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Reliability-based model for generation and transmission expansion planning

IET GENERATION TRANSMISSION & DISTRIBUTION 2017年第2期11卷 504-511页

作者： Ahmadi, Abdollah Mavalizadeh, Hani Zobaa, Ahmed F. Shayanfar, Heidar Ali Univ New South Wales Sch Elect Engn & Telecommun Sydney NSW Australia Iran Univ Sci & Technol Sch Elect Engn Ctr Excellence Power Syst Automat & Operat Tehran Iran Brunel Univ London Coll Engn Design & Phys Sci Uxbridge Middx England

This study presents a mixed integer linear multi-objective model based on information gap decision theory, which is used to solve coordinated multiyear generation and transmission expansion planning problems. The model maximises the robustness of each uncertain parameter while a maximum allowable budget range is set. Fuel transportation price is considered. The results provide a numerical tool for system planner to help him adjust the appropriate level of robustness for each uncertain parameter of the problem. Extra limits on security, gaseous emission and fuel availability are considered. A multi-objective method called the.-constraint method is used here to maximise the robust region of load and investment costs simultaneously. The model is implemented on a six-bus Garver test system and 24-bus IEEE test system. The numerical results show the good performance of the model.

关键词： power transmission planning power transmission reliability integer programming linear programming decision theory power generation planning power generation reliability reliability-based model transmission expansion planning mixed integer linear multiobjective model information gap decision theory coordinated multiyear generation fuel transportation price gaseous emission fuel availability multiobjective method ε-constraint method investment costs six-bus Garver test system 24-bus IEEE test system

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Zero bus load flow method for the integration of renewable DGs by mixed-discrete particle swarm optimisation-based fuzzy max-min approach

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IET RENEWABLE POWER GENERATION 2020年第19期14卷 4029-4042页

作者： Barik, Soumyabrata Das, Debapriya Bansal, Ramesh C. BITS Pilani Elect & Elect Engn Dept Pilani Goa India Indian Inst Technol Kharagpur Elect Engn Dept Kharagpur W Bengal India Univ Sharjah Elect Engn Dept Sharjah U Arab Emirates

This study proposes an approach to determine the optimal placement and sizing of renewable distributed generations (DGs) and shunt capacitor in the distribution network (DN) with a pre-defined energy contract strategy with the main grid by using fuzzy integrated mixed-discrete particle swarm optimisation (MDPSO) based method. The proposed pre-defined contract strategies are implemented in this study using the modified Newton-Raphson (NR) load flow method with the concept of the PQV delta-zero bus. The modifications in the Jacobian matrix in the NR load flow method is developed. MDPSO method is adopted to take care of both the continuous and the discrete variables, to determine the proper locations and the sizes of renewable DGs and shunt capacitor by reducing the active power loss, improving the voltage profile, and reducing the annual costs of the DGs. The multi-objective optimisation is solved by using the fuzzy max-min-based technique. The proposed method of DG placement is tested on 69 bus DN for three different scenarios. The results obtained from the proposed multi-objective method are also compared with the weighted sum approach for different combinations.

关键词： Jacobian matrices minimax techniques distribution networks distributed power generation load flow Newton-Raphson method particle swarm optimisation fuzzy set theory mixed-discrete particle swarm optimisation based method pre-defined contract strategies modified Newton-Raphson load flow method $PQV\delta -$PQV delta-zero bus NR load flow method MDPSO method discrete variables renewable DGs capacitor multiobjective optimisation fuzzy max-min-based technique multiobjective method weighted sum approach zero bus load flow method mixed-discrete particle swarm optimisation-based fuzzy max-min approach optimal placement renewable distributed generations distribution network pre-defined energy contract strategy

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Probabilistic multi-objective state estimation-based PMU placement in the presence of bad data and missing measurements

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IET GENERATION TRANSMISSION & DISTRIBUTION 2020年第15期14卷 3042-3051页

作者： Zargar, Saman Farhang Farsangi, Malihe Maghfoori Zare, Mohsen Shahid Bahonar Univ Kerman Dept Elect Engn Kerman Iran Jahrom Univ Dept Elect Engn Jahrom Iran

This study proposes a multi-objective probabilistic coordinated method for state estimation (SE) in a power system by optimal placement of phasor measurement units (PMUs) in the presence of bad data and missing measurements. For this purpose, using a three-stage SE approach and a linear estimator, the conventional and PMU measurements are used simultaneously for SE and then, the obtained estimates are integrated through estimation fusion theory. Subsequently, the proposed optimal PMU placement (OPP) method finds out the minimum number and the optimal location of PMUs required to achieve the desired accuracy of the power system SE. Furthermore, a 2m+1 point estimated method is used to model the uncertainty of measurements to increase the adaptation with realistic operation condition. A modified Jaya algorithm is formulated to minimises four objective functions in an effective multi-objective method where the network constraints are satisfied. The standard IEEE 30- and 57-bus systems are used to evaluate the efficiency of the proposed method. To investigate different aspects of the proposed formulation, different cases are proposed and the results obtained are compared. The obtained results show that the determined OPP by the proposed method can eliminate the effect of conventional bad measuring data and missing measurement devices.

关键词： phasor measurement power system measurement phase measurement state estimation probability power system state estimation optimisation sensor fusion probabilistic multiobjective state estimation bad data missing measurements multiobjective probabilistic coordinated method optimal placement phasor measurement units three-stage SE approach linear estimator conventional measurements PMU measurements estimation fusion theory optimal PMU placement method optimal location power system SE 2m+1 point estimated method minimises four objective functions multiobjective method 57-bus test systems conventional bad measuring data missing measurement devices reduced estimation errors conventional PMU placement problems size 2 0 m

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Multi-objective approach for distribution network reconfiguration with optimal DG power factor using NSPSO

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IET GENERATION TRANSMISSION & DISTRIBUTION 2016年第12期10卷 2842-2851页

作者： Tuladhar, Subas Ratna Singh, Jai Govind Ongsakul, Weerakorn Asian Inst Technol Sch Environm Resource & Dev Energy Field Study Pathum Thani 12120 Thailand

In this study, a multi objective method for optimal network reconfiguration as well as reactive power dispatches of distributed generations (DGs) has been proposed to improve the network performances by using non-dominated sorting particle swarm optimisation. The various network performances in terms of multi objective function include minimisation of system power loss, voltage deviation and energy wastage from solar and wind generation system. The effectiveness of the proposed method has been tested on the IEEE 33-bus radial distribution system for different combinations of network reconfiguration and reactive power output of DGs or its varying power factor. The obtained results also compared and indicated that better network performances achieved with both network reconfiguration and power factor optimisation over other cases. In addition, this strategy also results in lesser energy wastage from distributed renewable generation over without network reconfiguration option;hence, this approach is also suitable for saving and utilising maximum capacity of available renewable sources.

关键词： power factor distribution networks distributed power generation wind power plants solar power stations particle swarm optimisation multiobjective approach distribution network reconfiguration optimal DG power factor NSPSO multiobjective method optimal network reconfiguration reactive power dispatches distributed generations nondominated sorting particle swarm optimisation multiobjective function system power loss wind generation system solar generation system energy wastage IEEE 33-bus radial distribution system network reconfiguration reactive power output varying power factor power factor optimisation distributed renewable generation renewable sources

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Multi-objective optimisation method for coordinating battery storage systems, photovoltaic inverters and tap changers

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IET RENEWABLE POWER GENERATION 2020年第3期14卷 475-483页

作者： Hashemipour, N. Aghaei, Jamshid Lotfi, Mohamed Niknam, Taher Askarpour, Mohammad Shafie-khah, Miadreza Catalao, Joao P. S. Shiraz Univ Technol Dept Elect & Elect Engn Shiraz Iran Univ Porto Fac Engn P-4200465 Porto Portugal INESC TEC P-4200465 Porto Portugal Univ Vaasa Sch Technol & Innovat Vaasa 65200 Finland

The many well-established advantages of distributed generation (DG) make their usage in active distribution networks prevalent. However, uncontrolled operation of DG units can negatively interfere with the performance of other equipment, such as tap-changers, in addition to resulting in sub-optimal usage of their potential. Thus, adequate scheduling/control of DG units is critical for operators of the distribution system to avoid those adverse effects. A linearised model of a multi-objective method for coordinating the operation of photovoltaics, battery storage systems, and tap-changers is proposed. Three objective functions are defined for simultaneously enhancing voltage profile, minimising power losses, and reducing peak load power. The formulated multi-objective problem is solved by means of the epsilon-constraint technique. A novel decision-making methodology is offered to find the Pareto optimality and select the preferred solution. To assess to proposed model's performance, it is tested using 33-bus IEEE test system. Consequently, tap-changers suffer lessened stress, the batteries state-of-charge is kept within adequate limits, and the DG units operation is at higher efficiency. The obtained results verify the effectiveness of this approach.

关键词： optimisation distributed power generation distribution networks Pareto optimisation decision making multiobjective optimisation method battery storage systems photovoltaic inverters tap changers well-established advantages distributed generation active distribution networks uncontrolled operation tap-changers sub-optimal usage distribution system multiobjective method objective functions peak load power formulated multiobjective problem 33-bus IEEE test system batteries state-of-charge DG units operation

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Classification of Gene Expression Data Using multiobjective Differential Evolution

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ENERGIES 2016年第12期9卷 1061页

作者： Ma, Shijing Li, Xiangtao Wang, Yunhe Northeast Normal Univ Sch Comp Sci & Informat Technol Changchun 130117 Peoples R China

Gene expression data are usually redundant, and only a subset of them presents distinct profiles for different classes of samples. Thus, selecting high discriminative genes from gene expression data has become increasingly interesting in bioinformatics. In this paper, a multiobjective binary differential evolution method (MOBDE) is proposed to select a small subset of informative genes relevant to the classification. In the proposed method, firstly, the Fisher-Markov selector is used to choose top features of gene expression data. Secondly, to make differential evolution suitable for the binary problem, a novel binary mutation method is proposed to balance the exploration and exploitation ability. Thirdly, the multiobjective binary differential evolution is proposed by integrating the summation of normalized objectives and diversity selection into the binary differential evolution algorithm. Finally, the MOBDE algorithm is used for feature selection, and support vector machine (SVM) is used as the classifier with the leave-one-out cross-validation method (LOOCV). In order to show the effectiveness and efficiency of the algorithm, the proposed method is tested on ten gene expression datasets. Experimental results demonstrate that the proposed method is very effective.

关键词： multiobjective method differential evolution algorithm binary differential evolution binary optimization

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