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1. Adaptive Control for Energy Exchange with Probabilistic Interval Predictors in Isolated Microgrids

   https://doi.org/10.3390/en14020375  

   Cheng, Jiayu ; Duan, Dongliang ; Cheng, Xiang ; Yang, Liuqing ; Cui, Shuguang ( January 2021 , Energies)

   null (Ed.)

   Stability and reliability are of the most important concern for isolated microgrid systems that have no support from the utility grid. Interval predictions are often applied to ensure the system stability of isolated microgrids as they cover more uncertainties and robust control can be achieved based on more sufficient information. In this paper, we propose a probabilistic microgrid energy exchange method based on the Model Predictive Control (MPC) approach to make better use of the prediction intervals so that the system stability and cost efficiency of isolated microgrids are improved simultaneously. Appropriate scenarios are selected from the predictions according to the evaluation of future trends and system capacity. In the meantime, a two-stage adaptive reserve strategy is adopted to further utilize the potential of interval predictions and maintain the system security adaptively. Reserves are determined at the optimization stage to prepare some extra capacity for the fluctuations in the renewable generation and load demand at the operation stage based on the aggressive and conservative level of the system, which is automatically updated at each step. The optimal dispatch problem is finally formulated using the mixed-integer linear programming model and the MPC is formulated as an optimization problem with a discount factor introduced to adjust the weights. Case studies show that the proposed method could effectively guarantee the stability of the system and improve economic performance. 

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2. Frequency regulation for microgrid using genetic algorithm and particle swarm optimization tuned STATCOM

   https://doi.org/10.1002/cta.3319  

   Saxena, Nitin Kumar ; Gao, Wenzhong D. ; Kumar, Ashwani ; Mekhilef, Saad ; Gupta, Varun ( May 2022 , International Journal of Circuit Theory and Applications)

   This paper presents the genetic algorithm (GA) and particle swarm optimization (PSO) based frequency regulation for a wind‐based microgrid (MG) using reactive power balance loop. MG, operating from squirrel cage induction generator (SCIG), is employed for exporting the electrical power from wind turbines, and it needs reactive power which may be imported from the grid. Additional reactive power is also required from the grid for the load, directly coupled with such a distributed generator (DG) plant. However, guidelines issued by electric authorities encourage MGs to arrange their own reactive power because such reactive power procurement is defined as a local area problem for power system studies. Despite the higher cost of compensation, static synchronous compensator (STATCOM) is a fast‐acting FACTs device for attending to these reactive power mismatches. Reactive power control can be achieved by controlling reactive current through the STATCOM. This can be achieved with modification in current controller scheme of STATCOM. STATCOM current controller is designed with reactive power load balance for the proposed microgrid in this paper. Further, gain values of the PI controller, required in the STATCOM model, are selected first with classical methods. In this classical method, iterative procedures which are based on integral square error (ISE), integral absolute error (IAE), and integral square of time error (ISTE) criteria are developed using MATLAB programs. System performances are further investigated with GA and PSO based control techniques and their acceptability over classical methods is diagnosed. Results in terms of converter frequency deviation show how the frequency remains under the operating boundaries as allowed by IEEE standards 1159:1995 and 1250:2011 for integrating renewable‐based microgrid with grid. Real and reactive power management and load current total harmonic distortions verify the STATCOM performance in MG. The results are further validated with the help of recent papers in which frequency regulation is investigated for almost similar power system models. The compendium for this work is as following: (i) modelling of wind generator‐based microgrid using MATLAB simulink library, (ii) designing of STATCOM current controller with PI controller, (iii) gain constants estimation using classical, GA and PSO algorithm through a developed m codes and their interfacing with proposed simulink model, (v) dynamic frequency responses for proposed grid connected microgrid during starting and load perturbations, (vi) verification of system performance with the help of obtained real and reactive power management between STATCOM and grid, and (vii) validation of results with available literature.

    

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3. Trust-based User Interface Design for Islanded Alternating Current Microgrids

   https://doi.org/10.1109/GreenTech48523.2021.00079  

   Matlashova, Yuliya ; Oishi, Meeko ; Bidram, Ali ( April 2021 , 2021 IEEE Green Technologies Conference (GreenTech))

   null (Ed.)

   Microgrid systems can provide extensive information using their measurement units to the operators. As microgrid systems become more pervasive, there will be a need to adjust the information an operator requires to provide an optimized user-interface. In this paper, a combinatorial optimization strategy is used to provide an optimal user-interface for the microgrid operator that selects information for display depending on the operator's trust level in the system, and the assigned task. We employ a method based on sensor placement by capturing elements of the interface as different sensors, that find an optimal set of sensors via combinatorial optimization. However, the typical inverter-based microgrid model poses challenges for the combinatorial optimization due to its poor conditioning. To combat the poor conditioning, we decompose the model into its slow and fast dynamics, and focus solely on the slow dynamics, which are more well conditioned. We presume the operator is tasked with monitoring phase angle and active and reactive power control of inverter-based distributed generators. We synthesize user-interface for each of these tasks under a wide range of trust levels, ranging from full trust to no trust. We found that, as expected, more information must be included in the interface when the operator has low trust. Further, this approach exploits the dynamics of the underlying microgrid to minimize information content (to avoid overwhelming the operator). The effectiveness of proposed approach is verified by modeling an inverter-based microgrid in Matlab. 

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4. A Comparative Study of Formulations and Algorithms for Reliability-Based Co-Design Problems

   https://doi.org/10.1115/DETC2019-98307  

   Cui, Tonghui ; Allison, James T. ; Wang, Pingfeng ( August 2019 , American Society of Mechanical Engineers)

   Co-design, or integrated physical and control system design, has been demonstrated successfully for several engineering system design optimization applications, primarily in a deterministic manner. An opportunity exists to study non-deterministic co-design strategies, including incorporation of uncertainty-induced failures, into an integrated co-design framework. Reliability-based design optimization (RBDO) is one such method that can be used to increase the likelihood of having a feasible design that satisfies all reliability constraints. While significant recent advancements have been made in co-design and RBDO separately, limited work has been done where reliability-based dynamic system design and control design optimization are considered jointly. In this paper, the co-design problem is integrated with the RBDO framework to yield a system-optimal design and the corresponding control trajectory, which satisfy all reliability constraints in the presence of parameter variations. Different problem formulations and RBDO algorithms are compared through numerical examples. The design of a horizontal-axis wind turbine (HAWT) supported by a lattice tower (with parameter uncertainties) is presented to demonstrate the applicability of the proposed method. 

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5. Partitioning Analysis in Temporal Decomposition for Security-Constrained Economic Dispatch

   https://doi.org/10.1109/TPEC48276.2020.9042504  

   Safdarian, Farnaz ; Mohammadi, Ali ; Kargarian, Amin ; Falahati, Bamdad ( March 2020 , 2020 IEEE Texas Power and Energy Conference (TPEC))

   Distributed optimization algorithms are proposed to, potentially, reduce the computational time of large-scale optimization problems, such as security-constrained economic dispatch (SCED). While various geographical decomposition strategies have been presented in the literature, we proposed a temporal decomposition strategy to divide the SCED problem over the considered scheduling horizon. The proposed algorithm breaks SCED over the scheduling time and takes advantage of parallel computing using multi-core machines. In this paper, we investigate how to partition the overall time horizon. We study the effect of the number of partitions (i.e., SCED subproblems) on the overall performance of the distributed coordination algorithm and the effect of partitioning time interval on the optimal solution. In addition, the impact of system loading condition and ramp limits of the generating units on the number of iterations and solution time are analyzed. The results show that by increasing the number of subproblems, the computational burden of each subproblem is reduced, but more shared variables and constraints need to be modeled between the subproblems. This can result in increasing the total number of iterations and consequently the solution time. Moreover, since the load behavior affects the active ramping between the subproblems, the breaking hour determines the difference between shared variables. Hence, the optimal number of subproblems is problem dependent. A 3-bus and the IEEE 118-bus system are selected to analyze the effect of the number of partitions. 

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