Distributed Scalable Autonomous Market-Based Demand Response via Residential Plug-In Electric Vehicles in Smart Grids

Rassaei, Farshad; Soh, Wee-Seng; Chua, Kee-Chaing

doi:10.1109/tsg.2016.2629515

Cited by 60 publications

(27 citation statements)

References 26 publications

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“…The optimization problem must be solved with respect to several constraints associated with conventional generation units, network and wind power generation according to the load-generation balance constraint in the base case and the DC power flow equation is given in (8) and (9). The power transmission line congestion is one of the most important challenges in the operation of the wind power plant because the ISO could not schedule them so their power output usually leads to the ISO could not use the output of the other power plants.…”

Section: Solution Methodologymentioning

confidence: 99%

“…A practical solution to overcome the discussed challenges has been developed recently in the context of the autonomous DR (ADR) concept. ADR enables end-use consumers to automatically schedule their consumption based on price signals through appliance scheduling tools and also provides the possibility of information exchange with DR aggregators or load service entities (LSEs), simultaneously [8]. From this perspective, the end-use consumers can actively interact with DR aggregators or LSEs to plan their future demand.…”

Section: Aims and Motivationsmentioning

confidence: 99%

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Multi-Objective Market Clearing Model with an Autonomous Demand Response Scheme

et al. 2019

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Demand response (DR) is known as a key solution in modern power systems and electricity markets for mitigating wind power uncertainties. However, effective incorporation of DR into power system operation scheduling needs knowledge of the price–elastic demand curve that relies on several factors such as estimation of a customer’s elasticity as well as their participation level in DR programs. To overcome this challenge, this paper proposes a novel autonomous DR scheme without prediction of the price–elastic demand curve so that the DR providers apply their selected load profiles ranked in the high priority to the independent system operator (ISO). The energy and reserve markets clearing procedures have been run by using a multi-objective decision-making framework. In fact, its objective function includes the operation cost and the customer’s disutility based on the final individual load profile for each DR provider. A two-stage stochastic model is implemented to solve this scheduling problem, which is a mixed-integer linear programming approach. The presented approach is tested on a modified IEEE 24-bus system. The performance of the proposed model is successfully evaluated from economic, technical and wind power integration aspects from the ISO viewpoint.

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Section: Solution Methodologymentioning

confidence: 99%

Section: Aims and Motivationsmentioning

confidence: 99%

Multi-Objective Market Clearing Model with an Autonomous Demand Response Scheme

et al. 2019

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“…One the contrary, market designs with game theory-based models, auction theory-based models and simulation models are more scalable, which could be applied for markets where huge number of players are participating in. Rassaei et al [149] proposed a distributed game theory-based method for managing large number of EVs' participations in energy markets. The scalability of proposed method was proved.…”

Section: Comparisonsmentioning

confidence: 99%

Local flexibility markets: Literature review on concepts, models and clearing methods

2020

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“…We believe that minimizing and even elimination of the share of GHGs emissions arising from the transportation and the power generation sectors will be possible in the long run by further utilizing renewables, electro mobility and proper DDR techniques. Besides, the emissions from power generators could be reduced in smart grids wherein there is high penetration of renewables and distributed generation (DG) [21].…”

Section: Green Transportationmentioning

confidence: 99%

Environmental benefits of modern power system and clean energy

et al. 2019

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Nowadays, the world is at a critical moment of facing serious environmental and economic problems. A very large number of people in developing countries is exposed to dangers associated with flammability and toxicity of traditional source of energy while others in industrialized countries are facing the effects of atmospheric air pollution and green house (GHG) gas emission .Despite the global reforestation policies, despite latest remarkable increase in renewable energy and natural gas production, there is still a problem of domination fuel and coal consumption. This paper explored the effects of rapid economic growth, industrial development on climate. Additionally the effects of continuous exponential population growth, a fast increase of energy global energy demand, conventional transport system on carbon and GHG emission have discussed. Finally the paper revealed how modern smart electricity system with sustainable energy system and electric transport system contribute to the reduction of hazardous emission.

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Distributed Scalable Autonomous Market-Based Demand Response via Residential Plug-In Electric Vehicles in Smart Grids

Cited by 60 publications

References 26 publications

Multi-Objective Market Clearing Model with an Autonomous Demand Response Scheme

Multi-Objective Market Clearing Model with an Autonomous Demand Response Scheme

Local flexibility markets: Literature review on concepts, models and clearing methods

Environmental benefits of modern power system and clean energy

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