| 1. |
- Sabouri, Mohammad, et al.
(författare)
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Increasing the resiliency of power systems in presence of GPS spoofing attacks: A data-driven deep-learning algorithm
- 2023
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Ingår i: IET Generation, Transmission & Distribution. - : Institution of Engineering and Technology (IET). - 1751-8687 .- 1751-8695. ; 17:20, s. 4525-4540
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Tidskriftsartikel (refereegranskat)abstract
- The growing use of wireless technologies in power systems has raised concerns about cybersecurity, particularly regarding GPS spoofing attacks (GSAs). These attacks manipulate GPS data, leading to modifications in the phase angle of phasor measurement units (PMUs). In this paper, a Deep-learning GPS-Spoofing Counteraction (DLGSC) algorithm is proposed, utilizing PMU data for GSA detection and PMU data correction. The algorithm incorporates a recurrent neural network (RNN) and a set of long short-term memory (LSTM) units separately, for signal correction after attack detection. Unlike existing methods that struggle with simultaneous attacks or they are static methods, DLGSC tackles these challenges by leveraging deep learning techniques. By selecting appropriate features for GSA detection, DLGSC achieves accurate results. The algorithm is evaluated on standard IEEE 14-bus and IEEE 39-bus power systems, and its performance is compared to statistical, dynamic, and Deep Learning (DL) methods in the literature. Additionally, an experimental setup is designed to validate the algorithm in a laboratory environment. Results demonstrate the easy-implementable DLGSC algorithm's satisfactory real-time performance in various scenarios, such as load variations and noise, achieving over 98% accuracy. Notably, DLGSC is cable of detecting multiple GSAs on different PMUs.
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| 2. |
- Gholami, Amir Hossein, et al.
(författare)
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Decentralized Optimization in Scheduling Virtual Power Plant (VPP)
- 2023
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Ingår i: 2023 31st International Conference on Electrical Engineering, ICEE 2023. - : Institute of Electrical and Electronics Engineers (IEEE). - 9798350312560 ; , s. 420-425
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Konferensbidrag (refereegranskat)abstract
- The scheduling of virtual power plants (VPPs) has received much attention in the last few years. VPP refers to the integration of several power plant units together, which is considered as a single power plant. In this paper, three VPPs are considered, each of which includes different power plant units and must supply the desired load. Besides supplying the desired load, they should maximize their profit. Decentralized optimization method has been used to optimize these three VPPs. The reason for using decentralized method is to increase network security and also to not need a central computer. On the other hand, using the decentralized optimization method increases the speed of problem solving. Finally, the obtained results have been compared with the centralized method. The simulations show that almost the same result has been obtained by using different optimization methods. These results increase the tendency to use decentralized methods in VPPs.
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| 3. |
- Hesamzadeh, Mohammad Reza, et al.
(författare)
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Transmission Capacity Expansion in Imperfectly Competitive Power Markets
- 2014
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Ingår i: IEEE Transactions on Power Systems. - 0885-8950 .- 1558-0679. ; 29:1, s. 62-71
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Tidskriftsartikel (refereegranskat)abstract
- This paper proposes a mathematical model for transmission planning in an environment where there is imperfect competition in electricity supply industry. The model is developed based on the concept of the leader-followers game in applied mathematics. The leader of the game is the transmission planner and the followers are the strategic electricity producing firms. The reaction of the strategic electricity producing firms to the transmission planning decision is modeled using the introduced concept of the worst-Cournot-Nash equilibrium. The worst-Cournot-Nash equilibrium can handle the multiple Nash equilibria problem. The whole mathematical formulation is a bilevel mixed-integer linear programming problem. This formulation is achieved using the Karush-Kuhn-Tucker optimality conditions and a binary mapping approach. The application of the proposed approach to the three-node example system and the modified six-node Garver's example system are studied. The transmission planning with perfect competition is formulated and used as the benchmark. The numerical results show that the proposed approach in this paper can efficiently allocate the additional transmission capacity to the transmission grid such that it reduces the market power cost in the electricity supply industry. However, further studies should be carried out to scale up the proposed approach to the larger case studies.
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| 4. |
- Hesamzadeh, Mohammad Reza, et al.
(författare)
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Transmission Network Investment in a Time of Transition
- 2021
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Ingår i: Economics of Energy & Environmental Policy. - : International Association for Energy Economics (IAEE). - 2160-5882 .- 2160-5890. ; 10:2, s. 93-114
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Tidskriftsartikel (refereegranskat)abstract
- The electricity sector is in an unprecedented time of transition. The industry is in the process of adjusting from traditional fossil-fuel to renewable generation, from large-scale to distributed generation and from vertically-integrated monopolies to verticallyseparated industrial structuresunder diverse formsof competition. Efficient transmission investment planning and regulation is more important than ever, but this task has become extremely complex. Increasing penetration of intermittent generation makes predicting network flow patterns increasingly difficult. Moreover, the potential role for hydrogen as an alternative energy source in both domestic and transportation uses, makes predicting the long-term future of electricity demand more uncertain than at any time in its history. In this paper, we review key issues in electricity transmission investment and regulation. We start by reviewing the task of the theoretical well-intentioned network planner, and the complications that arise when transmission investment is separated from generation investment. We then review the issues associated with governing the transmission planner, including the question whether it is possible to design a financial mechanism which delivers correct incentives. We also discuss the question of whether it is possible to design a mechanism which allows transmission investment to be left entirely to the private sector. We finish with a summary of the key future challenges facing the sector in this time of transition.
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| 5. |
- Nazari, Mohammad, et al.
(författare)
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On-line control of multi-terminal HVDC systems connected to offshore wind farms using the POF-based multi-agent approarch
- 2015
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Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- Multi-terminal HVDC systems are an attractive option to connect offshore wind farms to onshore grids. Although scheduling the multi-terminal HVDC system is based on forecasted wind power, the forecasted values may differ from their real time ones. This paper presents a new controller based on multi-agent system which optimally tries to follow the variations of real time wind power outputs. Since a fast optimal power flow algorithm is needed, a convexified AC-OPF model which can be efficiently solved through interior point methods (IPMs) is embedded into the proposed online controller. Simulations are carried out and validated using GAMS platform and MATLAB/Simulink.
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| 6. |
- Sohrabi, Farnaz, et al.
(författare)
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Coordinated bidding of multi-product charging station in electricity markets using rolling planning and sample average approximation
- 2023
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Ingår i: International Journal of Electrical Power & Energy Systems. - : Elsevier BV. - 0142-0615 .- 1879-3517. ; 146, s. 108786-
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Tidskriftsartikel (refereegranskat)abstract
- Recently, there has been an urgent tendency to steer the transport system towards zero-emission. Along natural gas vehicles, electric and hydrogen vehicles represent a promising way to a low-carbon system. Since the development of these vehicles relies on advances of refueling stations, their economic and operational aspects need to be considered. Therefore, this paper addresses a multi-product charging station for refilling electric, hydrogen and natural gas vehicles. The station participates in day-ahead and intra-day markets where the market price is subject to the uncertainty. For charging station participating in sequential markets with different prices, it is necessary to consider the coordinated bidding. Taking into account the sequential clearing of these markets and the gradual realization of market prices, the bidding problem is formulated as a two-stage stochastic program. In order to solve this large-scale stochastic program with a huge number of scenarios, the rolling planning method in combination with sample average approximation and SCENRED tool are applied. The study aims to attain the optimal operation of devices and bidding curves of the charging station in order to maximize its profit. The obtained average optimality gap based on Monte Carlo sampling approach, which is less than 1%, proves the effectiveness of our proposed algorithm in solving this large scale stochastic optimization. The submitted bidding curves to the intra-day market are found to be dependent on changes in the day-ahead market prices. Tornado diagrams indicate that the selling price and demand of electricity are ranked as the most effective factors on profit.
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| 7. |
- Abedi, Amin, et al.
(författare)
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Adaptive robust vulnerability analysis of power systems under uncertainty : A multilevel OPF-based optimization approach
- 2022
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Ingår i: International Journal of Electrical Power & Energy Systems. - : Elsevier BV. - 0142-0615 .- 1879-3517. ; 134
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Tidskriftsartikel (refereegranskat)abstract
- With the growing level of uncertainties in today's power systems, the vulnerability analysis of a power system with uncertain parameters becomes a must. This paper proposes a two-stage adaptive robust optimization (ARO) model for the vulnerability analysis of power systems. The main goal is to immunize the solutions against all possible realizations of the modeled uncertainty. In doing so, the uncertainties are defined by some predetermined intervals defined around the expected values of uncertain parameters. In our model, there are a set of first-stage decisions made before the uncertainty is revealed (attacker decision) and a set of second-stage decisions made after the realization of uncertainties (defender decision). This setup is formulated as a mixedinteger trilevel nonlinear program (MITNLP). Then, we recast the proposed trilevel program to a single-level mixed-integer linear program (MILP), applying the strong duality theorem (SDT) and appropriate linearization approaches. The efficient off-the-shelf solvers can guarantee the global optimum of our final MILP model. We also prove a lemma which makes our model much easier to solve. The results carried out on the IEEE RTS and modified Iran's power system show the performance of our model to assess the power system vulnerability under uncertainty.
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| 8. |
- Abedi, Amin, et al.
(författare)
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An ACOPF-based bilevel optimization approach for vulnerability assessment of a power system
- 2021
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Ingår i: International Journal of Electrical Power & Energy Systems. - : Elsevier Ltd. - 0142-0615 .- 1879-3517. ; 125
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Tidskriftsartikel (refereegranskat)abstract
- This paper examines the effects of reactive power dispatch, losses, and voltage profile on the results of the interdiction model to analyze the vulnerability of the power system. First, an attacker-defender Stackelberg game is introduced. The introduced game is modeled as a bilevel optimization problem where the attacker is modeled in the upper level and the defender is modeled in the lower level. The AC optimal power flow (ACOPF) is proposed as the defender's tool in the lower-level problem to mitigate the attack consequences. Our proposed ACOPF-based mathematical framework is inherently a mixed-integer bilevel nonlinear program (MIBNLP) that is NP-hard and computationally challenging. This paper linearizes and then transforms it into a one-level mixed-integer linear program (MILP) using the duality theory and some proposed linearization techniques. The proposed MILP model can be solved to the global optimum using state-of-the-art solvers such as Cplex. Numerical results on two IEEE systems and Iran's 400-kV transmission network demonstrate the performance of the proposed MILP for vulnerability assessment. We have also compared our MILP model with the DCOPF-based approach proposed in the relevant literature. The comparative results show that the reported damage measured in terms of load shedding for the DCOPF-based approach is always lower than or equal to that for the ACOPF-based approach and these models report a different set of critical lines, especially in more stressed and larger power systems. Also, the effectiveness and feasibility of the proposed MILP model for power-system vulnerability analysis are discussed and highlighted.
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| 9. |
- Abolpour, Roozbeh, et al.
(författare)
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A New Power Flow Model With a Single Nonconvex Quadratic Constraint : The LMI Approach
- 2022
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Ingår i: IEEE Transactions on Power Systems. - : Institute of Electrical and Electronics Engineers (IEEE). - 0885-8950 .- 1558-0679. ; 37:2, s. 1218-1229
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Tidskriftsartikel (refereegranskat)abstract
- In this paper, we propose a new mathematical model for power flow problem based on the linear and nonlinear matrix inequality theory. We start with rectangular model of power flow (PF) problem and then reformulate it as a Bilinear Matrix Inequality (BMI) model. A Theorem is proved which is able to convert this BMI model to a Linear Matrix Inequality (LMI) model along with One Nonconvex Quadratic Constraint (ONQC). Our proposed LMI-ONQC model for PF problem has only one single nonconvex quadratic constraint irrespective of the network size, while in the rectangular and BMI models the number of nonconvex constraints grows as the network size grows. This interesting property leads to reduced complexity level in our LMI-ONQC model which in turn makes it easier to solve for finding a PF solution. The non-conservativeness, iterative LMI solvability, well-defined and easy-to-understand geometry and pathwise connectivity of feasibility region are other important properties of proposed LMI-ONQC model which are discussed in this paper. An illustrative two-bus example is carefully studied to show different properties of our LMI-ONQC model. We have also tested our LMI-ONQC model on 30 different power-system cases including four ill-conditioned systems and compared it with a group of existing approaches. The numerical results show the promising performance of our LMI-ONQC model and its solution algorithm to find a PF solution.
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| 10. |
- Abolpour, Roozbeh, et al.
(författare)
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Inside-Ellipsoid Outside-Sphere (IEOS) model for general bilinear feasibility problems : Feasibility analysis and solution algorithm
- 2023
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Ingår i: Automatica. - : Elsevier BV. - 0005-1098 .- 1873-2836. ; 147, s. 110738-
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Tidskriftsartikel (refereegranskat)abstract
- This paper deals with general bilinear feasibility problems. A nonlinear transformation is introduced that reformulates a general bilinear feasibility problem as a Linear Matrix Inequality (LMI) problem augmented with a single non-convex quadratic constraint. The single non-convex quadratic constraint has a regular concave constraint function. Due to the LMI part of this formulation, it is easier to analyze, and we prove that the solution space of this formulation is located inside several ellipsoids and outside a sphere. This leads to our proposed Inside-Ellipsoid and Outside-Sphere (IEOS) model for general bilinear feasibility problems. Then, the feasibility analysis of our proposed IEOS model is performed. The related necessary feasibility conditions and sufficient feasibility conditions are theoretically developed. Moreover, an iterative algorithm for solving our IEOS model is also proposed.Two applications including matrix-factorization problem in control systems and power-flow prob-lem in power systems are considered to evaluate the practicality of our proposed approach. Both problems are formulated as IEOS models. It is shown that our proposed model can provide more accurate solutions to these problems as compared to previous competing approaches in the relevant literature.
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