The main purpose of this paper is to evaluate the overall performance of a battery energy storage system (BESS) during I) grid‐connected, II) black start, and III) islanded operating modes. To do so, firstly, a novel three‐mode controller is proposed and developed. The proportional–integral–derivative (PID) controller is implemented, including the following three components: (1) inertia emulation, (2) frequency‐active power and voltage‐reactive power droops, and (3) secondary frequency and voltage controllers. Secondly, to effectively evaluate the proposed controller performance under various grid operating conditions during both black start and seamless transition to islanded operation, a set of comprehensive dynamic simulations using Matlab/Simulink is carried out. To this end, the sensitivity analyses on numerous grid operating parameters, such as pre‐disturbance grid power, total installed BESS capacity, battery state of charge, unbalanced three‐phase load flows, implemented power‐frequency controller parameters, and distribution network types with various shares of dynamic and static loads, are performed. Thirdly, to practically improve the seamless transition performance enabling the demand response participation, a fast‐controlled thermostatic load scheme is implemented. Simulation results show that the BESS unit using the proposed three‐mode controller has great potential to successfully control the frequency and voltage within allowable limits during both islanding and black start modes over a wide range of grid operating conditions.

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This paper summarises and evaluates in detail aggregate models of plug-in electric vehicles (PEVs) for primary frequency control (PFC) through dynamic simulations. A basic aggregate model of PEVs for PFC is introduced and then gradually developed in the following steps: 1) technical characteristics of PEVs are incorporated into the model; 2) technical characteristics of distribution networks are formulated and added; 3) a strategy is described to well-design the frequency-droop controller of PEVs for PFC. Moreover, from an economic point of view, a method is presented to assess the benefits which could result from PEVs for PFC. Four simulation scenarios are defined to evaluate the impact of: 1) different PEV’s penetration levels; 2) PEV’s operating modes and constraints; 3) power consumed in the network during the PFC; 4) well-designed frequency droop controller, on the frequency response following a contingency event. Simulation results show that aggregate PEVs have a great potential not only to improve the frequency response, while preserving the overall stability, but also to save some costs associated with PFC.@en

This paper describes a novel strategy to design the frequency-droop controller of plug in electric vehicles (PEVs) for primary frequency control (PFC). To be able to properly compare the frequency response of control system with and without PEVs, the design is done to guarantee the same stability margin for both systems in the worst case scenario. To identify the worst case, sensitivity analyses are conducted on a large set of system parameters performing eigenvalue analysis and bode plots. Three main contributions are included in this work: (i) we demonstrate that PEVs using the well-design droop controller significantly improve the PFC response while successfully preserving the frequency stability, (ii) since the fast response of PEVs may cause to mask the governor-turbine response in conventional units, a novel control scheme is developed to replace some portion of PEV’s reserve after a certain time by the reserve of conventional units during PFC, and (iii) a method is proposed to evaluate the positive economic impact of PEV’s participation in PFC. For the latter, the system PFC cost savings mainly through the avoidance of under frequency load shedding by PEVs are calculated. A large-scale power system and an islanded network are evaluated and compared through dynamic simulations, which illustrate the validity and effectiveness of the proposed methodologies.@en

The number of plug-in electric vehicles (PEVs) is likely to increase in the near future and these vehicles will probably be connected to the electric grid most of the day time. PEVs are interesting options to provide a wide variety of services such as primary frequency control (PFC), because they are able to quickly control their active power using electronic power converters. However, to evaluate the impact of PEVs on PFC, one should either carry out complex and time consuming simulation involving a large number of PEVs or formulate and develop aggregate models which could efficiently reduce simulation complexity and time while maintaining accuracy. This thesis proposes aggregate models of PEVs for PFC. The final aggregate model has been developed gradually through the following steps. First of all, an aggregate model of PEVs for the PFC has been developed where various technical characteristics of PEVs such as operating modes (i.e., idle, disconnected, and charging) and PEV’s state of charge have been formulated and incorporated. Secondly, some technical characteristics of distribution networks have been added to the previous aggregate model of PEVs for the PFC. For this purpose, the power consumed in the network during PFC as well as the maximum allowed current of the lines and transformers have been taken into account. Thirdly, the frequency stability margins of power systems including PEVs have been evaluated and a strategy to design the frequency-droop controller of PEVs for PFC has been described. The controller designed guaranties similar stability margins, in the worst case scenario, to those of the system without PEVs. Finally, a method to evaluate the positive economic impact of PEVs participation in PFC has been proposed.@en

Summary form only given. The penetration level of plug-in electric vehicles (PEVs) has the potential to be notably increased in the near future, and as a consequence, power systems face new challenges and opportunities. In particular, PEVs are able to provide different types of power system ancillary services. The capability of storing energy and the instantaneous active power control of the fast-switching converters of PEVs are two attractive features that enable PEVs to provide various ancillary services, e.g., primary frequency control (PFC). However, concurrently, PEVs are obliged to be operated and controlled within limits, which curbs the grid support from PEVs. This paper proposes a new model for PEV using a participation factor, which facilitates the incorporation of several PEV fleets characteristics such as minimum desired state of charge (SOC) of the PEV owners, drive train power limitations, constant current and constant voltage charging modes of PEVs. In order to reduce computational complexity, an aggregate model of PEVs is provided using statistical data. In the end, the performance of PEVs for the provision of PFC is evaluated in a power system. Results show that PEV fleets can successfully improve frequency response, once all the operating constraints are respected.@en

In the future, the number of plug-in electric vehicles (PEVs) that will participate in the primary frequency control (PFC) is likely to increase. In our previous research, the computational complexity of the PFC problem for a large number of PEVs was reduced using aggregate models of PEVs. However, in the literature on the PFC, the distribution network characteristics have not been included in the aggregate models of PEVs for the PFC, despite the fact that PEVs will be dispersedly connected to the distribution network. This paper proposes an aggregate model of PEVs for the PFC that further incorporates distribution network characteristics, i.e., the distribution network power loss (DNPL) and the maximum allowed current (MAC) of the lines and transformers. The DNPL variation is formulated according to the line and transformer impedance, spatial distribution of PEVs and loads, and active power variation of PEVs. Then, DNPL variation together with the MAC of the lines and transformers are incorporated in the proposed model of PEVs. Finally, the simulation results show an excellent agreement of 98% between the detailed model and the proposed aggregate model of PEVs.@en

In the future, the number of plug-in electric vehicles (PEVs) that will participate in the primary frequency control (PFC) is likely to increase. In our previous research, the computational complexity of the PFC problem for a large number of PEVs was reduced using aggregate models of PEVs. However, in the literature on the PFC, the distribution network characteristics have not been included in the aggregate models of PEVs for the PFC, despite the fact that PEVs will be dispersedly connected to the distribution network. This paper proposes an aggregate model of PEVs for the PFC that further incorporates distribution network characteristics, i.e., the distribution network power loss (DNPL) and the maximum allowed current (MAC) of the lines and transformers. The DNPL variation is formulated according to the line and transformer impedance, spatial distribution of PEVs and loads, and active power variation of PEVs. Then, DNPL variation together with the MAC of the lines and transformers are incorporated in the proposed model of PEVs. Finally, the simulation results show an excellent agreement of 98% between the detailed model and the proposed aggregate model of PEVs.@en

The penetration level of plug-in electric vehicles (PEVs) has the potential to be notably increased in the near future, and as a consequence, power systems face new challenges and opportunities. In particular, PEVs are able to provide different types of power system ancillary services. The capability of storing energy and the instantaneous active power control of the fast-switching converters of PEVs are two attractive features that enable PEVs to provide various ancillary services, e.g., primary frequency control (PFC). However, concurrently, PEVs are obliged to be operated and controlled within limits, which curbs the grid support from PEVs. This paper proposes a new model for PEV using a participation factor, which facilitates the incorporation of several PEV fleets characteristics such as minimum desired state of charge (SOC) of the PEV owners, drive train power limitations, constant current and constant voltage charging modes of PEVs. In order to reduce computational complexity, an aggregate model of PEVs is provided using statistical data. In the end, the performance of PEVs for the provision of PFC is evaluated in a power system. Results show that PEV fleets can successfully improve frequency response, once all the operating constraints are respected.@en

The development of smart grid solution concepts, such as islanding, make it possible to improve the security of supply in networks. The results experimented in real-life test systems must be extrapolated to wider areas and in other locations, which is not straightforward. The scalability and replicability analysis (SRA) aims to identify the relevant factors that affect smart grid implementations and understand the effects of their variation on the results achieved by smart grid solutions. This paper presents the SRA of an islanding use case in a medium voltage network using cogeneration. Furthermore, the results obtained have been used to obtain a set of scalability and replicability rules for islanding use cases that can be applied in other cases.@en

The new resources available in power system require a new agent to manage these resources in the most efficient way. Resources provided by the supply side or the demand side can be managed together in order to provide some services to the grid. New resources such as massive electric vehicle and distributed generation have been being gradually integrated to the grid and for the next years the integration tendency will follow increasing. These resources require a different approach to be managed adequately. The integration of intermittent resources into the grid is a challenging area but these issues can be addressed by an aggregator agent. On the other hand, the demand of power required by electric vehicle integration can impact the load curve of different distribution system far from its capability. An aggregator agent also can be useful to manage adequately the demand required by Electric Vehicles. This paper proposes an energy aggregator model (EAM) to manage power transactions between the grid and the demand side resources.@en