A. Jasemi; H. Abdi
Abstract
As a basic tool in power system control and operation, the optimal power flow (OPF) problem searches the optimal operation point via minimizing different objectives and maintaining the control variables within their applicable regions. In recent years, this problem has encountered many challenges due ...
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As a basic tool in power system control and operation, the optimal power flow (OPF) problem searches the optimal operation point via minimizing different objectives and maintaining the control variables within their applicable regions. In recent years, this problem has encountered many challenges due to the presence of renewable energy sources, which has led introducing of a combinatorial type of power networks known as AC/DC hybrid power systems. In this paper, the OPF problem is proposed in an AC/DC hybrid microgrid, including wind power plants. For the first time, the mentioned problem is considered as a multi-objective optimization problem via minimizing fuel cost and emission. The problem is modeled while considering the power flow equations, the voltage limits in AC and DC buses, the AC voltage angle limits, and the firing angle of the converters. Also, due to the uncertain power generated by wind power plants, the probabilistic OPF problem is modeled by the five-point estimation method. To solve the problem, the "fmincon" function in MATLAB software is used by applying the IP algorithm. The simulation case study on a 13-bus sample MG verifies the effectiveness of the proposed method. The numerical results confirm that increasing the wind farm capacity from 14.54 MW to 113 MW, will be led to increasing the fuel cost from 10% to 61%, in case of including the power losses compared to the condition in which they are neglected. It is also observed that in terms of different weights, the total air pollution including the power losses is 2.30 to 2.40 times higher than the total pollution without electrical losses
P. Hajiamosha; A. Rastgou; H. Abdi; S. Bahramara
Abstract
The important role of electricity generation in the power system is evident and is growing more and more with innovative technologies and requirements. Hence, addressing the combined heat and power economic dispatch (CHPED) as one of the relatively new issues in the power system operation and control ...
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The important role of electricity generation in the power system is evident and is growing more and more with innovative technologies and requirements. Hence, addressing the combined heat and power economic dispatch (CHPED) as one of the relatively new issues in the power system operation and control is more importance. Since the CHPED problem is a non-smooth, highly non-linear, and non-convex one, it is required to solve it so that an optimal global solution can be achieved. In this paper, by applying the piece-wise linearization approach the CHPED problem is solved so that the problem reformulated to a quadratic optimization problem with linear and quadratic constraints. To demonstrate the applicability of the proposed model, four case studies are implemented in the GAMS software environment and the results compared to the literature.
Energy Management
K. Masoudi; H. Abdi
Abstract
This paper deals with day-ahead programming under uncertainties in microgrids (MGs). A two-stage stochastic programming with the fixed recourse approach was adopted. The studied MG was considered in the grid-connected mode with the capability of power exchange with the upstream network. Uncertain electricity ...
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This paper deals with day-ahead programming under uncertainties in microgrids (MGs). A two-stage stochastic programming with the fixed recourse approach was adopted. The studied MG was considered in the grid-connected mode with the capability of power exchange with the upstream network. Uncertain electricity market prices, unpredictable load demand, and uncertain wind and solar power values, due to intrinsically stochastic weather changes, were also considered in the proposed method. To cope with uncertainties, the scenario-based stochastic approach was utilized, and the reduction of the environmental emissions generated by the power resources was regarded as the second objective, besides the cost of units’ operation. The ɛ-constraint method was employed to deal with the presented multi-objective optimization problem, and the simulations were performed on a sample MG with one month of real data. The results demonstrated the applicability and effectiveness of the proposed techniques in real-world conditions.
Planing & Reliability
S. Abbasi; H. Abdi
Abstract
Although significant private investment is absorbed in different sectors of power systems, transmission sector is still suffering from appropriate private investment. This is because of the pricing policies of transmission services, tariffs, and especially for investment risks. Investment risks are due ...
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Although significant private investment is absorbed in different sectors of power systems, transmission sector is still suffering from appropriate private investment. This is because of the pricing policies of transmission services, tariffs, and especially for investment risks. Investment risks are due to the uncertain behaviour of power systems that discourage investors to invest in the transmission sectors. In uncertain environment of power systems, a proper method is needed to find investment attractive transmission lines with high investment return and low risk. Nowadays, wind power generation has a significant portion in total generation of most power systems. However, its uncontrollable and variable nature has turned it as a main source of uncertainty in power systems. Accordingly, the wind power generation can play a fundamental role in increasing investment risk in the transmission networks. In this paper, impact of this type of generation on investment risk and returned investment cost in transmission network is investigated. With different levels of wind power penetration, the recovered values of investment cost and risk cost in transmission network are calculated and compared. This is a simple method to find investment attractive lines in presence of uncertainties. Wherein, transmission network expansion planning (TNEP) is formulated as a multi-objective optimization problem with objectives of minimizing the investment cost, maximizing the recovered investment cost and network reliability. The point estimation method (PEM) is used to address wind speed variations at wind farms sites in the optimization problem, and the NSGA II algorithm is applied to determine the trade-off regions between the TNEP objective functions. The fuzzy satisfying method is used to decide about the final optimal plan. The proposed methodology is applied on the IEEE 24-bus RTS and simplified Iran 400 kV network.
Power System Operation
Ehsan Dehnavi; Hamdi Abdi,; Farid Mohammadi
Volume 4, Issue 1 , June 2016, , Pages 29-41
Abstract
Nowadays, demand response programs (DRPs) play an important role in price reduction and reliability improvement. In this paper, an optimal integrated model for the emergency demand response program (EDRP) and dynamic economic emission dispatch (DEED) problem has been developed. Customer’s behavior ...
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Nowadays, demand response programs (DRPs) play an important role in price reduction and reliability improvement. In this paper, an optimal integrated model for the emergency demand response program (EDRP) and dynamic economic emission dispatch (DEED) problem has been developed. Customer’s behavior is modeled based on the price elasticity matrix (PEM) by which the level of DRP is determined for a given type of customer. Valve-point loading effect, prohibited operating zones (POZs), and the other non-linear constraints make the DEED problem into a non-convex and non-smooth multi-objective optimization problem. In the proposed model, the fuel cost and emission are minimized and the optimal incentive is determined simultaneously. The imperialist competitive algorithm (ICA) has solved the combined problem. The proposed model is applied on a ten units test system and results indicate the practical benefits of the proposed model. Finally, depending on different policies, DRPs are prioritized by using strategy success indices.
Distribution Systems
Soheil Derafshi Beigvand; Hamdi Abdi,
Volume 3, Issue 2 , December 2015, , Pages 102-115
Abstract
This paper proposes an Optimal Power Flow (OPF) algorithm by Direct Load Control (DLC) programs to optimize the operational cost of smart grids considering various scenarios based on different constraints. The cost function includes active power production cost of available power sources and a novel ...
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This paper proposes an Optimal Power Flow (OPF) algorithm by Direct Load Control (DLC) programs to optimize the operational cost of smart grids considering various scenarios based on different constraints. The cost function includes active power production cost of available power sources and a novel flexible load curtailment cost associated with DLC programs. The load curtailment cost is based on a virtual generator for each load (which participates in DLC program). To implement the load curtailment in the objective function, we consider incentive payments for participants and a load shedding priority list in some events. The proposed OPF methodology is applied to IEEE 14, 30-bus, and 13-node industrial power systems as three examples of the smart grids, respectively. The numerical results of the proposed algorithm are compared with the results obtained by applying MATPOWER to the nominal case by using the DLC programs. It is shown that the suggested approach converges to a better quality solution in an acceptable computation time.
