University of Mohaghegh Ardabili
Journal of Operation and Automation in Power Engineering
2322-4576
2423-4567
8
1
2020
02
01
Potentiometric of the Renewable Hybrid System for Electrification of Gorgor Station
1
14
EN
H.
Shayeghi
0000-0003-0398-399X
Technical Engineering Department, University of Mohaghegh Ardabili, Ardabil, Iran
hshayeghi@gmail.com
Y.
Hashemi
Technical Engineering Department, University of Mohaghegh Ardabili, Ardabil, Iran
yashar_hshm@yahoo.com
10.22098/joape.2019.5476.1410
<em>In this paper, an optimal design of the renewable combustion plant has been investigated with the aim of ensuring the required load on the Gorgor station. The purpose of this study is to minimize the cost of the proposed hybrid unit during the period of operation of the designed system simultaneously. Information on the intensity of solar radiation and the intensity of wind blowing in the area are taken and applied in the simulation of the system. The intended target function includes the cost of investment, replacement cost and maintenance cost. After the design phase, the main objective is to check the economic benefits of the project's utilization from the grid and compare it with the renewable electricity system, as well as to calculate the initial investment return in renewable electricity. First, the initial cost of consuming electricity from this project is calculated using a renewable electricity system, and then the cost of project is determined using the national grid. Further, by calculating the annual current cost of each of these combinations, the investment return in each mode is obtained. Various options for the use of renewable energies are surveyed separately and in combination. The technical-economic analysis is done on each of these options and ultimately the best one is presented.</em>
Gorgor station,Electrical energy audit,optimization,Design,Economic analysis
https://joape.uma.ac.ir/article_775.html
https://joape.uma.ac.ir/article_775_eff76b97ad8071b790a7f79223d13a2a.pdf
University of Mohaghegh Ardabili
Journal of Operation and Automation in Power Engineering
2322-4576
2423-4567
8
1
2020
02
01
A Bi-Level Optimization Approach for Optimal Operation of Distribution Networks with Retailers and Micro-grids
15
21
EN
H.
Fateh
Department of Electrical Engineering, Sanandaj Branch, Islamic Azad University, Sanandaj, Iran.
hadi.fateh1990@gmail.com
A.
Safari
Department of Electrical Engineering, Azarbaijan Shahid Madani University, Tabriz, Iran.
asafari1650@yahoo.com
S.
Bahramara
Department of Electrical Engineering, Sanandaj Branch, Islamic Azad University, Sanandaj, Iran.
s_bahramara@yahoo.com
10.22098/joape.2019.5432.1407
Distributed energy resources (DERs) including distributed generators (DGs) and controllable loads (CLs) are managed in the form of several microgrids (MGs) in active distributions networks (ADNs) to meet the demand locally. On the other hand, some loads of distribution networks (DNs) can be supplied by retailers which participate in wholesale energy markets. Therefore, there are several decision makers in DNs which their cooperation should be modeled for optimal operation of the network. For this purpose, a bi-level optimization approach is proposed in this paper to model the cooperation between retailers and MGs in DNs. In the proposed model, the aim of the upper level (leader) and lower level (follower) problems are to maximize the profit of retailers and to minimize the cost of MGs, respectively. To solve the proposed multi-objective bi-level optimization model, multi-objective Particle Swarm Optimization (MOPSO) algorithm is employed. The effectiveness of the proposed bi-level model and its solution methodology is investigated in the numerical results.
Bi-level Optimization,Micro-grids,Particle Swarm Optimization,Retailer
https://joape.uma.ac.ir/article_773.html
https://joape.uma.ac.ir/article_773_5c5e9fc6b3705ef2fd7a00c27f97be21.pdf
University of Mohaghegh Ardabili
Journal of Operation and Automation in Power Engineering
2322-4576
2423-4567
8
1
2020
02
01
Stochastic Assessment of the Renewable–Based Multiple Energy System in the Presence of Thermal Energy Market and Demand Response Program
22
31
EN
H.
Mousavi-Sarabi
Faculty of Electrical and Computer Engineering, University of Tabriz, Tabriz, Iran.
hessam.mousavi.7@gmail.com
M.
Jadidbonab
0000-0003-3772-9770
Faculty of Electrical and Computer Engineering, University of Tabriz, Tabriz, Iran.
mohammad.jadidbonab@gmail.com
B.
Mohammadi ivatloo
Faculty of Electrical and Computer Engineering, University of Tabriz, Tabriz, Iran.
ivatloo@gmail.com
10.22098/joape.2019.5072.1382
The impact of different energy storages on power systems has become more important due to the development of energy storage technologies. This paper optimizes the stochastic scheduling of a wind-based multiple energy system (MES) and evaluates the operation of the proposed system in combination with electrical and thermal demand-response programs and the three-mode CAES (TM-CAES) unit. The proposed wind-integrated MES consists of a TM-CAES unit, electrical boiler unit, and thermal storage system which can exchange thermal energy with the local thermal network and exchange electricity with the local grid. The electrical and thermal demands as well as wind farm generation are modeled as a scenario-based stochastic problem using the Monte Carlo simulation method. Afterwards, the computational burden is reduced by applying a proper scenario-reduction algorithm to initial scenarios. Finally, the proposed methodology is implemented to a case study to evaluate the effectiveness and appropriateness of the proposed method.
Three mode compressed air energy storage (TM-CAES),thermal energy market,Stochastic programming,wind generation,demand response program
https://joape.uma.ac.ir/article_778.html
https://joape.uma.ac.ir/article_778_64981506aeab33a060edece71c450189.pdf
University of Mohaghegh Ardabili
Journal of Operation and Automation in Power Engineering
2322-4576
2423-4567
8
1
2020
02
01
Selective Harmonics Elimination Technique in Cascaded H-Bridge Multi-Level Inverters Using the Salp Swarm Optimization Algorithm
32
42
EN
M.
Hosseinpour
0000-0001-5074-4604
Department of Electrical and Computer Engineering, University of Mohaghegh Ardabili, Ardabil, Iran.
hoseinpour.majid@gmail.com
S.
Mansoori
Department of Electrical and Computer Engineering, University of Mohaghegh Ardabili, Ardabil, Iran.
saeede.mansoori@gmail.com
H.
Shayeghi
0000-0003-0398-399X
Department of Electrical and Computer Engineering, University of Mohaghegh Ardabili, Ardabil, Iran.
hshayeghi@uma.ac.ir
10.22098/joape.2019.5545.1418
A new optimization method is proposed in this paper for finding the firing angles in multi-level voltage source inverters to eliminate low-order selective harmonics and reduce total harmonic distortion (THD) value of the output voltage. For thid end, Fourier series is used for calculating objective function and selecting specific harmonics. Regarding the nature and complexity of the employed non-algebraic equations in the optimization problem for achieving the optimal angle in the multi-level inverter, a recent developed meta-heuristic method known as Salp Swarm Algorithm (SSA) is presented. In the proposed method, the optimal angles for a given multi-level inverter are obtained based on the objective function such that the magnitudes of the selective harmonics and the THD value of the output voltage are reduced. The method is applied on a cascaded H-bridge type five-level inverter. The simulation results illustrate that the magnitudes of the selective harmonics and the THD percentage of the output voltage have been reduced through selecting the optimal switching angle by the proposed optimization algorithm. The result of this method are compared with those of SPWM method. Moreover, the performance of SSA algorithm with respect to PSO algorithm is compared which shows its rapid convergence speed and less THD value.
"Elimination of selective harmonics",'Cascaded multi-level H-bridge inverter","Total harmonic distortion (THD)","Salp swarm optimization algorithm"
https://joape.uma.ac.ir/article_779.html
https://joape.uma.ac.ir/article_779_44989d8539f38b3764d4dec563106ebd.pdf
University of Mohaghegh Ardabili
Journal of Operation and Automation in Power Engineering
2322-4576
2423-4567
8
1
2020
02
01
Energy management of virtual power plant to participate in the electricity market using robust optimization
43
56
EN
M.
Mohebbi-Gharavanlou
0000-0002-4299-6876
Faculty of Electrical and Computer Engineering, University of Tabriz, Tabriz, Iran.
mehran.mohebbi96@ms.tabrizu.ac.ir
S.
Nojavan
0000-0003-4110-2866
Department of Electrical Engineering, University of Bonab, Bonab, Iran.
sayyad.nojavan@bonabu.ac.ir
K.
Zareh
Faculty of Electrical and Computer Engineering, University of Tabriz, Tabriz, Iran.
kazem.zare@tabrizu.ac.ir
10.22098/joape.2019.5362.1400
Virtual power plant (VPP) can be studied to investigate how energy is purchased or sold in the presence of electricity market price uncertainty. The VPP uses different intermittent distributed sources such as wind turbine, flexible loads, and locational marginal prices (LMPs) in order to obtain profit. VPP should propose bidding/offering curves to buy/sell from/to day-ahead market. In this paper, robust optimization approach is proposed to achieve the optimal offering and bidding curves which should be submitted to the day-ahead market. This paper uses mixed-integer linear programming (MILP) model under GAMS software based on robust optimization approach to make appropriate decision on uncertainty to get profit which is resistance versus price uncertainty. The offering and bidding curves of VPP are obtained based on derived data from results. The proposed method, due to less computing, is also easy to trace the problem for the VPP operator. Finally, the price curves are obtained in terms of power for each hour, which operator uses the benefits of increasing or decreasing market prices for its plans. Also, results of comparing deterministic and RO cases are presented. Results demonstrate that profit amount in maximum robustness case is reduced 25.91 % and VPP is resisted against day-ahead market price uncertainty.
Virtual power plant,Electricity market uncertainty,Robust optimization approach,Bidding and offering curves,Distributed energy resources
https://joape.uma.ac.ir/article_782.html
https://joape.uma.ac.ir/article_782_5505c388c0742d22d0e1127eb502ffca.pdf
University of Mohaghegh Ardabili
Journal of Operation and Automation in Power Engineering
2322-4576
2423-4567
8
1
2020
02
01
FOA: ‘Following’ Optimization Algorithm for solving Power engineering optimization problems
57
64
EN
M.
Dehghani
Department of Electrical and Electronics Engineering, Shiraz University of Technology, Shiraz, Iran.
adanbax@gmail.com
M.
Mardaneh
Department of Electrical and Electronics Engineering, Shiraz University of Technology, Shiraz, Iran.
mardaneh@sutech.ac.ir
O. P.
Malik
Department of Electrical Engineering, University of Calgary, Calgary Alberta Canada.
maliko@ucalgary.ca
10.22098/joape.2019.5522.1414
These days randomized-based population optimization algorithms are in wide use in different branches of science such as bioinformatics, chemical physics andpower engineering. An important group of these algorithms is inspired by physical processes or entities’ behavior. A new approach of applying optimization-based social relationships among the members of a community is investigated in this paper. In the proposed algorithm, search factors are indeed members of the community who try to improve the community by ‘following’ each other. FOA implemented on 23 well-known benchmark test functions. It is compared with eight optimization algorithms. The paper also considers for solving optimal placement of Distributed Generation (DG). The obtained results show that FOA is able to provide better results as compared to the other well-known optimization algorithms.
optimization,social relationships,heuristic algorithms,following optimization, following
https://joape.uma.ac.ir/article_784.html
https://joape.uma.ac.ir/article_784_ac38155da2b4a0a2d65cb69530c79d23.pdf
University of Mohaghegh Ardabili
Journal of Operation and Automation in Power Engineering
2322-4576
2423-4567
8
1
2020
02
01
Multi-Area State Estimation Based on PMU Measurements in Distribution Networks
65
74
EN
O.
Eghbali
Faculty of Electrical Engineering, Sahand University of Technology, Tabriz, Iran.
om_eghbali@sut.ac.ir
R.
Kazemzadeh
Faculty of Electrical Engineering, Sahand University of Technology, Tabriz, Iran.
r.kazemzadeh@sut.ac.ir
K.
Amiri
Faculty of Electrical Engineering, Sahand University of Technology, Tabriz, Iran.
k_amiri@sut.ac.ir
10.22098/joape.2019.5798.1434
State estimation in the energy management center of active distribution networks has attracted many attentions. Considering an increase in complexity and real-time management of active distribution networks and knowing the network information at each time instant are necessary. This article presents a two-step multi-area state estimation method in balanced active distribution networks. The proposed method is based on the location of PMU measurements of the network. The network is divided into several sub-areas about PMUs in the first step. A local sate estimation is implemented in each sub-area. The estimated values of the first step along with real measurements are used as measurements for second step estimation. The measurements are located in each sub-area using these values based on the ellipse area method, and the best location of measurements is extracted. Therefore, a second step state estimation including integrated state estimation of the whole network is performed by using the measurements obtained and located from the first step. The estimation results of the first step are used in the second step which improve the estimation accuracy. Simulations are performed on a standard IEEE 69-bus network to validate the proposed method.
measurements location,state estimation,synchronous measurements,two-step state estimation,zoning distribution networks
https://joape.uma.ac.ir/article_807.html
https://joape.uma.ac.ir/article_807_922eccb415dfc79e25950f2f5f2e7aed.pdf
University of Mohaghegh Ardabili
Journal of Operation and Automation in Power Engineering
2322-4576
2423-4567
8
1
2020
02
01
SCA based Fractional-order PID Controller Considering Delayed EV Aggregators
75
85
EN
F.
Babaei
0000-0001-6477-3748
Department of Electrical Engineering, Shahid Madani Azarbaijan University, Tabriz, Iran
farshad291371@gmail.com
A.
Safari
Department of Electrical Engineering, Shahid Madani Azarbaijan University, Tabriz, Iran
asafari1650@yahoo.com
10.22098/joape.2019.6088.1460
The EVs battery has the ability to enhance the balance between the load demand and power generation units. The EV aggregators to manage the random behaviour of EV owners and increasing EVs participation in the ancillary services market are employed. The presence of aggregators could lead to time-varying delay in load frequency control (LFC) schemes. The effects of these delays must be considered in the LFC controller design. Due to the dependency of controller effectiveness on its parameters, these parameters should be designed in such a way that the LFC system has desired performance in the presence of time-varying delay. Therefore, a Sine Cosine Algorithm (SCA) is utilized to adjust the fractional-order PID (FOPID) controller coefficients. Also, some evaluations are performed about the proposed LFC performance by integral absolute error (IAE) indicator. Simulations are carried out in both single and two area LFC system containing EV aggregators with time-varying delay. According to results, the proposed controller has fewer frequency variations in contrast to other controllers presented in the case studies. The obtained output could be considered as a solution to evaluate the proposed controller performance for damping the frequency oscillations in the delayed LFC system.
Electric vehicle aggregator,Time-varying delay,Fractional-order PID,Sine cosine algorithm,Load frequency control
https://joape.uma.ac.ir/article_808.html
https://joape.uma.ac.ir/article_808_3ceb7f93070b19e90417e0d0a73693d5.pdf