Hierarchical Coordination of Heterogeneous Flexible Loads

Xu, Zhiwei; Callaway, Duncan S.; Hu, Zechun; Song, Yonghua

doi:10.1109/tpwrs.2016.2516992

Cited by 74 publications

(65 citation statements)

References 31 publications

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“…Finds the time-slots in which each of the n k+ EVs need to be charged [31,93,155] Calculates the urgency factor of charging [31,67,155] The least laxity first (LLF) algorithm calculates the laxity [34,157,158] A SOC and laxity-based charging/discharging [34] To overcome the drawback, the authors in [34] have proposed a SOC and laxity-based charging/discharging. It divides the entire SOC-laxity plane into several groups as in Fig.…”

Section: Charging Strategies Referencesmentioning

confidence: 99%

“…Carlo simulation [29]), these strategies are suitable only for day-ahead scheduling [166] and realtime charging control for a large time resolution (e.g., 15 minutes [158]). Such unsuitability originates from the fact that a large number of samples entail running the load flow for a significant number of times, which adds up to a long runtime.…”

Section: Real-time Ev Load Dispatching Addressing Pv Output Variabilimentioning

confidence: 99%

“…The V2G includes services ranging from arbitraging energy in the market to providing ancillary services such as frequency and voltage support [15]. For the purpose, an EV population can be lumped together under the control of an aggregator, which can act as big virtual energy storage [158]. The aggregator can control the charging and discharge (V2G) of the aggregated EV population under the instructions of the grid owner regarding the grid constraints and costs.…”

Section: Estimation and Scheduling V2g Servicesmentioning

confidence: 99%

“…3.5 and prioritizing charging accordingly [34]. The laxity is defined as the degree of deferrability of charging [158]. However, since the laxity is relatively low for business premises, the SOC-laxity Cartesian plane can be approximated as in Fig.…”

Section: Soc-based Fair Charging Strategy (Fcs)mentioning

confidence: 99%

“…They now want to know what will be the impact of these charging rates if the charging rates remain unchanged at 12:01 pm, owing to the uncertainties involved in PV output and grid load. Two such uncertain cases are tested separately, namely 1) 50% reduction in PV output and 2) 5% increase in the grid, and the results are compared 158 in Table 6.10. This table shows that the operating conditions can quickly change due to the involved uncertainties, and the network operators can readily predict these new conditions.…”

Section: ) Applications Of the Impact Indicesmentioning

confidence: 99%

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PV-based EV charging station with vehicle-to-grid services for business premises

Islam¹

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The transportation sector is the second major contributor to the global greenhouse gas (GHG) emissions, next to electricity generation sector. GHG emissions are projected to grow in the future due to the over-reliance on fossil fuels for both electricity generation and transportation sectors.However, the growth can be stalled by gradually introducing electric vehicles (EVs) as they produce less GHG compared to their conventional counterparts. Despite that, their proliferation has been stunted by a completely new set of challenges in addition to a very high capital cost. These challenges include low driving ranges, scarcity of electric vehicle charging stations (EVCS), long charging time and inability to provide charging service readily. Nevertheless, some of these challenges can be addressed by installing EVCS at business premises (i.e., offices, universities, etc.) and augmenting EVCS with onsite PV and battery energy storage (BES). In that case, the impacts of EV charging on the grid will be less significant; charging services will be available readily, and GHG emissions growth can be reduced significantly. Moreover, EVCS, under suitable conditions, would be able to provide vehicle-to-grid (V2G) services, which makes EVCS more attractive.Despite such prospective opportunities, offhand planning and operational planning of EVCS would deem them unachievable. In addition, the inherent intermittency of PV, and EV and grids loads will pose considerable hindrance on availing those benefits.Hence, this research focusses on an EVCS with onsite PV and BES, in the perspective of planning and operational planning including V2G services. The cornerstone of the planning and operational planning is an appropriate EV load model that captures the uncertainties of EV charging. In addition, the EV load model reflects the grid voltage and EV battery's state of charge (SOC)-dependency of EV charging. Moreover, it accounts for the diversity of the EV population embodied by market shares, battery sizes, charging levels, and charging voltages, currents, and power factors. Furthermore, it is scalable to facilitate seamless assimilation of a large EV population. Therefore, a new EV load model is first proposed with MATLAB/Simulink validation reflecting the factors above along with the recommendations by the standard BS EN 61851-23:2014. This EV model is then incorporated into the planning activities, which include four chronological exercises. Firstly, the impact (i.e., grid voltage, current, losses, etc.) of the EV charging on the grid at different locations, namely home, office, public charging, is investigated considering the uncertainties. Secondly, the optimal location of the PV and BES based EVCS is divulged regarding the reduction of the impact and costs involved while enhancing the charging quality of service (QoS). Thirdly, a suitability analysis is performed for the obtained optimal location to find the most suitable combination of the grid upgrading, PV deployment, and BES iii deployment to satisfy the QoS, ...

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Section: Charging Strategies Referencesmentioning

confidence: 99%

Section: Real-time Ev Load Dispatching Addressing Pv Output Variabilimentioning

confidence: 99%

Section: Estimation and Scheduling V2g Servicesmentioning

confidence: 99%

Section: Soc-based Fair Charging Strategy (Fcs)mentioning

confidence: 99%

Section: ) Applications Of the Impact Indicesmentioning

confidence: 99%

See 3 more Smart Citations

PV-based EV charging station with vehicle-to-grid services for business premises

Islam¹

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An evaluation method for the response flexibility of aggregated inverter air conditioners

Lin

Liu

et al. 2020

Int Trans Electr Energ Syst

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Unified value-based feedback, optimization and risk management in complex electric energy systems

Ilić

Jaddivada

2020

Optim Eng

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The ideas in this paper are motivated by an increased need for systematic data-enabled resource management of large-scale electric energy systems. The basic control objective is to manage uncertain disturbances, power imbalances in particular, by optimizing available power resources. To that end, we start with a centralized optimal control problem formulation of system-level performance objective subject to complex interconnection constraints and constraints representing highly heterogeneous internal dynamics of system components. To manage spatial complexity, an inherent multi-layered structure is utilized by expressing interconnection constraints in terms of unified power variables and their dynamics. Similarly, the internal dynamics of components and sub-systems (modules), including their primary automated feedback control, is modeled so that their input-output characterization is also expressed in terms of power variables. This representation is shown to be key to managing the multi-spatial complexity of the problem. In this unifying energy/power state space, the system constraints are all fundamentally convex, resulting in the convex dynamic optimization problem, for typically utilized quadratic cost functions. Based on this, an interactive multi-layered modeling and control method is introduced. While the approach is fundamentally based on the primal-dual decomposition of the centralized problem, it is proposed for the first time to utilize sensitivity functions of distributed agents for solving the primal distributed problem. Iterative communication complexity typically required for convergence of point-wise information exchange is replaced by

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Hierarchical Coordination of Heterogeneous Flexible Loads

Cited by 74 publications

References 31 publications

PV-based EV charging station with vehicle-to-grid services for business premises

PV-based EV charging station with vehicle-to-grid services for business premises

An evaluation method for the response flexibility of aggregated inverter air conditioners

Unified value-based feedback, optimization and risk management in complex electric energy systems

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