Impact of Plug-in Electric Vehicle on Residential Demand Side Management

Yadav, Mohini; Pandey, Nikhil; Jamil, Majid

doi:10.1109/parc49193.2020.236627

Cited by 2 publications

(1 citation statement)

References 14 publications

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“…A. Keyhani and B. Ramachandran [9] have extended the topic further by comparing the peak shaving effect under different EV participation levels. M. Yadav [10] has evaluated EVs' performance on shaping the residential load, which indicates that EVs can either perform as a cluster or perform independently in each household. The function of PV generation with DSM is also evaluated in some papers.…”

Section: Introductionmentioning

confidence: 99%

Demand Side Management Considering Household Appliances and EV

Dong

Jiang

Hai-ya

et al. 2022

2022 6th International Conference on Smart Grid and Smart Cities (ICSGSC)

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Combination of the information technology and the power engineering is the feature of next-generation grid. Depending on bidirectional communications, demand side management (DSM) aims at optimizing the electricity usage pattern of customers to improve energy efficiency and alleviate environmental impact. In this study, a DSM optimization algorithm is designed, which can perform load shifting on a household level based on the Time-of-Use strategy. Several flexible appliances, plug-in hybrid electric vehicle (EV) charging and rooftop photovoltaic (PV), are considered. Results show that the daily electricity cost has declined by 19% after the optimization. A 12% reduction of the domestic carbon emission is also achieved from the variation of grid carbon intensity and energy provided by rooftop PV. It is validated that with the growing penetration rate of EVs and renewable energy generation, smart scheduling of household load can greatly benefit grid stability and energy efficiency.

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Section: Introductionmentioning

confidence: 99%

Demand Side Management Considering Household Appliances and EV

Dong

Jiang

Hai-ya

et al. 2022

2022 6th International Conference on Smart Grid and Smart Cities (ICSGSC)

View full text Add to dashboard Cite

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Optimal Cooperative Power Management Framework for Smart Buildings Using Bidirectional Electric Vehicle Modes

et al. 2023

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The high potential for implementing demand management approaches across multiple objectives has been significantly enhanced. This study proposes a cooperative energy management strategy based on the end-user sharing of energy. The proposed method promotes the intelligent charging and discharging of EVs to achieve vehicle-to-anything (V2X) and anything-to-vehicle (X2V) operating modes for both integrated and nonrenewable residential applications. These sharing modes have already been discussed, but resolution approaches are applicable to a specific use case. Other application cases may require additional metrics to plan the fleet of electric vehicles. To avoid that problem, this study proposes the MIP method using a robust Gurobi optimiser based on a generic framework for cooperative power management (CPM). Moreover, the CPM ensures an overall target state of charge (SoC) at leaving time for all the vehicles without generating a rebound peak in total grid power, even without introducing photovoltaic power. Two different methods are proposed based on the flow direction of the EV power. The first method only includes the one-way power flow, while the second increases the two-way power flow between vehicles, operating in vehicle-to-vehicle or vehicle-to-loads modes. A thorough analysis of the findings of the proposed model was conducted to demonstrate the robustness and efficiency of the charging and discharging schedule of several EVs, favouring a sharing economy concept, reducing peak power, and increasing user comfort.

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Impact of Plug-in Electric Vehicle on Residential Demand Side Management

Cited by 2 publications

References 14 publications

Demand Side Management Considering Household Appliances and EV

Demand Side Management Considering Household Appliances and EV

Optimal Cooperative Power Management Framework for Smart Buildings Using Bidirectional Electric Vehicle Modes

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