carried out through a modified microgrid test system consisting of synchronous generators which considering different cases studies, the proposed scheme ability is evaluated. It is revealed that through different case studies about 100 ms time duration is required to estimate an islanding operating condition which the proposed MICI index goes lower than criteria. Simulation results dedicate the effectiveness of the proposed approach for online and fast identification of islanding scenarios with respect to other corresponding techniques.
Research paper
Z. Faramarzi; S. Abazari; S. Hoghoughi; N.R. Abjadi
Abstract
In this paper, Doubly Feed Induction Generator (DFIG) improves the dynamic stability of the power system in the presence of Static Synchronous Series Compensator (SSSC) using nonlinear control theory. The control method used in this study is based on the nonlinear multi-input adaptive backstepping control. ...
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In this paper, Doubly Feed Induction Generator (DFIG) improves the dynamic stability of the power system in the presence of Static Synchronous Series Compensator (SSSC) using nonlinear control theory. The control method used in this study is based on the nonlinear multi-input adaptive backstepping control. The control signals are assigned to DFIG and SSSC and synchronous generator excitation system. The applied control method is more effective than the conventional linear and nonlinear ones which are reported in the literature. Also in this study, control inputs are designed considering their appropriate constraints. The controller coefficients are optimally selected using intelligent algorithms that increase the performance of the controller in terms of achieving stability. The designed control is robust against parameter variations and load changes as well as changing in the location of the disturbances. This method is simulated in two aspects of the synchronous machine model as a third-order model and a second-order one. The methods are implemented on a 39-bus IEEE system and the simulation results show the effectiveness of the proposed control mechanism.
Research paper
H. Shayeghi; A. Rahnama
Abstract
This paper's main purpose is to offer an innovative multistage controller for load-frequency regulation of a standalone interconnected microgrid (SMG). A multistage TDF(FOPI+1) controller is designed, with the first stage being a filter built of the tilting and derivative operators. Transferring the ...
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This paper's main purpose is to offer an innovative multistage controller for load-frequency regulation of a standalone interconnected microgrid (SMG). A multistage TDF(FOPI+1) controller is designed, with the first stage being a filter built of the tilting and derivative operators. Transferring the integrator component to the second stage of the controller and employing its fractional-order (FO) form as a FO proportional-integrator (FOPI) controller results in the latter stage of the controller. To calculate the optimal controller parameters, the recently introduced Bonobo optimization algorithm (BOA) is applied. Besides, the optimization objective function is a mix of the control error signal in each area and the dynamic response characteristics of the system. In complex operating conditions such as sudden changes in power demands, uncertainties in renewable energy units' output, considering nonlinear factors, and parametric uncertainties in a two-area SMG, the performance of the proposed controller is compared with classical and multistage controllers. The results show that the TDF(1+FOPI) controller has a competent dynamic response and can be a suitable choice for performing LFC duties in SMGs. This control strategy's advantages include enhanced controller resistivity in diverse circumstances, faster reaction times, and better dynamic behavior. The results of the five studied scenarios show that using the proposed control strategy, the value of the objective function is improved by an average of more than 50% compared to other classical and conventional controllers. Similarly, improvements of more than 70% and 50% in key integral of time-weighted square error (ITSE) and Integral of absolute error (IAE) time zone indicators, respectively, are among the results of these studies.
Research paper
Z. K. Gurgi; A. I. Ismael; R. A. Mejeed
Abstract
Solar cell efficiency considers an important part of the PV system, the parameters (Io, IL, n, Rs, and Rsh) of solar cell is the main part that effected on efficiency. The Matlab simulation program was used to estimate the three parameters' optimization values and evaluated by the Fminsearch method, ...
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Solar cell efficiency considers an important part of the PV system, the parameters (Io, IL, n, Rs, and Rsh) of solar cell is the main part that effected on efficiency. The Matlab simulation program was used to estimate the three parameters' optimization values and evaluated by the Fminsearch method, they calculated for solar cells measured from 0oC to 100oC for seven temperatures, then make comparing for the results between the Genetic Algorithm method with Neural Network Algorithm. This paper establishes the results are frequently in GA was better than NNA, with the Io being 3.0992 e-7 and IL being 3.8059 found by GA. GA is good if they have the same population size and number of iterations. The value of the objective function (fval) in GA is 0.002856 but in NNA is 0.005518. And also second objective function (fvaltemp) in GA is 0.1035 with a 0.1069 value in NNA. From the side, the execution time considers in the Fminsearch method is less than NNA and GA that being 64.9 s, 781 s, and 289 s respectively.
Research paper
A. Namvar; J. Salehi
Abstract
One of the crucial challenges within the optimal operation of smart cities is coordinated management of multiple energy carriers in the residential buildings owing to disparate and often conflicting objectives. In response to this challenge, this paper proposes a novel conceptual cost-emission-based ...
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One of the crucial challenges within the optimal operation of smart cities is coordinated management of multiple energy carriers in the residential buildings owing to disparate and often conflicting objectives. In response to this challenge, this paper proposes a novel conceptual cost-emission-based scheme for optimal energy-gas use in a smart home in the context of residential energy hubs considering a meaningful trade-off between cost saving and environmental protection. Various energy conversion resources containing energy and heat storage systems, rooftop photovoltaic modules, and also combined heat and power units along with responsible electrical and thermal loads are taken into account in the proposed model. Furthermore, an efficient stochastic scenario-based method is executed to tackle the intense uncertainty associated with photovoltaic production. The proposed model reduces domestic energy consumption and utility costs by incorporating a weighted summation mixed objective function under various system constraints and user preferences, while at t the same time optimal task scheduling and comfort for the resident that it can guarantee a good lifestyle. The presented scheme is carried out on a realistic case study equipped with energy hubs and as expected, introduces its applicability and effectiveness in the optimal energy management of the proposed residential energy hub problem. The simulation results confirm that energy procurement costs can be saved by up to 46.16% and emission costs by 34.07% while maintaining the desired level of comfort for the head of the household.
Research paper
F. Jabari; M. Zeraati; M. Sheibani; H. Arasteh
Abstract
In the semi-autonomous regions and remote islands, the multiple diesel units are usually used for supplying demand and exchanging power with other adjacent zones. In the risk-aware generation companies consisting of diesel engines, photovoltaic panels (PVs), and wind turbines, the uncertain electricity ...
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In the semi-autonomous regions and remote islands, the multiple diesel units are usually used for supplying demand and exchanging power with other adjacent zones. In the risk-aware generation companies consisting of diesel engines, photovoltaic panels (PVs), and wind turbines, the uncertain electricity market prices affect the optimum operating points of these units, the total revenue gained from selling energy to neighbor microgrids, and the daily fuel cost of the diesel generators. Moreover, the output power of the diesel engines is a nonlinear function of their specific fuel consumption at discrete loading intervals. Therefore, this paper aims to present a risk-aware mixed integer nonlinear optimization problem for finding the best generation schedules of the diesel units involving the energy price fluctuations. The total fuel costs of the diesel engines minus the total revenue achieved from procuring power for nearby regions is minimized as a cost objective function satisfying the lower and upper generation bounds in each loading subinterval, the load-generation balance criterion, and the nominal capacities of generating units. The cubic spline interpolation is used for accurately fitting the fuel-power curves of the diesel generators at successive loading subintervals because of its zero norm of residual in comparison with 5${}^{th}$ degree and quadratic polynomials. A benchmark microgrid with six diesel generators, PVs and wind turbines is robustly scheduled using the budget of uncertainty with no need to probability distribution and membership functions of energy prices. It is revealed that this strategy is practical for each price-taker generation company, which desires the risk-aversion production patterns of the diesel power production units against the energy market price uncertainty in a specific operating horizon.
Research paper
F. Shamsini Ghiasvand; K. Afshar; N. Bigdeli
Abstract
In the restructured electricity industry, the electricity retailer, as a profit-oriented company, buys electricity from wholesale electricity markets and sells it to end customers. On the other hand, with the move of the electricity networks towards smart grids, small customers who, in addition to receiving ...
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In the restructured electricity industry, the electricity retailer, as a profit-oriented company, buys electricity from wholesale electricity markets and sells it to end customers. On the other hand, with the move of the electricity networks towards smart grids, small customers who, in addition to receiving energy from the distribution network, can generate power on a small scale, have emerged as prosumers in the electricity market environment. Therefore, the prosumers' aggregator is defined to maximize the profit of a set of prosumers in this environment. In this paper, the energy exchange between the retailer and the aggregator has been modeled as a bi-level game. At a higher level, the retailer, as a leader to maximize its profit or minimize its expenses, offers a price to buy or sell energy to the prosumers' aggregator. The aggregator also decides on the amount of exchange energy to buy or sell, to minimize the energy supply costs required of its consumers according to the retailer's bid price. In this paper, a combined method based on~MILP (Mixed Integer Linear Programming)~and MO (Mayfly Optimization) has been used to find the optimal point of this modeled game. To evaluate the efficiency of the proposed method, the three pricing methods FP (Fixed Pricing),~TOU (Time Of Using), and RTP (Real Time Pricing) as price-based demand response programs have been compared using the proposed algorithm. The simulation results show that among the three pricing methods for customers, the RTP pricing method has the highest profit for the retailer and the lowest cost for the aggregator.
Research paper
M.H. Amirioun; E. Heydarian-Forushani
Abstract
With the advent of advanced measurement and supervisory devices in power systems, wide area measurement systems and real-time monitoring of power systems have become viable. Accordingly, modeling techniques should be updated as well. This paper proposes a transformer asset management model based on real-time ...
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With the advent of advanced measurement and supervisory devices in power systems, wide area measurement systems and real-time monitoring of power systems have become viable. Accordingly, modeling techniques should be updated as well. This paper proposes a transformer asset management model based on real-time condition monitoring in the presence of distributed generation. The model is tested under different case studies and compared with the previous models in which constant failure rate model was used for asset management of transformers. The system cost includes operation, repair, and interruption costs. The objective is to determine the hourly loading of the transformer so that the cost of system is minimized. The long-term objective is to determine the loading pattern of the transformer which guaranties the most economical pattern among various options. Results showed that the proposed model is efficiently capable of returning more accurate responses if real-time monitoring data is used. A set of sensitivity analysis studies are also performed to highlight the impact of each factor separately. The contribution of distributed generators to supply the load is also investigated. Results showed that the use of distributed generators reduces the overall cost of the system by diminishing the risk-based element of the system cost.
