Robust expansion planning of a distribution system with electric vehicles, storage and renewable units

Baringo, Luis; Boffino, Luigi; Oggioni, Giorgia

doi:10.1016/j.apenergy.2020.114679

Cited by 60 publications

(19 citation statements)

References 45 publications

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“…A distribution expansion planning problem was solved by an adaptive robust optimization approach (Baringo et al, 2020). The objective function was to minimize the sum of both investment and operation costs.…”

Section: Distribution System Planningmentioning

confidence: 99%

Optimal Sequential Distribution Planning for Low-Voltage Network With Electric Vehicle Loads

Sangob

Sirisumrannukul

2021

Front. Energy Res.

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There has been a growing presence of electric vehicles in many countries including Thailand, where many forms of incentives have been provided to build integrated infrastructure, and to encourage drivers to switch to electric vehicles (EVs). Because the immediate entry of EVs unavoidably can alter household load profiles, reinforcement on the existing system based on traditional planning may not be sufficient and can introduce over or under capital and operating expenditure over the time horizon. Therefore, if distribution systems are unreadily prepared for such an uptake, three obvious problems can be expected: 1) voltage regulation, 2) overloads of the distribution feeders and the distribution transformers, and 3) high energy loss. In this paper, an activity-based, time-sequential Monte Carlo Simulation algorithm was comprehensively developed for uncontrollable and smart charging, given annually updated information of EV locations and number of EVs, their energy consumption, hourly average vehicle speed, number of daily trips, travel distance per trip, size of EV batteries, time to arrive home and time to leave home. Minimizing the annual sum of investment and operating costs over a planning period could then be sequentially solved by a Particle Swarm Optimization (PSO) algorithm. The results from a practical 122-bus, 24 kV/400 V distribution system with different scenarios of uncontrollable and smart charging show that the sequential optimization embedded with deterministic decision can help improve customer voltage profile, keep feeder and transformer loading within acceptable operating limits and offer significant cost savings from energy loss. As far as a large number of low-voltage networks, and the associated large sum of cost savings are concerned, the proposed planning framework is practical to be applied and expected to be served as a new guideline for future implementation in Thailand.

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Section: Distribution System Planningmentioning

confidence: 99%

Optimal Sequential Distribution Planning for Low-Voltage Network With Electric Vehicle Loads

Sangob

Sirisumrannukul

2021

Front. Energy Res.

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“…10, shows that when the energy demand is higher than the energy produced, i.e. [11][12][13][14][15][16][17][18][19][20][21][22] peak hours, the storage unit supplies the energy stored to satisfy the DSO demand. Figure 11, reveals that the total energy in the storage unit decreases because of the discharge during that period.…”

Section: Simulation Resultsmentioning

confidence: 99%

“…Figure 10, shows that when the energy demand is higher than the energy produced, i.e [11][12][13][14][15][16][17][18][19][20][21][22]. peak hours, the storage unit supplies the energy stored to satisfy the DSO demand.…”

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confidence: 99%

Modelling and analysis of virtual power plants interactive operational characteristics in distribution systems

Ullah¹,

Mirjat

2021

Energy Conversion and Econom

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This study provides an overview of virtual power plants as aggregated flexibility service providers in distribution systems. The integration of photovoltaic energy sources increases uncertainty regarding the operation of distribution grids, impacting power quality. Innovative ideas are therefore needed to support the migration of traditional systems toward a smart grid. A virtual power plant could make use of the flexibility of emerging technologies to address these power quality and grid operation issues. To this end, this study introduces a new concept describing a location-specific interactive flexibility market framework in the context of a virtual power plant setting. In this proposed setting, flexibility providers (i.e. prosumers) can support location-based services in distribution systems. These services would reasonably alleviate the need to upgrade or substitute power capacity cost-effectively and facilitate the reliable and safe operation of the distribution grid. A direct control algorithm is designed and developed for the market studied, which was implemented to verify its efficacy experimentally. The efficiency of the proposed mathematical model and method is confirmed by the results of a case study using the UK-16 busbar generic distribution system, and finally some specific conclusions are drawn regarding the application of the proposed method.

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“…In [7] the MILP model of power system expansion planning was deployed to evaluate the impact of EVs on the distribution system with charging stations, storages, and distributed energy resources. An adaptive robust optimization model, formulated as MILP, was used in [63] to determine the least-cost investment planning of charging stations, solar units, and battery storage, considering long-term uncertainty and short-term meteorological variability. Banol Arias et al [64] focused on the small scale local distribution system expansion planning, co-optimized with the least-cost allocation of the charging stations.…”

Section: B Overview Of Ev Modeling Literaturementioning

confidence: 99%

Analyzing Electric Vehicle Load Impact on Power Systems: Modeling Analysis and a Case Study for Maldives

Suski¹,

Remy

Chattopadhyay

et al. 2021

IEEE Access

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Robust expansion planning of a distribution system with electric vehicles, storage and renewable units

Cited by 60 publications

References 45 publications

Optimal Sequential Distribution Planning for Low-Voltage Network With Electric Vehicle Loads

Optimal Sequential Distribution Planning for Low-Voltage Network With Electric Vehicle Loads

Modelling and analysis of virtual power plants interactive operational characteristics in distribution systems

Analyzing Electric Vehicle Load Impact on Power Systems: Modeling Analysis and a Case Study for Maldives

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