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Presents closure to discussions held on the above named paper.
M. Esfahani; Nima Amjady; B. Bagheri; Nikos D. Hatziargyriou. Closure to Discussion on “Robust Resiliency-Oriented Operation of Active Distribution Networks Considering Windstorms”. IEEE Transactions on Power Systems 2021, 36, 4901 -4901.
AMA StyleM. Esfahani, Nima Amjady, B. Bagheri, Nikos D. Hatziargyriou. Closure to Discussion on “Robust Resiliency-Oriented Operation of Active Distribution Networks Considering Windstorms”. IEEE Transactions on Power Systems. 2021; 36 (5):4901-4901.
Chicago/Turabian StyleM. Esfahani; Nima Amjady; B. Bagheri; Nikos D. Hatziargyriou. 2021. "Closure to Discussion on “Robust Resiliency-Oriented Operation of Active Distribution Networks Considering Windstorms”." IEEE Transactions on Power Systems 36, no. 5: 4901-4901.
The emergence of renewable energy technologies in distribution networks and microgrids has raised the importance of integrating energy storage systems into these grids. However, their high investment costs deter decision makers from effectively expanding these assets. In this paper, a cooperative community storage expansion plan is proposed as a bargaining problem between distribution company and private microgrids to jointly invest in energy storage systems. By doing so, each party takes a quota of shared investment costs and thus the burden of high investment costs is alleviated. A modified version of the Nash bargaining theory approach is proposed to implement the cooperative framework in a fair manner. Two cases of non-cooperation and cooperation are distinctively defined and the merits of cooperation are illustrated. The lead acid battery is considered as the storage candidate, for which a novel linearized lifetime model and replacement approach is also proposed. The bargaining results presented on a distribution network test case indicate that through the proposed cooperation, all players receive positive surpluses by decreasing their costs or increasing their revenues. Thus, both distribution company and microgrids would have incentives to participate in the proposed cooperation. Moreover, the superiority of the proposed modified Nash bargaining theory compared to conventional Nash bargaining theory in terms of cooperation fairness is illustrated. Finally, the ability of the proposed cooperative community storage expansion plan to effectively manage cooperative storage installations and replacements is demonstrated.
Amirali Nazari; Reza Keypour; Nima Amjady. Joint investment of community energy storage systems in distribution networks using modified Nash bargaining theory. Applied Energy 2021, 301, 117475 .
AMA StyleAmirali Nazari, Reza Keypour, Nima Amjady. Joint investment of community energy storage systems in distribution networks using modified Nash bargaining theory. Applied Energy. 2021; 301 ():117475.
Chicago/Turabian StyleAmirali Nazari; Reza Keypour; Nima Amjady. 2021. "Joint investment of community energy storage systems in distribution networks using modified Nash bargaining theory." Applied Energy 301, no. : 117475.
An aggregation of distributed energy resources (DERs) can bring economic and technical benefits for the DER owners and system operator. However, the operation of DERs encounters various uncertainties, which can seriously impact the benefits of DER aggregation. This article presents a new operation optimization approach for an aggregator of DERs considering the unavailability of DERs (as discrete uncertainty sources) as well as forecast uncertainties of electricity prices, solar powers, and wind powers (as continuous uncertainty sources). The proposed approach for DER aggregator (DERA) operation optimization comprises stochastic multiobjective information-gap decision theory (IGDT) to model these discrete and continuous uncertain variables. Moreover, a hybrid endogenous/exogenous scenario generation method is incorporated into the proposed approach to enhance the efficiency of the stochastic programming part by producing decision-dependent scenario trees. The proposed approach is formulated as a nested bilevel optimization model. The proposed approach is compared with other DERA operation optimization models using an out-of-sample analysis method. The comparative results illustrate the superiority of the proposed stochastic multiobjective IGDT approach over various deterministic, stochastic, and IGDT methods. In addition, the high tractability of the proposed solution method is illustrated, while its linearization error for the stochastic multiobjective IGDT problem is well below 1%.
Mohsen Yazdaninejad; Nima Amjady; Nikos D. Hatziargyriou. Nested Bilevel Optimization for DERA Operation Strategy: A Stochastic Multiobjective IGDT Model With Hybrid Endogenous/Exogenous Scenarios. IEEE Systems Journal 2021, PP, 1 -12.
AMA StyleMohsen Yazdaninejad, Nima Amjady, Nikos D. Hatziargyriou. Nested Bilevel Optimization for DERA Operation Strategy: A Stochastic Multiobjective IGDT Model With Hybrid Endogenous/Exogenous Scenarios. IEEE Systems Journal. 2021; PP (99):1-12.
Chicago/Turabian StyleMohsen Yazdaninejad; Nima Amjady; Nikos D. Hatziargyriou. 2021. "Nested Bilevel Optimization for DERA Operation Strategy: A Stochastic Multiobjective IGDT Model With Hybrid Endogenous/Exogenous Scenarios." IEEE Systems Journal PP, no. 99: 1-12.
Generation expansion planning (GEP) can be a challenging problem when short-circuit (SC) levels and transient stability constraints are considered. We propose a multi-period GEP model in which resistive superconducting fault current limiters (SFCLs) are deployed to limit SC levels, which may be elevated by new generators, and to enhance transient stability at the same time. Through investigating the effect of SFCLs on transient stability and SC levels, efficient linear regions of SFCL deployment are identified and employed to achieve a more cost-effective solution and enhance problem tractability. An effective solution method is also presented by decomposing the main problem into smaller ones. We also propose a linearized AC network framework incorporating bilinear terms based on McCormick envelopes. Relaxation errors are minimized by an exactness loop until the linearized model solution sufficiently matches the original nonlinear model solution. The methodology is illustrated and discussed using the IEEE 118-bus test system.
Mohammad Ghamsari-Yazdel; Masoud Esmaili; Nima Amjady; C. Y. Chung. A Linearized AC Planning Model for Generations and SFCLs Incorporating Transient Stability and Short-Circuit Constraints. IEEE Transactions on Power Systems 2021, PP, 1 -1.
AMA StyleMohammad Ghamsari-Yazdel, Masoud Esmaili, Nima Amjady, C. Y. Chung. A Linearized AC Planning Model for Generations and SFCLs Incorporating Transient Stability and Short-Circuit Constraints. IEEE Transactions on Power Systems. 2021; PP (99):1-1.
Chicago/Turabian StyleMohammad Ghamsari-Yazdel; Masoud Esmaili; Nima Amjady; C. Y. Chung. 2021. "A Linearized AC Planning Model for Generations and SFCLs Incorporating Transient Stability and Short-Circuit Constraints." IEEE Transactions on Power Systems PP, no. 99: 1-1.
In this paper, we propose a risk-based optimal sizing model for Storage as Transmission Alternative (SATA) intended for Transmission Congestion Relief (TCR) services. The storage system is sized from the perspective of the regulator/network operator with the ultimate goal of minimizing the cost of TCR to the ratepayers. The concept of Energy Storage as a Service (ESaaS) is considered when developing the models assuming that SATA’s idle capacity is rented out for a fee to third parties who would participate in energy and ancillary services markets. The fees collected through market participation services are assumed to be credited back to the ratepayers to offset the overall costs of removing network congestion. The presented simulation results provide insights into the financial benefits and risks associated with allowing SATA to share its excess capacity for additional revenues.
Juan Arteaga; Hamidreza Zareipour; Nima Amjady. Energy Storage as a Service: Optimal sizing for Transmission Congestion Relief. Applied Energy 2021, 298, 117095 .
AMA StyleJuan Arteaga, Hamidreza Zareipour, Nima Amjady. Energy Storage as a Service: Optimal sizing for Transmission Congestion Relief. Applied Energy. 2021; 298 ():117095.
Chicago/Turabian StyleJuan Arteaga; Hamidreza Zareipour; Nima Amjady. 2021. "Energy Storage as a Service: Optimal sizing for Transmission Congestion Relief." Applied Energy 298, no. : 117095.
The growing concern over catastrophic weather events, mostly as a direct result of climate changes, has underscored the need for expanding traditional power system contingency analyses to handle the associated risks of extreme power outages. To enable power system operators to make timely decisions when facing extreme events, we explore in this paper the viability of a classifier which uses the machine learning approach based on the Bayes decision theory as a means of predicting power system component outages. However, owing to an excessively imbalance and largely sparse power component outage datasets, the corresponding classifier learning is a challenging problem in the data mining community. In the proposed approach, we apply a resampling method to overcome the class imbalance problem. The proposed classifier provides an effective framework that not only minimizes outage prediction errors for power system components, but also considers the cost of each preventive action according to its implication in extreme events. The outcome of the proposed model can be used for introducing operation-oriented preventive measures that allow the rescheduling of generation resources for maximizing the power system resilience.
Mohammad Shahidehpour; Mostafa Mohammadian; Farrokh Aminifar; Nima Amjady. Data-Driven Classifier for Extreme Outage Prediction Based on Bayes Decision Theory. IEEE Transactions on Power Systems 2021, PP, 1 -1.
AMA StyleMohammad Shahidehpour, Mostafa Mohammadian, Farrokh Aminifar, Nima Amjady. Data-Driven Classifier for Extreme Outage Prediction Based on Bayes Decision Theory. IEEE Transactions on Power Systems. 2021; PP (99):1-1.
Chicago/Turabian StyleMohammad Shahidehpour; Mostafa Mohammadian; Farrokh Aminifar; Nima Amjady. 2021. "Data-Driven Classifier for Extreme Outage Prediction Based on Bayes Decision Theory." IEEE Transactions on Power Systems PP, no. 99: 1-1.
This paper presents a distributionally robust network-constrained unit commitment (DR-NCUC) model considering AC network modeling and uncertainties of demands and renewable productions. The proposed model characterizes uncertain parameters using a data-driven ambiguity set constructed by training samples. The non-convex AC power flow equations are approximated by convex quadratic and McCormick relaxations. Since the proposed min-max-min DR-NCUC problem cannot be solved directly by available solvers, a new decomposition algorithm with proof of convergence is reported in this paper. The master problem of this algorithm is solved using both primal and dual cuts, while the max-min sub-problem is solved using the primal-dual hybrid gradient method, obviating the need for using duality theory. Also, an active set strategy is proposed to enhance the tractability of the decomposition algorithm by ignoring the subset of inactive constraints. The proposed model is applied to a 6-bus test system and the IEEE 118-bus test system under different conditions. These case studies illustrate the performance of the proposed DR-NCUC model to characterize uncertainties and the superiority of the proposed decomposition algorithm over other decomposition approaches using either primal or dual cuts.
Shahab Dehghan; Petros Aristidou; Nima Amjady; Antonio J. Conejo. A Distributionally Robust AC Network-Constrained Unit Commitment. IEEE Transactions on Power Systems 2021, PP, 1 -1.
AMA StyleShahab Dehghan, Petros Aristidou, Nima Amjady, Antonio J. Conejo. A Distributionally Robust AC Network-Constrained Unit Commitment. IEEE Transactions on Power Systems. 2021; PP (99):1-1.
Chicago/Turabian StyleShahab Dehghan; Petros Aristidou; Nima Amjady; Antonio J. Conejo. 2021. "A Distributionally Robust AC Network-Constrained Unit Commitment." IEEE Transactions on Power Systems PP, no. 99: 1-1.
This paper presents a decision‐driven stochastic adaptive‐robust microgrid operation optimization model considering the uncertainties of wind and solar generations, electricity price, and demand as well as the availability uncertainties of microgrid's components. Unlike previous works, this paper utilizes stochastic adaptive‐robust optimization approach to model both continuous and binary uncertainties simultaneously. To do so, adaptive‐robust optimization is used to model the continuous uncertainties, while the binary uncertainties are modelled by means of stochastic programming. An operating dispatchable unit usually exhibits a higher forced outage rate than a de‐committed one. Hence, due to the effect of the optimization decisions on the availability uncertainties, this research work proposes an intrinsic scenario production technique to model these binary uncertainties. In addition, a tri‐level decomposition method is introduced to solve the proposed microgrid operation optimization problem. In this decomposition method, the worst‐case realization of continuous uncertain parameters and unit commitment decisions are determined at each iteration considering the produced scenarios in the previous iteration. Case studies on the IEEE 69‐bus test system exhibit the effectiveness of the proposed decision‐driven stochastic adaptive‐robust model and the proposed solution method.
Mohammad Reza Ebrahimi; Nima Amjady. Contingency‐constrained operation optimization of microgrid with wind and solar generations: A decision‐driven stochastic adaptive‐robust approach. IET Renewable Power Generation 2021, 15, 326 -341.
AMA StyleMohammad Reza Ebrahimi, Nima Amjady. Contingency‐constrained operation optimization of microgrid with wind and solar generations: A decision‐driven stochastic adaptive‐robust approach. IET Renewable Power Generation. 2021; 15 (2):326-341.
Chicago/Turabian StyleMohammad Reza Ebrahimi; Nima Amjady. 2021. "Contingency‐constrained operation optimization of microgrid with wind and solar generations: A decision‐driven stochastic adaptive‐robust approach." IET Renewable Power Generation 15, no. 2: 326-341.
This letter proposes a model for tracking the equilibrium point of the real-time locational marginal price (LMP) based residential demand response program, where elastic demand is modeled as a monotonously decreasing linear function of the LMP. The resulting bi-level model contains both primary and dual variables, making it difficult to solve. Using duality, the dual model is formulated as a convex quadratic problem which is tractable to solve and find the global optimum. Furthermore, the condition for the existence of the equilibrium point is given. Numerical results on the IEEE 30-bus system verifies the effectiveness of the demand response model.
Tao Ding; Ming Qu; Nima Amjady; Fengyu Wang; Rui Bo; Mohammad Shahidehpour. Tracking Equilibrium Point Under Real-Time Price-Based Residential Demand Response. IEEE Transactions on Smart Grid 2020, 12, 2736 -2740.
AMA StyleTao Ding, Ming Qu, Nima Amjady, Fengyu Wang, Rui Bo, Mohammad Shahidehpour. Tracking Equilibrium Point Under Real-Time Price-Based Residential Demand Response. IEEE Transactions on Smart Grid. 2020; 12 (3):2736-2740.
Chicago/Turabian StyleTao Ding; Ming Qu; Nima Amjady; Fengyu Wang; Rui Bo; Mohammad Shahidehpour. 2020. "Tracking Equilibrium Point Under Real-Time Price-Based Residential Demand Response." IEEE Transactions on Smart Grid 12, no. 3: 2736-2740.
Disastrous and hazardous events (eg, natural disasters and cyber‐physical attacks) have significantly increased in power systems, which drastically affect their performance. Different research works have been recently introduced in the literature, aiming at thoroughly evaluating power system resilience against various types of disastrous and hazardous events. In this article, a review of these research works is presented. Moreover, the main differences between the concept of resiliency and the concepts of accessibility, durability, flexibility, hardening, maintainability, reliability, stability, survivability, sustainability, and vulnerability are described. Additionally, various resiliency indices are presented, and different techniques to increase power system resilience against disastrous and hazardous events are reviewed. Furthermore, uncertainty handling approaches used in the literature to analyze power system resiliency are discussed. Some concluding remarks are also presented.
Mehdi Izadi; Seyed Hossein Hosseinian; Shahab Dehghan; Ahmad Fakharian; Nima Amjady. A critical review on definitions , indices, and uncertainty characterization in resiliency‐oriented operation of power systems. International Transactions on Electrical Energy Systems 2020, 31, 1 .
AMA StyleMehdi Izadi, Seyed Hossein Hosseinian, Shahab Dehghan, Ahmad Fakharian, Nima Amjady. A critical review on definitions , indices, and uncertainty characterization in resiliency‐oriented operation of power systems. International Transactions on Electrical Energy Systems. 2020; 31 (1):1.
Chicago/Turabian StyleMehdi Izadi; Seyed Hossein Hosseinian; Shahab Dehghan; Ahmad Fakharian; Nima Amjady. 2020. "A critical review on definitions , indices, and uncertainty characterization in resiliency‐oriented operation of power systems." International Transactions on Electrical Energy Systems 31, no. 1: 1.
To improve electrical energy system resilience under catastrophic events, an efficient intentional controlled islanding (ICI) model is proposed in this article. The proposed remedial action relies on a new mixed integer linear programming (MILP) model which aims at minimizing the overall energy curtailment, power flow disruption, and generation and demand re‐dispatches through a cost‐based objective function. Another innovative characteristic of this model is demand response (DR) inclusion in the proposed ICI. To improve the balance between demand and supply of electricity, DR can be employed as an effective strategy in the ICI problem. In addition, another main original feature of the proposed model is considering energy storage units (ESUs) in each resulted island after the splitting process. To provide enough time for the system operator to re‐dispatch the islands and to improve frequency stability of islands, a charging/discharging scheme is proposed for ESUs during ICI. Moreover, a new time decomposition is proposed to accurately model the fast and slow corrective actions considering their interactions. Using this time decomposition, energy curtailments, considering their period durations, are treated as decision variables in the ICI problem to minimize involuntary load shedding as the most expensive corrective action. The results of scrutinizing the proposed ICI framework on the IEEE 118‐bus test system illustrate its performance. In addition, the results of the proposed ICI approach are compared with the results of other ICI models to illustrate the effectiveness of the new features of the proposed approach.
Mohammad Ghamsari‐Yazdel; Hamid Reza Najafi; Nima Amjady. Incorporating energy storage and demand response into intentional controlled islanding using time decomposition. International Transactions on Electrical Energy Systems 2020, 30, 1 .
AMA StyleMohammad Ghamsari‐Yazdel, Hamid Reza Najafi, Nima Amjady. Incorporating energy storage and demand response into intentional controlled islanding using time decomposition. International Transactions on Electrical Energy Systems. 2020; 30 (10):1.
Chicago/Turabian StyleMohammad Ghamsari‐Yazdel; Hamid Reza Najafi; Nima Amjady. 2020. "Incorporating energy storage and demand response into intentional controlled islanding using time decomposition." International Transactions on Electrical Energy Systems 30, no. 10: 1.
Intentional controlled islanding (ICI) is the last resort to split an endangered power system into smaller islands to prevent blackout. New lines that are planned by transmission expansion planning (TEP) can affect the stability of islands during ICI. In this paper, an ICI-TEP method is proposed to improve the stability of islands by more efficient planning of transmission assets. Moreover, by developing a criterion for the frequency of center of inertia (COI) in each island, the frequency deviations of generators from the COI frequency are minimized to result in more stable islands. The proposed ICI-TEP, incorporating AC network representation, is modeled as mixed-integer linear programming and quadratic convex problems ensuring tractability. A Benders decomposition strategy is also proposed to solve the problem. Results of testing the proposed ICI-TEP method on IEEE 39-bus and 300-bus test systems confirm its effectiveness, compared to conventional TEP, in terms of coping with sever disturbances by creating more stable islands with a lower load shedding.
Masoud Esmaili; Mohammad Ghamsari-Yazdel; Nima Amjady; C. Y. Chung. Convex Model for Controlled Islanding in Transmission Expansion Planning to Improve Frequency Stability. IEEE Transactions on Power Systems 2020, 36, 58 -67.
AMA StyleMasoud Esmaili, Mohammad Ghamsari-Yazdel, Nima Amjady, C. Y. Chung. Convex Model for Controlled Islanding in Transmission Expansion Planning to Improve Frequency Stability. IEEE Transactions on Power Systems. 2020; 36 (1):58-67.
Chicago/Turabian StyleMasoud Esmaili; Mohammad Ghamsari-Yazdel; Nima Amjady; C. Y. Chung. 2020. "Convex Model for Controlled Islanding in Transmission Expansion Planning to Improve Frequency Stability." IEEE Transactions on Power Systems 36, no. 1: 58-67.
We propose a transmission expansion planning model that integrates thyristor-controlled series compensators (TCSCs) to enhance line transmission capacity, and superconducting fault current limiters (SFCLs) to control short-circuit levels. The harmonious interplay between TCSCs and SFCLs results in effective and economically attractive optimal expansion plans. This multi-stage planning model translates into a complex mixed-integer nonlinear programming problem, which is hard to solve. To solve it, we propose a successive linearization technique within a Benders’ decomposition scheme that proves effective in finding optimal solutions and efficient in terms of computational burden. We illustrate the methodology proposed using the IEEE 39-bus system.
Masoud Esmaili; Mohammad Ghamsari-Yazdel; Nima Amjady; C. Y. Chung; Antonio J. Conejo. Transmission Expansion Planning Including TCSCs and SFCLs: A MINLP Approach. IEEE Transactions on Power Systems 2020, 35, 4396 -4407.
AMA StyleMasoud Esmaili, Mohammad Ghamsari-Yazdel, Nima Amjady, C. Y. Chung, Antonio J. Conejo. Transmission Expansion Planning Including TCSCs and SFCLs: A MINLP Approach. IEEE Transactions on Power Systems. 2020; 35 (6):4396-4407.
Chicago/Turabian StyleMasoud Esmaili; Mohammad Ghamsari-Yazdel; Nima Amjady; C. Y. Chung; Antonio J. Conejo. 2020. "Transmission Expansion Planning Including TCSCs and SFCLs: A MINLP Approach." IEEE Transactions on Power Systems 35, no. 6: 4396-4407.
Recent climate changes have created intense natural disasters, such as windstorms, which can cause significant damages to power grids. System resilience is defined as the ability of the system to withstand such high-impact low-probability events. This paper proposes a robust resilient operational schedule for active distribution networks against windstorms. In order to capture dynamic behaviors of these disasters, zonal disaster-specific uncertainty sets associated with the windstorm are proposed. Additionally, the unavailability uncertainties of N-K contingencies as well as the forecast uncertainties of load demand, wind power, and solar power are taken into account. Instead of committing micro-turbines and energy storage systems in the first stage (here-and-now) of the decision-making process, the proposed model considers these commitment decisions in the second stage (wait-and-see) of the decision-making process, which is more consistent with the fast response time of these units. Since the second stage of the proposed model has binary decision variables, recent KKT-based and duality-based methods are not applicable. Therefore, a new solution method based on block coordinate descent (BCD) and line search (LS) techniques is proposed to solve the bi-level problem. Eventually, IEEE 33-bus distribution test system is used to illustrate the effectiveness of the proposed model and solution method.
Moein Esfahani; Nima Amjady; Bahareh Bagheri; Nikos D. Hatziargyriou. Robust Resiliency-Oriented Operation of Active Distribution Networks Considering Windstorms. IEEE Transactions on Power Systems 2020, 35, 3481 -3493.
AMA StyleMoein Esfahani, Nima Amjady, Bahareh Bagheri, Nikos D. Hatziargyriou. Robust Resiliency-Oriented Operation of Active Distribution Networks Considering Windstorms. IEEE Transactions on Power Systems. 2020; 35 (5):3481-3493.
Chicago/Turabian StyleMoein Esfahani; Nima Amjady; Bahareh Bagheri; Nikos D. Hatziargyriou. 2020. "Robust Resiliency-Oriented Operation of Active Distribution Networks Considering Windstorms." IEEE Transactions on Power Systems 35, no. 5: 3481-3493.
Shahab Dehghan; Nima Amjady; Petros Aristidou. A Robust Coordinated Expansion Planning Model For Wind Farm-Integrated Power Systems With Flexibility Sources Using Affine Policies. IEEE Systems Journal 2019, 14, 4110 -4118.
AMA StyleShahab Dehghan, Nima Amjady, Petros Aristidou. A Robust Coordinated Expansion Planning Model For Wind Farm-Integrated Power Systems With Flexibility Sources Using Affine Policies. IEEE Systems Journal. 2019; 14 (3):4110-4118.
Chicago/Turabian StyleShahab Dehghan; Nima Amjady; Petros Aristidou. 2019. "A Robust Coordinated Expansion Planning Model For Wind Farm-Integrated Power Systems With Flexibility Sources Using Affine Policies." IEEE Systems Journal 14, no. 3: 4110-4118.
This paper presents a new robust self-scheduling strategy for virtual power plants (VPPs) considering the uncer-tainty sources of electricity prices, wind generations, and loads. Multi-horizon information-gap decision theory (MH-IGDT) as a non-deterministic and non-probabilistic uncertainty modeling framework is proposed here to specifically model the uncertainty sources considering their various uncertainty horizons. Since each uncertain parameter tends to optimize its uncertainty horizon competitively for a particular value of the uncertainty budget, the proposed MH-IGDT model is formulated as a multi-objective op-timization problem. To solve this multi-objective problem, en-hanced normalized normal constraint (ENNC) method is pre-sented, which can obtain efficient uniformly-distributed Pareto optimal solutions. The proposed ENNC includes augmented nor-malized normal constraint method and lexicographic optimiza-tion technique to enhance the search performance in the objective space. To address the unsolved issue of being risk-averse or risk-seeker for a VPP in the market, a bi-directional decision-making approach is presented. This decision maker comprises an ex-ante performance evaluation method and a forward-backward dy-namic programming approach to hourly find the best Pareto so-lution within the generated risk-averse and risk-seeker Pareto frontiers. Simulation results of the proposed self-scheduling strat-egy are presented for a VPP including dispatchable/non-dispatch-able units, storages, and loads.
Mohsen Yazdaninejad; Nima Amjady; Shahab Dehghan. VPP Self-Scheduling Strategy Using Multi-Horizon IGDT, Enhanced Normalized Normal Constraint, and Bi-Directional Decision-Making Approach. IEEE Transactions on Smart Grid 2019, 11, 3632 -3645.
AMA StyleMohsen Yazdaninejad, Nima Amjady, Shahab Dehghan. VPP Self-Scheduling Strategy Using Multi-Horizon IGDT, Enhanced Normalized Normal Constraint, and Bi-Directional Decision-Making Approach. IEEE Transactions on Smart Grid. 2019; 11 (4):3632-3645.
Chicago/Turabian StyleMohsen Yazdaninejad; Nima Amjady; Shahab Dehghan. 2019. "VPP Self-Scheduling Strategy Using Multi-Horizon IGDT, Enhanced Normalized Normal Constraint, and Bi-Directional Decision-Making Approach." IEEE Transactions on Smart Grid 11, no. 4: 3632-3645.
This paper presents a new adaptive robust operation optimization approach for energy hub (EH) to identify the optimal decisions on purchased energy carriers, upstream network interactions, and storing/conversion of the energy resources considering uncertainties. In this regard, a linearized framework for EH operation is first introduced. The proposed model is used to develop an EH including electrical energy, natural gas, and direct heat as inputs and electricity and heat demands as outputs. The electrical input energy is provided considering both purchased energy from upstream market and a photovoltaic (PV) generation, operated by the EH operator (EHO). The proposed approach characterizes the uncertain nature of loads, energy prices, and PV generations through polyhedral uncertainty sets, while the robustness of the proposed model can be controlled using the budget of uncertainty. The proposed adaptive robust model is formulated as a min‐max‐min optimization problem, which cannot be solved directly through an off‐the‐shelf optimization package. Thus, a new method, consisting decomposition + primal cutting plane + duality theory + exact linearization + post‐optimization analysis, is introduced to determine the EH optimal solution. The performance of the proposed approach is evaluated through a comprehensive case study.
Mehrdad Aghamohamadi; Nima Amjady; Ahmad Attarha. A linearized energy hub operation model at the presence of uncertainties: An adaptive robust solution approach. International Transactions on Electrical Energy Systems 2019, 30, 1 .
AMA StyleMehrdad Aghamohamadi, Nima Amjady, Ahmad Attarha. A linearized energy hub operation model at the presence of uncertainties: An adaptive robust solution approach. International Transactions on Electrical Energy Systems. 2019; 30 (3):1.
Chicago/Turabian StyleMehrdad Aghamohamadi; Nima Amjady; Ahmad Attarha. 2019. "A linearized energy hub operation model at the presence of uncertainties: An adaptive robust solution approach." International Transactions on Electrical Energy Systems 30, no. 3: 1.
Recently, microgrid (MG) power flow (PF) studies have gained a lot of attention due to the emergence of autonomous MGs which feature distributed generations (DGs). There are some inherent limitations in the islanded operation mode of MGs which cannot be addressed by conventional PF methods. In this regard, recent studies have proposed some updates to the conventional approaches by inclusion of network frequency as a variable in their modeling and omission of the slack bus from the grid. These considerations specifically in the Newton-Raphson (NR) method change the Jacobean matrix (JM) formulations. This paper concentrates on improving the previous NR methods for MGs which include droop controlled DGs. For this purpose, the partial derivatives of both calculated and scheduled powers are considered in the Taylor series expansion of bus power injections. Thus, the convergence and accuracy of the PF method are enhanced by adding these derivatives in modeling of generations, loads and losses. Moreover, these extended PF equations are decoupled by reformulating the JM based on the consideration that the lines in MGs are mostly resistive, which results in simplified JM calculations and improved convergence speed. The effectiveness of the proposed decoupled extended NR (DENR) method for MG PF analysis is illustrated in several case studies including 6-bus and 38-bus networks. Moreover, two convergence enhancement methods are also incorporated into the proposed approaches and their merits are investigated.
Amir Ali Nazari; Reza Keypour; M.H. Beiranvand; Nima Amjady. A decoupled extended power flow analysis based on Newton-Raphson method for islanded microgrids. International Journal of Electrical Power & Energy Systems 2019, 117, 105705 .
AMA StyleAmir Ali Nazari, Reza Keypour, M.H. Beiranvand, Nima Amjady. A decoupled extended power flow analysis based on Newton-Raphson method for islanded microgrids. International Journal of Electrical Power & Energy Systems. 2019; 117 ():105705.
Chicago/Turabian StyleAmir Ali Nazari; Reza Keypour; M.H. Beiranvand; Nima Amjady. 2019. "A decoupled extended power flow analysis based on Newton-Raphson method for islanded microgrids." International Journal of Electrical Power & Energy Systems 117, no. : 105705.
This paper presents a new AC optimal power flow (AC OPF) model for sub-transmission networks. This model, which consists of sub-transmission and distribution bus-bar switching actions, can avoid undesirable over-current (OC) status and subsequent actions of OC relays. The proposed AC OPF optimizes the bus-bar switching actions along with optimizing sub-transmission control actions. Also, to consider the impact of OC relays’ actions in the proposed AC OPF, the cost of load shedding caused by these relay actions is included in the objective function and is minimized along with the sub-transmission operation cost. The bus-bar switching actions are modeled using binary decision variables. Therefore, the proposed AC OPF model is formulated as a Mixed Integer Non-linear Programming (MINLP) optimization problem. The effectiveness of the proposed model is illustrated on a real-world sub-transmission network of Iran’s power system. Scientia Iranica (SCI)
Mohammad Ali Tavakkoli; Nima Amjady. Incorporating Bus-Bar Switching Actions into AC OPF to Avoid Over-Current Status. Scientia Iranica 2019, 1 .
AMA StyleMohammad Ali Tavakkoli, Nima Amjady. Incorporating Bus-Bar Switching Actions into AC OPF to Avoid Over-Current Status. Scientia Iranica. 2019; ():1.
Chicago/Turabian StyleMohammad Ali Tavakkoli; Nima Amjady. 2019. "Incorporating Bus-Bar Switching Actions into AC OPF to Avoid Over-Current Status." Scientia Iranica , no. : 1.
Shima Rahmani; Nima Amjady. Optimal operation strategy for multi-carrier energy systems including various energy converters by multi-objective information gap decision theory and enhanced directed search domain method. Energy Conversion and Management 2019, 198, 1 .
AMA StyleShima Rahmani, Nima Amjady. Optimal operation strategy for multi-carrier energy systems including various energy converters by multi-objective information gap decision theory and enhanced directed search domain method. Energy Conversion and Management. 2019; 198 ():1.
Chicago/Turabian StyleShima Rahmani; Nima Amjady. 2019. "Optimal operation strategy for multi-carrier energy systems including various energy converters by multi-objective information gap decision theory and enhanced directed search domain method." Energy Conversion and Management 198, no. : 1.