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Fast and systematic approach for adjusting ROCOF relay used in islanding detection of SDG

IET GENERATION TRANSMISSION & DISTRIBUTION 2020年第2期14卷 275-283页

作者： Ahmadzadeh-Shooshtari, Babak Hamedani Golshan, Mohamad Esmail Rezaei-Zare, Afshin York Univ Dept Elect Engn & Comp Sci Lassonde Sch Engn Toronto ON M3J 1P3 Canada Isfahan Univ Technol Dept Elect & Comp Engn Esfahan *** Iran

Frequency-based relays, commonly used for islanding detection of synchronous distributed generation (SDG), may either have large non-detection zones (NDZs) or wrongly operate for non-islanding disturbances unless they are efficiently adjusted. Trial and error simulation-based methods, employing application region (AR) and/or power imbalance AR (PIAR), are presented in the literature to adjust these relays for quick islanding detection without false trips. However, the associated settings are not optimal and finding them is time-consuming. In this study, an approach utilising particle swarm optimisation algorithm is proposed to adjust a rate of change of frequency (ROCOF) relay, one of the most effective relays in SDG islanding detection. The proposed approach needs a set of analytical formulas for determining the ROCOF relay performance curve and NDZ as well as AR and PIAR. These formulas are developed to be employed in the relay adjustment. By applying the developed analytical formulas to the optimisation-based approach, the ROCOF relay is adjusted fast and systematically. It is shown that while the performance of the relay adjusted by the proposed approach is close to the one with setting obtained by corresponding trial and error-based method, the latter is much more time-consuming than the former.

关键词： relay protection distributed power generation power distribution faults power distribution protection particle swarm optimisation systematic approach frequency-based relays synchronous distributed generation nondetection zones nonislanding disturbances error simulation-based methods quick islanding detection associated settings particle swarm optimisation algorithm frequency relay effective relays SDG islanding detection ROCOF relay performance curve optimisation-based approach error-based method ROCOF relay adjustment

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Siting and sizing of electric vehicle fast-charging station based on quasi-dynamic traffic flow

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IET RENEWABLE POWER GENERATION 2020年第19期14卷 4204-4215页

作者： Qian, Zhang Yi, Zhu Zhong, Wang Yue, Hu Yaojia, Su Chongqing Univ State Key Lab Power Transmiss Equipment & Syst Se 174 Shazhengjie Chongqing Peoples R China State Grid Chengdu Power Supply Co 63Sect 4Renmin South Rd Chengdu Sichuan Peoples R China

In engineering practice, the Voronoi diagram is often used to plan electric vehicle (EV) fast-charging stations but it does not consider the spatio-temporal distribution of EV trip. Research on the spatio-temporal distribution of EVs mainly uses the shortest path method to reduce the amount of iterative calculations. The influence of the external environment and traffic congestion on the travel of EVs has not been considered, which results in the inaccuracy of the EV charging demand. To solve the above problems, this study proposes a method for predicting the spatio-temporal distribution of EVs based on quasi-dynamic traffic flow. This method takes into account the external environment and the impact of traffic congestions on EV trips and balances the problem between simulation accuracy and calculation efficiency. Based on this, the particle swarm optimisation algorithm is used to optimise the travel cost of the EVs and the cost of the construction and operation of the charging infrastructure. An optimal siting and sizing model for the fast-charging station based on quasi-dynamic traffic flow is established. Simulation results verify the effectiveness of the model.

关键词： particle swarm optimisation electric vehicles electric vehicle charging iterative methods computational geometry road traffic particle swarm optimisation algorithm iterative calculations Voronoi diagram sizing model optimal siting charging infrastructure EV charging demand shortest path method spatio-temporal distribution electric vehicle fast-charging stations quasidynamic traffic flow

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FHCS: Hybridised optimisation for virtual machine migration and task scheduling in cloud data center

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IET COMMUNICATIONS 2020年第12期14卷 1942-1948页

作者： Balaji Naik, Banavath Singh, Dhananjay Samaddar, Arun B. Natl Inst Technol Sikkim Dept Comp Sci & Engn Sikkim India HUFS Global Campus Dept Elect Engn Yongin South Korea Natl Inst Technol Sikkim Dept Comp Sci & Engn Sikkim India

Cloud computing and virtualisation are recent approaches to develop minimum energy usage in virtualised cloud data centre (DC) for resource management. One of the major problems faced by cloud DCs is energy consumption which increases the cost of cloud user and environmental influence. Therefore, virtual machine (VM) consolidation is properly proposed in many approaches which reallocate the VMs by VM migration with the objective of minimum energy consumption. Here, VM consolidation based on the Fruit fly Hybridised Cuckoo Search (FHCS) algorithm is proposed to obtain the optimal solution with the help of two objective functions in cloud DC. This FHCS approach efficiently minimises the energy usage and resource depletion in cloud DC. The proposed work comparison is done with Ant Colony System (ACS), particle swarm optimisation (PSO) algorithm and Genetic algorithm (GA). The simulation conclusion reveals the advantage of the FHCS and VM migration method over existing procedures such as GA, PSO and ACS in terms of energy consumption and resource utilisation. The proposed method achieves 68 Kwh less energy and 72% less resources than existing methods. Simulation results have shown that energy consumption of the proposed method is reduced with less number of active PMs than other conventional approaches.

关键词： computer centres cloud computing virtual machines particle swarm optimisation genetic algorithms virtualisation energy consumption search problems virtual machine migration task scheduling cloud data center minimum energy usage virtualised cloud data centre resource management cloud DC cloud user environmental influence virtual machine consolidation minimum energy consumption VM consolidation objective functions FHCS approach resource depletion particle swarm optimisation algorithm Genetic algorithm VM migration method resource utilisation hybridised optimisation Fruit fly Hybridised Cuckoo Search algorithm

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Optimal multiaxial sensor placement for modal identification of large structures

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STRUCTURAL CONTROL & HEALTH MONITORING 2014年第1期21卷 61-79页

作者： He, Longjun Lian, Jijian Ma, Bin Wang, Haijun Tianjin Univ State Key Lab Hydraul Engn Simulat & Safety Tianjin 300072 Peoples R China

Research on optimal sensor placement has become a very important topic because of the need to obtain effective testing results with limited testing resources in modal identification and structural health monitoring. An integer-encoding multi-swarm particle swarm optimisation (IMPSO) algorithm is proposed to place multiaxial sensors optimally on large structures for modal identification. The concepts of grade evaluation and migration strategy and the mutation operators of genetic algorithm are introduced into the integer-encoding particle swarm optimisation algorithm. Three different fitness functions for optimal multiaxial sensor placement (OMSP) are investigated. The second fitness function considers spatial correlation based on Moran's I to solve the information redundancy of multiaxial sensor placement, whereas the other two functions evolve from the existing methods for comparison with the second fitness function. The novel algorithm and three fitness functions are further applied to the Laxiwa arch dam for verifications. The results show that the proposed IMPSO outperforms two existing algorithms in its global optimisation capability. The results also prove that the second fitness function has advantages in sensor distribution and ensuring the well-conditioned information matrix and observability of multidimensional modal shapes. The multiaxial sensor placement scheme determined by the proposed method is applied to the modal test of the Laxiwa arch dam under simulative ambient excitation. The results show that the scheme determined by the second fitness function can identify the frequencies and multidimensional mode shapes accurately, indicating that this method may be used to provide guidance for OMSP in various types of large structures. Copyright (c) 2013 John Wiley & Sons, Ltd.

关键词： multiaxial sensor optimal placement particle swarm optimisation algorithm Moran's I spatial correlation large structure

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Area optimisation of Two Stage Miller Compensated Op-Amp in 65 nm Using Hybrid PSO

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IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS II-EXPRESS BRIEFS 2022年第1期69卷 199-203页

作者： Rashid, Ria Nambath, Nandakumar Indian Inst Technol Goa Sch Elect Sci Ponda 403401 India

Analog circuit design can be formulated as a nonlinear constrained optimisation problem that can be solved using any suitable optimisation algorithms. Different optimisation techniques have been reported to reduce the design time of analog circuits. A hybrid particle swarm optimisation algorithm with linearly decreasing inertia weight for the optimisation of analog circuit design is proposed in this study. The proposed method is used to design a two-stage operational amplifier circuit with Miller compensation. The results show that the proposed optimisation method can substantially reduce the design time needed for analog circuits.

关键词： Optimization Analog circuits Transistors Optimization methods Standards Circuits and systems Circuit synthesis Analog circuit design area optimization particle swarm optimisation algorithm

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Velocity obstacle-based conflict resolution and recovery method

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AERONAUTICAL JOURNAL 2022年第1296期126卷 345-364页

作者： Sun, F. Chen, Y. Xu, X. Mu, Y. Wang, Z. Nanjing Univ Aeronaut & Astronaut Jiangning Rd Campus Nanjing Jiangsu Peoples R China 1 Jiazi Changle East Rd Xian Shanxi Peoples R China

Considering the shortcomings of current methods for real-time resolution of two-aircraft flight conflicts, a geometric optimal conflict resolution and recovery method based on the velocity obstacle method for two aircraft and a cooperative conflict resolution method for multiple aircraft are proposed. The conflict type was determined according to the relative position and velocity of the aircraft, and a corresponding conflict mitigation strategy was selected. A resolution manoeuvre and a recovery manoeuvre were performed. On the basis of a two-aircraft conflict resolution model, a multi-aircraft cooperative conflict resolution game was constructed to identify an optimal solution for maximising group welfare. The solution and recovery method is simple and effective, and no new flight conflicts are introduced during track recovery. For multi-aircraft conflict resolution, an equilibrium point that maximises the welfare function of the group was identified, and thus, an optimal strategy for multi-aircraft conflict resolution was obtained.

关键词： collision detection and resolution cooperative game geometrical algorithm optimal solution of alliance welfare particle swarm optimisation algorithm recovery track velocity obstacle method

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Bounded rational real-time charging pricing strategy under the traffic-grid coupling network

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IET ELECTRICAL SYSTEMS IN TRANSPORTATION 2022年第4期12卷 251-268页

作者： Wang, Chudi Ma, Shaohua Cai, Zhiyuan Yan, Ning Wang, Qiwei Shenyang Univ Technol Dept Elect Engn 111 Shenliao West Rd Shenyang Peoples R China

This study proposes a bounded rational charging guidance strategy based on mental account theory, which guides users to charge in an orderly manner by formulating real-time charging prices. Firstly, an orderly guidance framework for fast-charging EVs under the traffic-grid coupling network is constructed, and the influencing factors of various dimensions when users make charging decisions are analysed. Secondly, considering the bounded rational behaviour of users when making charging decisions, a multifactor bounded rational charging model for EV users based on mental account theory is proposed so as to obtain different charging costs for users when selecting charging stations. On this basis, a real-time charging price strategy based on the Stackelberg game model is constructed, with the goal of maximising the economic benefits of charging station operators while reducing the charging cost of EV users as much as possible. Finally, the particle swarm optimisation algorithm is used to solve the game model so as to solve the real-time charging price under various constraints. The simulation of an example verifies the rationality of the proposed real-time charging price formulation method and the superiority of the bounded rational charging guidance strategy.

关键词： game theory multifactor bounded rational charging guidance strategy particle swarm optimisation charging cost particle swarm optimisation algorithm EV users electric vehicle charging Stackelberg game model mental account theory traffic-grid coupling network power grids pricing charging price formulation method

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Active power optimisation for wind farms under generator inter-turn short-circuit fault

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IET RENEWABLE POWER GENERATION 2020年第12期14卷 2079-2088页

作者： Ma, Kuichao Soltani, Mohsen Hajizadeh, Amin Zhu, Jiangsheng Chen, Zhe Aalborg Univ Dept Energy Technol Niels Bohrs Vej 8 Esbjerg Denmark SEWPG European Innovat Ctr Inge Lehmanns Gade 10 Aarhus Denmark Aalborg Univ Dept Energy Technol Pontoppidanstr 111 Aalborg Denmark

Inter-turn short-circuit fault of the stator winding is one of the most common faults of asynchronous generators and often found in doubly-fed wind turbines. The improper treatment methods will lead to unnecessary power loss or further damage to the insulation layer. To solve this problem, an optimal power dispatch strategy (OPDS) is proposed which combines the control at the turbine level and the optimisation at the farm level. At the turbine level, the faulty turbine is down-regulated based on the principle that the fault current does not exceed the rated current. At the farm level, particle swarm optimisation is used to optimise the power references considering wake effects to compensate for the power loss caused by the downregulated turbine. The effectiveness of OPDS is illustrated by comparing with two usually used strategies, one takes proportional dispatch strategy (PDS) and directly shuts down the faulty turbine, the other takes PDS but ignores the fault. The results show that OPDS can minimise power loss under the premise of protecting the faulty turbine. The study contributes to reduce the maintenance costs of wind farms and improve the operational capability of the wind turbine under fault conditions.

关键词： power engineering computing power generation dispatch wind power plants optimisation wind turbines power generation control fault diagnosis stators particle swarm optimisation asynchronous generators turbine level faulty turbine farm level particle swarm optimisation algorithm power references down-regulated turbine OPDS proportional dispatch strategy wind farms wind turbine fault conditions active power optimisation generator inter-turn short-circuit fault stator winding asynchronous generators doubly-fed wind turbines improper treatment methods unnecessary power loss insulation layer optimal power dispatch strategy

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Mitigating the effects of geomagnetically induced currents in the power network

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IET GENERATION TRANSMISSION & DISTRIBUTION 2020年第23期14卷 5514-5525页

作者： Hesami Naghshbandy, Ali Ghaderi Baayeh, Arman Faraji, Ayda Univ Kurdistan Fac Engn Dept Elect Engn Sanandaj Kurdistan Iran

Geomagnetically induced currents (GICs) in long high-voltage transmission lines cause half-cycle saturation of transformers, malfunction of protective relays, reactive power loss, and voltage instability. This study describes the design for a GIC effects mitigation device (GEMD) that can be installed at a power system autotransformer common node connection to block the flow of GIC DC flux at the cores of the autotransformers. The devices consist of variable resistors, which are controlled by a wide-area method based on particle swarm optimisation algorithm. The effectiveness of the proposed protective electrical devices is investigated and validated through simulation studies under many operational cases. The test results obtained from 648 cases verify the high performance of GEMD. The proposed method can mitigate the reactive power loss due to GIC in the power system with average improvements by 7.9 and 7.09% over resistive and capacitive blocking devices, respectively.

关键词： power grids autotransformers transformer windings relay protection power transmission lines geomagnetism reactive power particle swarm optimisation power transmission protection reactive power loss resistive blocking devices capacitive blocking devices geomagnetically induced currents power network high-voltage transmission lines protective relays voltage instability mitigation device GEMD power system autotransformer common node connection GIC DC flux autotransformers wide-area method particle swarm optimisation algorithm protective electrical devices

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Optimal sizing and siting of smart microgrid components under high renewables penetration considering demand response

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IET RENEWABLE POWER GENERATION 2019年第10期13卷 1809-1822页

作者： Hakimi, Seyed Mehdi Hasankhani, Arezoo Shafie-khah, Miadreza Catalao, Joao P. S. Islamic Azad Univ Dept Elect Engn Damavand Branch Damavand Iran Amirkabir Univ Technol Dept Elect Engn Tehran Iran Univ Vaasa Sch Technol & Innovat Vaasa 65200 Finland Univ Porto Fac Engn P-4200465 Porto Portugal INESC TEC P-4200465 Porto Portugal

The purpose of this article is to determine the size and place of different components in microgrids (MGs) including renewable energy resources (RERs). Various factors like reliability, the uncertainty of wind speed, solar irradiance, load, and load growth are considered. The Ekbatan residential complex is studied as the pilot case study placed in Tehran, Iran. Ekbatan complex has three separate sets of buildings called phase 1, 2, and 3 considered as smart MGs. The multi-objective optimisation problem is solved considering RERs uncertainties, improving reliability and power quality and minimizing power loss by particle swarm optimisation algorithm. Different constraints in terms of voltage, frequency, resources, and energy storage systems (ESSs) capacity are taken into consideration. The effect of load growth, photovoltaic (PV) and ESSs placement, changing the capital cost of RERs, and demand response of controllable loads are studied on optimal sizing and siting. The proposed method is tested on a wind turbine/PV/fuel cell (FC)/hydrogen tank MGs system and the optimal sizing and siting of mentioned sources could decelerate the rate of increase in the total cost of MG considering the load growth.

关键词： energy storage wind turbines smart power grids renewable energy sources battery storage plants photovoltaic power systems optimisation distributed power generation hybrid power systems particle swarm optimisation energy management systems smart microgrid components high renewables penetration demand response size place different components microgrids including renewable energy resources wind speed solar irradiance load growth Ekbatan residential complex pilot case study Ekbatan complex smart MGs multiobjective optimisation problem RERs uncertainties minimizing power loss particle swarm optimisation algorithm different constraints energy storage systems capacity controllable loads wind turbine PV fuel cell /hydrogen tank MGs system

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