Transactive charging management of electric vehicles in office buildings: A distributionally robust chance-constrained approach

Saber, Hossein; Ehsan, Mehdi; Anvari‐Moghaddam, Amjad

doi:10.1016/j.scs.2022.104171

Cited by 13 publications

(8 citation statements)

References 38 publications

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“…𝑍 𝑒,𝑘 𝐸 = ∑ ∑ 𝐿𝐶 𝑛,𝑡,𝑒 𝑘 𝑛∈𝑁 𝑡∈𝑇 (16) The constraints of SP2 are the same as ( 8)-( 15) while considering the outage of component 𝑘. Moreover, Λ ELL is the set of decision variables of SP2.…”

Section: ∑ 𝑃mentioning

confidence: 99%

“…Also, this table indicates that corridors (6-10) and ( 14 problem. Also, several corridors, including (3-24), (6-10), (10)(11), (11)(12)(13)(14), (14-16), (15)(16)(17)(18)(19)(20)(21), (16)(17), and (16)(17)(18)(19)(20)(21)(22)(23), are among the selected corridors to install new transmission lines in the proposed co-planning and TEP problems which In the last step of the simulation study, a sensitivity analysis is conducted to measure the influence of private investors' minimum RoR on wind power's installed capacity and the transmission network's investment expenditure. In this regard, running the proposed robust TEP model, the total capacity of wind farms, and the investment cost of newly added lines for different values of the minimum RoR are determined and illustrated in Figure 7.…”

Section: B Robust Tepmentioning

confidence: 99%

“…In contrast, the RO technique is usually easier to understand and does not require exact information about uncertain parameters such as probability distribution functions. The RO technique models the uncertainties by defining parametric sets with inadequate information considering the lower and upper bounds of uncertain parameters; so that to find the best solution associated with the worst-case scenario in a settled interval [15,16].…”

Section: Introductionmentioning

confidence: 99%

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Developing a Robust Expansion Planning Approach for Transmission Networks and Privately-Owned Renewable Sources

et al. 2023

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Power system restructuring has changed transmission expansion planning (TEP) and caused many complications due to conflicting and contradictory objectives. The transmission capacity expansion would significantly affect the revenue of investor-owned renewable energy sources (RESs). Thus, the investment decisions on merchant RESs must be considered in the TEP studies conducted by the transmission system operator (TSO). In this regard, this paper aims to propose a multi-objective co-planning of investment in transmission networks and merchant RESs with three objective functions: minimizing the investment cost of newly deployed transmission lines, minimizing transmission congestion cost, and minimizing load curtailment in N-1 conditions. Moreover, the TSO guarantees a desirable rate of return for private investors to finance renewable energy projects. Further, a robust optimization (RO) technique is employed to cope with the uncertainties associated with demand and renewable energy production. Also, a posteriori multi-objective optimization algorithm, i.e., the non-dominated sorting genetic algorithm (NSGAII), is applied to solve the advanced optimization problem, followed by the fuzzy min-max method to acquire the final optimal solution. Finally, the IEEE RTS 24-bus test system is utilized to demonstrate the effectiveness and applicability of the suggested approach.

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Section: ∑ 𝑃mentioning

confidence: 99%

Section: B Robust Tepmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Developing a Robust Expansion Planning Approach for Transmission Networks and Privately-Owned Renewable Sources

et al. 2023

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“…The proposed algorithm managed to significantly lower the total parking lot peak load in 300 simulated scenarios, with a 50-70% decrease in most cases, and increased the utilization of the muchlowered peak power. Moreover, a new energy management model has been proposed to determine the optimal scheduling of an office building that includes EV charging piles, batteries, and rooftop photovoltaic systems while minimizing the total operation cost by employing the flexibility of building batteries and EV charging [42]. Another two-stage optimization technique has been proposed to determine the charging and discharging schedule for EVs participating in a vehicle-to-grid (V2G) program in an office building [43].…”

Section: Battery Capacitymentioning

confidence: 99%

Electric Vehicle Charging Facility Configuration Method for Office Buildings

et al. 2023

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With the advent of advanced battery technology, EVs are gradually gaining momentum. An appropriate decision-making method for the number of charging piles is in need to meet charging needs, and concurrently, to avoid the waste of infrastructure investment. In this study, an optimal charging pile configuration method for office building parking lots is proposed. With the determination of the design period of charging facilities, a charging load prediction model is established under a collection of charging scenarios. Taking the average utilization rate of charging facilities and the average satisfaction rate of charging demand as the objective functions, the distribution of the optimal number of piles is obtained with the genetic algorithm. The benefits of the configuration method are also explored under the building demand response process. The results show that the optimal configuration of charging piles in office buildings with different volumes have similar characteristics. When the design period is 5 years and 10 years, the comprehensive indicator of the utilization rate of the charging facilities and the satisfaction rate of the charging demand can, respectively, be improved by 8.18% and 17.45%. Moreover, the reasonable scheduling strategy can realize the load regulation response with a maximum load transfer rate of 25.55%.

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“…Moreover, the massive deployment of smart homes with small-scale DERs raises operational challenges. Thus, policymakers are rethinking to design of energy management mechanisms for more efficient integration of these types of resources into the distribution level of power systems [2], [3].…”

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confidence: 99%

Distributed Transactive Coordination of Residential Communities Aiming at Fulfilling Households’ Preferences

et al. 2022

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Transactive energy (TE) provides joint market and control functionality to manage distributed energy resources (DERs) in distribution networks. This work develops a real-time TE management framework that allows residential customers to actively join in the real-time transactive market with fulfilling households' preferences including comfort, economical energy consumption, and privacy-preserving. In this regard, first, a user-friendly algorithm is developed to calculate the real-time willingness to pay (bid) for electric vehicles (EVs) and heating, ventilation, and air conditioning (HVAC) units considering customers' preferences and concerns. Then, to preserve the privacy of households, the centralized market-clearing problem to maximize social welfare is decomposed into several subproblems using the alternating direction method of multipliers (ADMM) approach. Also, closed-form solutions to all subproblems are derived to simplify implementation and mitigate the computational complexity instead of solving optimization subproblems directly. This model is then implemented in a case study with several numbers of smart homes. The numerical results illustrate that the proposed distributed transactive model not only satisfies households' comfort preferences but also decreases the average charging cost of EV batteries by 40% compared to the uncontrolled charging model. Further, the results show that our proposed model significantly mitigates the computational burden of the transactive market clearing problem compared to the centralized approach and the distributed approach without closed-form solutions.

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Transactive charging management of electric vehicles in office buildings: A distributionally robust chance-constrained approach

Cited by 13 publications

References 38 publications

Developing a Robust Expansion Planning Approach for Transmission Networks and Privately-Owned Renewable Sources

Developing a Robust Expansion Planning Approach for Transmission Networks and Privately-Owned Renewable Sources

Electric Vehicle Charging Facility Configuration Method for Office Buildings

Distributed Transactive Coordination of Residential Communities Aiming at Fulfilling Households’ Preferences

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