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5th IEEE Global Power, Energy and Communication Conference (GPECOM)

作者： Shahinzadeh, Hossein Moradi, Jalal Yaici, Wahiba Roscia, Mariacristina Ebrahimi, Farshad Nafisi, Hamed Amirkabir Univ Technol Dept Elect Engn Tehran Iran Amirkabir Univ Technol Iran Grid Secure Operat Res Inst Tehran Iran Nat Resources Canada CanmetENERGY Res Ctr Ottawa ON Canada Univ Bergamo DISA Dipartimento Ingn Sci Applicate Bergamo Italy Univ Houston Dept Elect & Comp Engn Houston TX 77004 USA

ISBN: (纸本)9798350301984

A novel paradigm for home energy management in a renewable energy-based residential energy hub using probabilistic optimization methods is presented in this work. Various converters and energy storage facilities, along with combined heat and power (CHP) units, plug-in hybrid electric vehicles, heat storage units, solar panels, and controllable and uncontrollable appliances are counted as a component in the energy hub. Consumer energy cost is considered as the goal of optimizing home energy management and operating restrictions of different energy hub components are considered optimization terms. In this paper, the probabilistic method of two-point estimation is employed to model the uncertainty of solar panels. Hence, a hybrid optimization algorithm including the gray wolf optimization algorithm and the shark smell optimization (SSO) algorithm has been used to solve the desired objective function under different terms and the prevailing constraints. The results show that by applying the proposed method and considering the proposed strategy in energy management, energy efficiency can be increased and the operating costs of the energy hub can be significantly reduced.

关键词： Energy management and efficiency Energy hub Energy Storage Solar panel Electric vehicle Uncertainty CHP two-point estimation method

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Stochastic Optimization of Electromagnetic Inertial Mass Dampers in Nonlinear Hybrid Base Isolation Systems Under Seismic Excitations

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INTERNATIONAL JOURNAL OF STRUCTURAL STABILITY AND DYNAMICS 2024年第21期24卷

作者： Lei, Ying Yang, Xiongjun Xiamen Univ Dept Civil Engn Siming Rd Xiamen 361000 Peoples R China

Recently developed inerter-based dampers have been installed at the base layer to reduce base displacement and simultaneously improve the superstructure's performance. However, in the existing research on optimizing damper parameters, the nonlinear property of base isolation is simplified and stochastic linearization technique is introduced to approximate such nonlinearity, which would inevitably introduce errors. In this paper, an improved method is proposed for stochastic optimization of electromagnetic inertial mass dampers (EIMD) in nonlinear hybrid isolation systems subject to seismic excitations. First, a stochastic seismic excitation is represented by one elementary random variable adopting the dimension-reduction spectral representation method. Then, statistical moments of nonlinear base-isolated structural responses are estimated using two-point estimation method (2PEM). Finally, the EIMD optimal parameters are obtained via the modified directional bat algorithm (MDBA) recently proposed by the authors through minimizing base layer response moments. This proposed improved method could fully consider the base isolation nonlinearity compared with the previous stochastic linearization technique. Moreover, the proposed stochastic optimization of the EIMD only requires two dynamic analyses to achieve its efficiency. A seven-story base-isolated frame building equipped with an EIMD is investigated in the numerical simulation, and results indicate that EIMD optimized by this proposed method obviously outperforms the results by the stochastic linearization technique and the conventional viscous damper (VD) in the base layer displacement reduction.

关键词： Electromagnetic inertial mass damper (EIMD) nonlinear base isolation parameter optimization dimension-reduction spectral representation two-point estimation method

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Bi-layer energy optimal scheduling of regional integrated energy system considering variable correlations

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INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS 2023年第1期148卷

作者： Zhang, Jing Kong, Dezheng He, Yu Fu, Xiaofan Zhao, Xiangyu Yao, Gang Teng, Fei Qin, Yuan Guizhou Univ Sch Elect Engn Guizhou Peoples R China Zhejiang Power Grid Co State Grid Zhejiang Mkt Serv Ctr Meterol Ctr Hangzhou Zhejiang Peoples R China Guizhou Power Grid Co Dispatching & Control Ctr Guizhou Peoples R China

As the capacity of new energy sources connected to the regional integrated energy system increases, it is necessary to consider (i) the energy imbalance caused by multiple uncertainty factors and (ii) the correlation between the power output of those uncertainty sources in the overall system. This paper proposes a bi-level optimal energy scheduling strategy, which combines information gap decision theory (IGDT) with model pre-dictive control (MPC). In order to reduce the large deviation between the day-ahead scheduling plan and the actual scheduling caused by prediction errors of source and load, the IGDT is adopted in the upper layer strategy to model the uncertain factors in the day-ahead scheduling plan. To support IGDT in dealing with multiple uncertainties, the two-point estimation method and Cornish-Fisher series expansion is used to transform the uncertainties of the sources and the loads into uncertainties of power unbalance. Moreover, the Nataf trans -formation and singular value decomposition (SVD) technique are introduced, so that the two-point estimation and Cornish-Fisher method could handle correlative variables, thereby the solving efficiency of the IGDT model can be improved much more. The MPC rolling optimization is adopted within a day to correct the day-ahead scheduling deviation and compensate for the shortcomings of IGDT open-loop control. Finally, the proposed method is applied to a numerical example to verify its effectiveness.

关键词： Regional integrated energy system Model predictive control Information gap decision theory two-point estimation method Cornish-Fisher series expansion Nataf transformation Singular Value Decomposition

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Three-based level model to determine optimal scheduling of the MG integrated operation using Benders decomposition

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IET GENERATION TRANSMISSION & DISTRIBUTION 2019年第20期13卷 4712-4723页

作者： Kouhian, Farhad Zangeneh, Ali Marti, Jose Ramon Shahid Rajaee Teacher Training Univ Elect Engn Dept Tehran Iran Univ British Columbia Dept Elect & Comp Engn Vancouver BC V6T 1Z4 Canada

In this study, an optimal scheduling model is proposed to perform energy management in a microgrid (MG) including distributed energy resources in both grid-connected and islanded modes. To this end, a tri-level optimization model has been presented, in which Benders method decomposes the original problem into the main problem (the first level), sub-problem (SP) (the second level) and optimal SP (the third level). The first and second levels model the MG operation in grid-connected and islanded modes, respectively. Finally, the third level directs the obtained feasible solution of the second level to an optimal solution in the islanded mode. In the proposed model, the effect of an adjacent MG is also considered, and a call-option contract is used to model the transaction power between networked MG. While it is assumed that they are connected to each other, they only exchange power in the islanded mode to prevent the arbitrage state. The aim of the proposed model is to present a flexible and integrated operation of the MG, which has the ability to work in both grid connected and island modes. Uncertainties of the problem are modelled using the two-point estimation method (2 m+1).

关键词： integer programming energy management systems pricing distributed power generation power generation economics power markets power distribution economics power generation scheduling renewable energy sources island modes MG integrated operation Benders decomposition optimal scheduling model energy management distributed energy resources tri-level optimisation model Benders method optimal solution islanded mode integer programming method linear programming method flexible operation microgrid grid-connected mode transaction power exchange power arbitrage state integrated operation generation cost purchasing energy power generation renewable resources electric energy price two-point estimation method

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Optimal Micro-PMU Placement Using Mutual Information Theory in Distribution Networks

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ENERGIES 2018年第7期11卷 1917页

作者： Wu, Zhi Du, Xiao Gu, Wei Ling, Ping Liu, Jinsong Fang, Chen Southeast Univ Sch Elect Engn Nanjing 210096 Jiangsu Peoples R China State Grid Shanghai Elect Power Co Elect Power Res Inst Shanghai 200090 Peoples R China

Micro-phasor measurement unit (mu PMU) is under fast development and becoming more and more important for application in future distribution networks. It is unrealistic and unaffordable to place all buses with mu PMUs because of the high costs, leading to the necessity of determining optimal placement with minimal numbers of mu PMUs in the distribution system. An optimal mu PMU placement (OPP) based on the information entropy evaluation and node selection strategy (IENS) using greedy algorithm is presented in this paper. The uncertainties of distributed generations (DGs) and pseudo measurements are taken into consideration, and the two-point estimation method (2PEM) is utilized for solving stochastic state estimation problems. The set of buses selected by improved IENS, which can minimize the uncertainties of network and obtain system observability is considered as the optimal deployment of mu PMUs. The proposed method utilizes the measurements of smart meters and pseudo measurements of load powers in the distribution systems to reduce the number of mu PMUs and enhance the observability of the network. The results of the simulations prove the effectiveness of the proposed algorithm with the comparison of traditional topological methods for the OPP problem. The improved IENS method can obtain the optimal complete and incomplete mu PMU placement in the distribution systems.

关键词： micro-phasor measurement unit mutual information theory stochastic state estimation two-point estimation method

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Simplified probabilistic voltage stability evaluation considering variable renewable distributed generation in distribution systems

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IET GENERATION TRANSMISSION & DISTRIBUTION 2015年第12期9卷 1464-1473页

作者： Liu, Ke-yan Sheng, Wanxing Hu, Lijuan Liu, Yongmei Meng, Xiaoli Jia, Dongli China Elect Power Res Inst Power Distribut Res Dept Beijing 100192 Peoples R China

This study investigates the evaluation of static voltage stability using a two-point estimation method (2PEM) and continuation power flow (CPF) in distribution systems. The stochastic distribution generation (DG) units have been considered with their respective probability density function (PDF). The proposed static voltage stability evaluation method first chooses several sample points to replace the PDFs using 2PEM. Then, based on each sample point, the critical static voltage stability value is calculated by CPF. On the basis of the critical values corresponding to all selected sample points, Cornish-Fisher series are used to evaluate the PDF of the critical static voltage stability, and then the static voltage stability state can be obtained. The proposed method has been tested on IEEE 33-bus, PG&E 69-bus and a real case with two stochastic DG units. Comparisons have been made with the Monte Carlo simulation and the first-order second-moment method. The results show that the proposed method has better efficiency and accuracy.

关键词： power system stability distributed power generation stochastic processes load flow simplified probabilistic voltage stability evaluation variable renewable distributed generation distribution systems two-point estimation method 2PEM continuation power flow CPF stochastic distribution generation DG units probability density function PDF Cornish-Fisher series IEEE 33-bus PG& E 69-bus Monte Carlo simulation first-order second-moment method

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Probabilistic framework for risk analysis of power system small-signal stability

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PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART O-JOURNAL OF RISK AND RELIABILITY 2012年第O1期226卷 118-133页

作者： Rueda, J. L. Erlich, I. Univ Duisburg Essen Inst Elect Power Syst D-47057 Duisburg Germany

In power system planning and operation studies, conventional methodologies are still largely used for small-signal stability analysis under the deterministic framework. Nevertheless, no information concerning the small-signal instability risk can be derived and the obtained results are too conservative since deterministic approaches are unable to properly reflect the existing uncertainties in real power systems. Hence, there is a need to develop new approaches which can handle a wider range of operating conditions and consequently capture all of the possible scenarios that may lead to insecure conditions. The present paper explores relevant issues associated with the conditions for application of the Monte Carlo method (MC) in probabilistic eigenanalysis (PE), namely the selection of: a suitable sampling technique for MC-based PE;and a stopping rule which is sufficient to achieve some specified confidence level. The proposed MC-based PE approach provides probabilistic indexes for small-signal stability assessment and enhancement. Several power systems of different sizes and with different small-signal stability performances are used to investigate the feasibility of the probabilistic indexes as well as to compare MC-based PE with an analytical probabilistic approach based on the two-point estimation method (TPE).

关键词： small-signal stability Monte Carlo method eigenanalysis probabilistic indexes controllability observability two-point estimation method

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