Optimal Management of Mobile Energy Generation and Storage Systems

Samara, S. M.; Shaaban, Mostafa F.; Osman, Ahmed

doi:10.1109/access.2020.3036702

Cited by 10 publications

(7 citation statements)

References 25 publications

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“…Thus, the first part that manages the duration of the MESS visits assumes a fixed order using the binary decision variable X p,t , where X p,t = 1 indicates that the MESS is connected to PL p at time t. A binary decision variable M p,t is introduced to express the traveling phase between PLs p and p + 1. At any time segment, the MESS can be either connected to a PL p or travelling between two PLs as in (20). The MESS should visit all the PLs as in (21) and it should also travel from all PLs except the last one as in (22).…”

Section: Scheduling and Sequencing Modellingmentioning

confidence: 99%

“…An operation strategy of MESSs is presented in [19], which uses a progressive hedging (PH) algorithm. In [20], a mix of mobile energy generation and storage systems (MEGSSs) is proposed to serve commercial customers aiming at maximizing the economic profitability. The optimal dispatch of a fleet of MEGSSs to supply power to customers who require alternative sources of power during peak time is developed.…”

Section: Introductionmentioning

confidence: 99%

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Optimal dispatch of a mobile storage unit to support electric vehicles charging stations

Elmeligy,

Shaaban,

Azzouz

et al. 2023

IET Intelligent Trans Sys

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As transportation electrification increases globally, new technologies emerged in the past few years to meet the growth of the electricity demand. Mobile Energy Storage Systems (MESS) offer versatile solutions, aiding distribution systems with reactive power, renewables integration, and peak shaving. An MESS can be utilized to serve electric vehicles (EVs) in different parking lots (PLs), in addition to supplying power to the grid during overloads. The task of multiple stationary units can be achieved using MESS at a relatively lower cost. This paper proposes an MESS owned by multiple PLs sharing the same geographical area and sharing its capital and operational cost. The main objective of the proposed approach is to dispatch the MESS in conjunction with optimal EVs’ charging coordination to minimize operational costs and address the extra demand of PLs. A mixed‐integer nonlinear programming (MINLP) problem is formulated and solved. Considering electricity price variations and EVs uncertainties, three different case studies are performed to highlight the efficiency and success of the proposed approach. The simulation results in a huge reduction in the total operation cost and the savings reach up to 27.51% in comparison with the base case.

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Section: Scheduling and Sequencing Modellingmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Optimal dispatch of a mobile storage unit to support electric vehicles charging stations

Elmeligy,

Shaaban,

Azzouz

et al. 2023

IET Intelligent Trans Sys

Self Cite

View full text Add to dashboard Cite

show abstract

“…The active power output P PV i,φ,t,s of a PV depends on the rating of the solar cell P rate i and the solar irradiance I r i,t,s [21]. The generated output power from the PV can be determined in constraints (12) and (13), respectively. The binary variable χ i,t,s equals 1 if bus i is energized at time t and scenario s.…”

Section: Pv System Constraintsmentioning

confidence: 99%

“…In [10] and [11], a two-stage framework is developed to position mobile emergency generators (MEGs) for pre-and post-disasters. Mobile energy storage devices (MESs) are investigated in [12] and [13] for resilience enhancement of power distribution systems. However, there remain limitations in the above studies on pre-event preparation and resource allocation.…”

Section: Introductionmentioning

confidence: 99%

Stochastic Pre-Event Preparation for Enhancing Resilience of Distribution Systems with High DER Penetration

Zhang,

Wang,

et al. 2020

Preprint

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This paper proposes a stochastic optimal preparation and resource allocation method for upcoming extreme weather events in distribution systems, which can assist utilities to achieve faster and more efficient post-event restoration. With the objective of maximizing served load and minimizing operation cost, this paper develops a two-stage stochastic mixed-integer linear programming (SMILP) model. The first-stage determines the optimal positions

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“…In [90] and [91], a two-stage framework is developed to position mobile emergency generators (MEGs) for pre-and post-disasters. Mobile energy storage devices (MESs) are investigated in [92] and [93] for the resilience enhancement of power distribution systems. However, there are limitations in the above studies on pre-event preparation and resource allocation.…”

Section: Pre-event Preparation and Resource Allocationmentioning

confidence: 99%

Multi-agent optimization and learning methods for sustainable, smart and resilient power distribution systems and microgrids

Zhang

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Optimal Management of Mobile Energy Generation and Storage Systems

Cited by 10 publications

References 25 publications

Optimal dispatch of a mobile storage unit to support electric vehicles charging stations

Optimal dispatch of a mobile storage unit to support electric vehicles charging stations

Stochastic Pre-Event Preparation for Enhancing Resilience of Distribution Systems with High DER Penetration

Multi-agent optimization and learning methods for sustainable, smart and resilient power distribution systems and microgrids

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