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The purpose of this paper is to quantitatively compare two types of dual-permanent-magnet-excited (DPME) machines, one is with fewer stator poles and the other is with fewer rotor poles. Four different magnetization patterns of permanent magnets (PMs) are considered. Calculation results obtained using finite-element analysis demonstrate that with exactly the same usage of magnets and copper windings, the DPME machine with fewer rotor poles can offer significantly higher electromagnetic torque than that with fewer stator poles, and the torque ripple of the DPME machine with fewer rotor poles is lower than that with fewer stator poles. Another finding is that DPME machines can offer satisfactorily high-torque capability only when the two sets of PMs are with the same magnetization directions. [ABSTRACT FROM PUBLISHER]

• An inflatable structure is designed for Savonius wind turbine. • A double-layer fabrication process is proposed for the inflatable wind turbine. • Geometry parameters of the inflatable wind turbine are optimized based on CFD. • Static and dynamic performances are investigated through wind tunnel tests. • The inflatable wind turbine shows high portability and rapid deployment capability. Faced with the increasingly severe issue of the greenhouse effect, wind power emerges as a sustainable solution. However, the large size, heavy weight, and high risk associated with traditional wind turbines restrict their widespread deployment in urban, rural, and outdoor settings , wasting a vast amount of untapped wind energy resources. To address these challenges, this paper proposes an inflatable structure for the Savonius wind turbine and explores a double-layer fabrication process to manufacture the inflatable Savonius wind turbine (ISWT). 2D simulations are carried out on ANSYS-Fluent. Within predetermined parameter ranges, this paper successfully identifies the optimal geometric parameters for the ISWT model, with a blade thickness of 7 cm and a blade arc angle of 120°. This model exhibits the maximum power coefficient (C p) of 0.1912 at the tip speed ratio (λ) of 0.7. The manufactured ISWTs are fabricated based on the optimal geometric parameters. Due to deformation after inflation, the actual blade arc angle of the first ISWT sample is only 89.7°. Therefore, by adjusting the fabric template, an approximate blade arc angle of 120° is achieved for the second ISWT sample. Both ISWT samples are subjected to open-section wind tunnel tests. The results revealed that while the C p curves of Sample 1 and Sample 2 display trends similar to those in numerical results, the overall performance is lower. The reasons for the deviation include the simplification of vertical flow in 2D simulation and the lack of endplates. Specifically, Sample 2 also achieves the highest C p value of 0.1486 at λ = 0.7. Due to an inflation time within 60 s to the required pressure of 1.4 bar and a compressed volume lower than 0.021 m3, the ISWTs demonstrate rapid deployment capability during installation, portability during transportation, and storability during severe weather. [ABSTRACT FROM AUTHOR]

This paper addresses the significant challenges faced by distribution system operators (DSOs) in competitive electricity markets due to uncertainties arising from electricity markets, electric vehicles (EVs), and conventional loads. To tackle these challenges, this paper proposes a pseudo-local reserve market between the DSO and EVs, which enables the DSO to integrate EV flexibility into the overall market framework while compensating for deviations in the conventional load across the wholesale electricity market. Furthermore, a two-stage framework is developed to facilitate the participation of EVs in electricity markets. In the first stage, the reserve capacity of EVs is integrated into the decision-making process for day-ahead bidding, taking into account uncertainties of the load and electricity. In the second stage, the day-ahead results are coordinated to enable the efficient dispatch of EVs for real-time market participation. To assess the efficacy of the proposed framework, a case study is conducted within a 31-node distribution system situated on a university campus located in Guangdong, China. This paper investigates the economic impact of load deviation constraints on EV reserves, revealing a penalty reduction of 3100 CNY for a daily reservation of 1000 EVs and a net profit increase of 1300 CNY for DSOs utilizing reserves. It further introduces a method for quantifying reserve capacity, enhancing DSO decision-making accuracy. • A pseudo-local reserve market is established considering EV's reserve potential. • Optimal bidding strategy for DSO in China's electricity markets is constructed. • A framework for EV coordinated V2G operation is developed. • The proposed method can limit load deviation cost for more profits. [ABSTRACT FROM AUTHOR]

The vehicle-to-grid (V2G) technology is an effective and economic solution to enable the integration of electric vehicles (EVs) into power grids. As an effort to present the state of the art in relevant fields, the power interaction mode between EVs and power grids, and the scheduling methodology for the V2G implementation are overviewed comprehensively in this paper. To be specific, technical requirements, grid impacts and battery degradations regarding each power interaction mode are discussed; the operating processes of centralized and decentralized scheduling approaches are introduced and compared. More importantly, it is noted that few attentions are given to the solving algorithms of programming models used for optimizing the scheduling strategy of EVs and few works examine their feasibilities to acquire the optimal charging strategies especially for a large number of EVs. In this context, this paper also illuminates the mathematical foundation on optimization techniques for the optimal V2G strategy, and provides new insights for evaluating these models. • A review in the aspect of the EV-grid integration is made including power interaction mode and mainstream scheduling method. • Mathematical foundation on optimization techniques for the V2G strategy is given. • New insights are provided to make an overall evaluation on the existing methods. [ABSTRACT FROM AUTHOR]

Coordinated charging can utilize the properties of electric vehicles (EVs) to obtain various benefits. However, there are two major challenges, viz. the uncertainty of EV charging behaviors and the overlong solving time for the optimal solutions in the charging scheduling problem of large-scale EVs. It is almost infeasible to precisely predict the charging information of EVs due to the uncertainty of their mobility as transportation tools. In order to tackle this issue, the real-time charging scheduling method is employed in this paper. Even so, the computational complexity is crucially important in the real-time scheduling methods since the charging strategies of large-scale EVs must be acquired in a short time. Hence, a high efficient methodology is proposed for EV real-time scheduling based on the definition of capacity margin index and charging priority index. Finally, the simulation results show that the proposed scheduling method has a significant superiority over the uncoordinated charging in the regard of relieving the demand stress on the power system. Moreover, the complexity analysis demonstrates that the proposed method has near-linear complexity so that it can acquire the optimal real-time charging scheme in a rather shorter time than other methods. [ABSTRACT FROM AUTHOR]

Unplanned en-route charging of electric vehicles (EVs) can unexpectedly cripple traffic conditions. As less-effective location of fast charging station (FCS) may exacerbate this issue, the effects of FCS on EVs' charging behaviors should be incorporated at the system planning stage. This paper proposes a strategic-charging-behavior awared model in the context of electrified transportation network environment. This model is formulated into a bilevel mixed-integer programming problem. A newly designed network equilibrium model targets on the low-level problem, which is to model the drivers' charging reaction to a certain FCS layout. In considering the EV self-serving routing and charging behaviors as well as power network constraints, the upper-level problem is formulated for location and sizing decision-makings, of which the objective is to minimize the overall traffic time and investment cost. To handle the proposed bilevel problem, a descent algorithm is further developed. To examine the effectiveness of the proposed approach, extensive numerical experiments are conducted, through which the obtained results demonstrate that the EV charging demand can perfectly be met while traffic congestions can be alleviated to a great extent. • An augmented user equilibrium is introduced for EV traffic predicting. • A bilevel optimization model is designed for EV fast charging station location and sizing. • A descent solving algorithm is developed for tractable problem solving. [ABSTRACT FROM AUTHOR]

This paper proposes a novel management scheme, namely, the distribution system operator (DSO) as a key player participating in China's electricity markets owing to its high value-added capability, high customer loyalty and robust risk resistance. In light of this, this paper discusses the maximal marginal revenue for DSO in uncertain electricity markets with vehicle-to-grid operation incorporated. Initially, considering different benefit expectations of electric vehicles (EVs) owners, DSO could provide preferential contracts, including the discount price contract (DPC) and revenue-sharing contract (RSC), in exchange for the management rights of EVs. Then, the stochastic optimization model considering the spatiotemporal uncertainties of EVs and electricity markets is built up, and the optimal bidding and coordinating strategy are proposed to maximize the marginal revenue of DSO. Comprehensive case studies are conducted in a 31-node distribution system of a university campus under the electricity markets in Guangdong, China. Results reveal that different distribution of EVs parking lots has a significant impact on the profit of DSO, and the revenue for DSO is 13,477 yuan more than that for EVA by scheduling 1400 EVs' charging/discharging behavior properly. Additionally, the DSO with RSCs is exposed to 25% less market volatility risk than that with DPCs. • Comparing EV aggregator(EVA) and distribution system operator(DSO) characteristics. • Discount price contracts and revenue-sharing contracts are compared. • The advantages of DSO over EVA in market participation are analyzed. [ABSTRACT FROM AUTHOR]

• An easy-to-implement hybrid microgrid reconstruction scheme is proposed for old residential communities. • The existing transformers and power lines could be reused in the proposed hybrid microgrid architecture. • A significant maximum 297% of EV penetration could be obtained with the proposed architecture and operation strategy. • Real-time voltage regulation, desirable operation efficiency, and improved load ratio are to be implemented. The widespread popularity of electric vehicles (EVs) imposes great challenges for distribution grids, such as feeder congestion, voltage deviation, and so forth. Although building new electrical facilities is feasible to release more capacity for EV integration, this is not a wise scheme to be applied in old residential communities owing to huge costs and limited spaces. In light of this, the paper proposes an easy-to-implement and cost-effective hybrid AC/DC microgrid reconstruction scheme for low-voltage distribution grids of old residential communities. The advanced power electronic device called smart interlinking unit (SIU) is incorporated in prior power distribution rooms of residential communities, featuring integrated structure, dedicated interfaces, and flexible control capability. The SIU-based architecture reuses existing redundant transformers and power lines to form AC/DC subgrids. An outstanding transfer capacity improvement and power loss reduction via the DC renovation are quantified. Considering the varied efficiency characteristics of multiple power converters and transformers, a hierarchical coordinated operation strategy is proposed for this architecture to realize the overall energy-saving operation. The optimal operation point tracking and AC/DC voltage regulation are included in the strategy design. Regarding the target scenario in the case study, the adopted reconstruction scheme would achieve a significant 297% of the maximum EV penetration. The real-time voltage regulation for AC and DC feeders is also realized to avoid possible voltage violations. Additionally, the proposed architecture and operation strategy could obtain about 10% of load ratio improvement and 1.5% of average efficiency promotion compared to the traditional AC architecture. [ABSTRACT FROM AUTHOR]

As the number of electric vehicles (EVs) surges, EVs are expected to supply auxiliary services for power grid through the vehicle-to-grid (V2G) operation. Specifically, vehicle-to-vehicle (V2V), as a beneficial supplement of V2G, has received increasing attention owing to the capability for flexible EVs deployment and profitable individual interaction. In this paper, a genuine V2V market mechanism aiming for maximum revenue of each EV owner is proposed to construct a distributed electricity market. It reveals the dominance of EV owners from the perspective of market and allows the trade among EV owners in local distribution grid with charging points such as charging stations and auto parks. To this end, the implementation of V2V market mechanism is analyzed in detail, including the electricity price, the process and the integration with the internet of smart charging points (ISCP), a cyber-physical architecture. Then, EVs' energy dispatching is formulated via the non-cooperative game model, in which each EV owner anticipates maximizing individual revenue by choosing feasible strategies. The existence and uniqueness of Nash Equilibrium (NE) in a non-cooperative game is proved by means of variation inequality (VI) theory. Finally, the ISCP-based optimal algorithm is developed to solve the NE efficiently, thereby maximizing reward of each EV owner. Comprehensive case studies show that the proposed V2V market mechanism can implement distributed dealing among EV owners with reducing individual charging cost and regional load variance effectively. Specially, the costs of EV1, EV8 and EV9 decrease by 31%, 36% and 34%, respectively. And V2V charging demonstrates much lower variance (10.5209) than regular charging (14.1124). Additionally, the convergence of the algorithm is also demonstrated, reaching the NE in less than 30 iterations for each EV. • A genuine V2V market mechanism considering the dominance of EV owners is proposed. • The integration of V2V market mechanism and cyber-physical architecture is executed. • A non-cooperative game model and corresponding algorithm are adopted to solve the NE. • Revenue and load variance in EVs and convergence of the algorithm are analyzed. [ABSTRACT FROM AUTHOR]

• The so-called pseudo hierarchical energy management architecture built upon the smart EV charging point is firstly introduced. • The proposed energy management architecture is a compact, cost-effective, and easy-to-build scheme for nanogrid. • The introduced nanogrid operation strategy enables autonomous power coordination with V2G incorporated and efficient power dispatching simultaneously. • Comprehensive nanogrid operation scenarios and modes are analyzed via system simulation and hardware-in-loop experiment. Most recently, DC nanogrid incorporating effective energy management has attracted widespread attention. Due to its favorability to integrate renewable energy sources and emerging power electronic loads, such as photovoltaics and electric vehicles (EVs), DC nanogrid is believed to be able to improve the energy utilization efficiency and mitigate the carbon footprint in the coming decades. Towards a compact, cost-effective, and easy-to-build energy management scheme for nanogrid, this paper presents a pseudo hierarchical management architecture built upon the smart charging point. The proposed architecture incorporates the upper-level central controller with the local power role creatively and comprises two timescale management levels with corresponding operation strategies. In the short-timescale local management level, a state-triggered droop strategy based on the decentralized control mechanism is introduced to realize the autonomous power coordination without extensive communication links. The autonomous vehicle-to-grid (V2G) operation is also implemented with providing real-time power balance capability to unpredicted and short-timescale load variation in peak periods. In the power dispatching level, a multi-mode power dispatching strategy involving six operation modes is introduced to realize the efficient power scheduling for the nanogrid. The effectiveness of the proposed architecture and operation strategy is verified in the detailed simulation model and hardware-in-loop experiment platform. The results show that the real-time, autonomous, and stabilized power coordination in nanogrid could be realized along with a self-regulated V2G operation. Additionally, the peak-shaving and valley-filling of load curve, the satisfaction of EV charging demand, and an improved operation economy are achieved under the proposed architecture and operation strategy. [ABSTRACT FROM AUTHOR]

• A scalable and reconfigurable hybrid microgrid clustering architecture is proposed. • The proposed ENU features multiplexed structure and flexible functionalities. • The ENUs could realize mutual AC/DC interconnection by same converter modules. • The autonomous power coordination within and between microgrids is achieved. • The utilization and local consumption of RESs with system reliability is improved. Microgrid clusters are effective to increase utilization of renewable energy resources (RESs), and improve reliability and stability of power systems. Facilitating flexible configurations, grid networking and coordinated operation among multiple microgrids are essential for the microgrid cluster. In view of this, this paper presents a scalable and reconfigurable hybrid microgrid clustering architecture and a corresponding decentralized control method. Initially, a new interlinking converter referred as energy networking unit (ENU) is proposed. The ENU is used to interface the AC and DC subgrid in single hybrid microgrid, and also facilitates the connection with the external power grid. Then the ENU-based hybrid microgrid clustering architecture is established, which is characterized by scalability, reconfigurability and modularity. Thanks to the reconfigurable topology of ENUs, the architecture could realize flexible AC/DC interconnection between microgrids by the same converter modules with less power conversion units. Finally, a proposed decentralized control strategy for this architecture could realize autonomous power exchange between subgrids in single microgrid with considering energy storage restrictions and smooth mode switch. And an adaptive and autonomous power interaction among neighboring microgrids is also achieved with full utilization of the compensation capacity of clusters, thus improving the system reliability, as well as the utilization and local consumption of RESs. The effectiveness of the proposed clustering architecture and decentralized control strategy is verified by comprehensive cases. [ABSTRACT FROM AUTHOR]

• A cyber-physical co-modeling is developed to fulfill the essential insights of ISCP. • A hierarchical distributed V2G coordination apt to parallel computing is proposed. • The cyber topology for ISCP is fully discussed in terms of communication efficiency. Vehicle-to-grid (V2G) technology plays an important part in achieving carbon neutrality. Hence, reducing the execution time under the real-time application becomes an urgent issue. In this paper, we develop a cyber-physical co-modeling to fulfill the fundamental insights into the internet of smart charging points (ISCP), wherein the local controllers are designed near the plug-in electric vehicles (PEVs), and are coordinated with each other. In perspective of energy dispatching, a hierarchical V2G scheduling is implemented in a distributed way to decompose the optimization problem into several sub-problems. Besides, the parallel computing is applied in the V2G problem to accelerate the speed of obtaining results. Moreover, the voltage regulation is applied near the energy coordinator with high-performance computer rather than by the local controller. In perspective of network communication, the small-world network is applied to ensure the communication efficiency and decrease the wiring costs. Besides, the privacy-preserving of both the energy coordinator and the PEV users is guaranteed by processing and storing the sensitive information of the two participants nearby. Finally, the cyber-physical co-modeling is performed in Matlab and Network Simulator 2. Results show load flatting, self-consumption of photovoltaic output, voltage regulation, and up/down regulation are achieved. Moreover, the delay of small-world network is 90.94 times faster than that of lattice network, and the cost of small-world network is nearly 500 times less than that of full mesh network. Particularly, the execution time for V2G operation at one-time interval is less than 1 s. [ABSTRACT FROM AUTHOR]

• The day-ahead bidding strategy of electric vehicle (EV) aggregator is explored. • Two typical agent modes between EV users and EV aggregator are introduced. • The market uncertainty is handled by analyzing potential market clearing scenarios. • The Guangdong electricity market is first investigated for case study. The electric vehicle (EV) aggregator is a new entity that coordinates the charging of an EV fleet to exploit the business opportunities in the electricity market. This paper explores the optimal bidding strategy for the EV aggregator participating in day-ahead markets. Two typical agent modes between the EV aggregator and the EV user are introduced based on the reality need of the EV user, viz. the centralized protocol management mode (CPMM) and the decentralized demand response mode (DDRM). After that, the stochastic optimization model is developed to maximize the expected profits of EV aggregator. The uncertainties from the electricity market and the EV charging are incorporated into the stochastic optimization model. The Guangdong electricity market, as the pioneer of China's power reform, is first investigated as the target market to verify the rationality of the proposed approach. The possible real-time clearing scenarios are extracted from the historical market clearing data using the multi-class support vector machine (MSVM). Results reveal that the EV aggregator can make an optimal bidding strategy for the potential clearing scenarios when multiple agent modes are involved. Moreover, the comparison of two agent modes indicates that the EVs with the CPMM are more sensitive to the electricity price than those with the DDRM. [ABSTRACT FROM AUTHOR]

• An V2G scheme concerning on edge computing is proposed. • The architecture of scheme is scalable, reliable and information secure. • The algorithm of scheme aims at PV self-consumption and load flattening. • The proposed scheme provides very high computational performance. • Case studies are verified in terms of the short-time scale and the long-time scale. Plug-in electric vehicles (PEVs) and renewable energy sources (RESs) can relief the stress on air pollution. Particularly, using RES for PEV energy requirement can integrate more RESs on the grid. In this paper, a vehicle-to-grid (V2G) scheme concerning on RES and edge computing, i.e. the internet of smart charging points with photovoltaics integration, is presented. Within the architecture of the scheme, each charging point equips computing and storage units, so as to store PEV sensitive information locally and conduct "burn after scheduling". Besides, this architecture can transform the traditional large-scale V2G problem into several sub-problems, which are small enough to optimize. Based on the architecture of the scheme, an associated high-efficiency algorithm is designed. Six typical scenarios of PEV charging are elaborated and two indexes are presented to facilitate 1) the self-consumption of photovoltaics energy by PEV charging and 2) the peak-shaving and valley-filling of net load. Additionally, voltage regulation and real-time control are applied to ensure the security of the distribution grid and mitigate the uncertain conditions. Finally, compared with uncoordinated charging, the short-time scale simulation realizes the peak-shaving and valley-filling by 17.54% and 12.42%, respectively; and the amount of self-consumption of photovoltaics energy increases by 258.74%. Furthermore, the long-time scale simulations also present a satisfying performance for the grid energy saving and the load factor. Particularly, the proposed scheme offers high computational efficiency compared with different architecture and algorithm, and the execution time for scheduling one PEV at one-time interval shows a microsecond basis. [ABSTRACT FROM AUTHOR]

• For the first time, the GA surface of WEVC systems is found out as a thermal safety hazard. • Based on IEC standards, four hazard levels are proposed to rate the over-temperature risks of GA surface. • Before thermal stability is reached, transient-state simulations are used to reflect the time-dependent hazard level. • An area-based approach is used to rate the thermal-stable hazard level. • The sensitivity of different misalignments to the temperature rise of GA surface is analyzed. To support e-mobility, wireless electric vehicle charging (WEVC) emerges as a promising technology by virtue of convenience characteristics and the mitigation of range anxiety. Recently, the safety issues on WEVC systems have drawn considerable attention. In light of thermal safety, the most critical part of WEVC systems is the surface of ground assembly (GA). During the charging process, its temperature increases due to the power losses, possibly resulting in cutaneous injury to living bodies and the ignition of foreign objects. Especially when there are evitable misalignments between the GA and vehicle assembly, its temperature rise will be higher as a penalty of efficiency deterioration of WEVC systems. Unfortunately, it has rarely been deemed as a safety hazard yet. Taking a commercialized WEVC system rated at 6.6 kW as an example, this paper focuses on the safety assessment of GA surface. The overtemperature-related losses, including core loss, ohm loss and eddy-current loss, are calculated. The thermal analysis is conducted based on the heat transfer theory. The temperature distribution of GA surface is obtained using transient-state FEM simulations. Based on IEC standards, four hazard levels are proposed as evaluation criteria. Finally, the calculated accuracy is validated experimentally. The results reveal direct influence of misalignments on the temperature rise. The sensitivity of different misalignments to the temperature rise is also analyzed. When the horizontal displacement exceeds 98.86 mm or the angular offset (type II) exceeds 9.91 deg., the highest hazard level could be reached, which highlights severe over-temperature risks of GA surface. [ABSTRACT FROM AUTHOR]

• An integrated and reconfigurable hybrid AC/DC microgrid architecture based on a novel interlinking converter is proposed. • The hierarchical control strategy for the proposed microgrid architecture is designed considering 17 operation modes. • The optimal coordination of power exchanges between AC and DC sub-grid can be realized. • The utilization and local consumption of renewable energy resources in the proposed microgrid architecture are increased. With the ever-increasing of population and economy worldwide, buildings have become major energy consumers and greenhouse gas (GHG) emitters. The hybrid AC/DC microgrid is a promising alternative for existing power distribution systems to achieve the goal of nearly/net zero energy buildings (nZEBs). However, the increasing demand for compact structure, seamless integration of distributed generators (DGs) and loads, as well as more control flexibility of hybrid microgrids cannot be adequately satisfied by conventional grid architectures. In view of this, an integrated and reconfigurable hybrid AC/DC microgrid architecture with its hierarchical control strategy is proposed in this paper. Firstly, a novel interlinking converter named smart interlinking unit (SIU) is presented, which can provide multiple AC/DC interfaces and diverse operation modes with various control functionalities. Secondly, the SIU-based hybrid microgrid architecture and its hierarchical control structure are established. The dedicated interfaces and cluster controllers for electric vehicles (EVs) facilitate the implementation of centralized vehicle-to-grid (V2G) service. Thirdly, a hierarchical control strategy of SIU, which involves local control in primary control level and power flow control in secondary control level, is introduced to realize coordinated operation of microgrid. The model of the proposed hybrid microgrid architecture is built, and the simulation results demonstrate that the microgrid architecture and hierarchical control strategy can achieve a reliable and coordinated system operation under various kinds of scenarios. Additionally, the mutual power support between AC and DC sub-grids is realized with increased utilization and local consumption of renewable energy resources (RESs). [ABSTRACT FROM AUTHOR]

With the growing adoption of electric vehicles (EVs), there is a pressing need for constructing charging infrastructures. In this context, wireless charging technology has been under development for the past few decades. Dispensed with awkward plugs and wires, wireless power transfer (WPT) technology is very safe, convenient and easy-to-use. Researchers have taken sustained efforts to make it an improved technology and automakers also work to provide the wireless charging option for their customers. In this paper, the basic principles of resonant inductive power transfer that is common-used for wireless electric vehicle charging (WEVC) are elaborated. Then, with a different emphasis on WEVC technologies, the key issues in academia and industry are discussed respectively. The core technologies of a fully-function WEVC system in academia are summarized and a comparative study is conducted among the selected WEVC industry standards. In addition, based on the possible technical development and currently valid policies, the author envisions the future of WEVC, followed by some conclusions and helpful advice. • Comprehensive overview of the core technologies of a fully-function wireless charging system for EVs. • Comparative analysis of several industry standards on wireless charging for EVs. • Constructive advice on the future development of wireless charging for EVs. [ABSTRACT FROM AUTHOR]