A Novel Methodology for Predicting Potential Responsiveness in Residential Demand

Davarzani, Sima; Pisică, Ioana; Taylor, Gregory P.

doi:10.1049/cp.2017.0326

Cited by 4 publications

(5 citation statements)

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“…Tumble Dryer (TD). The model of each controllable appliance is described in [34]. The total loads l ",$ at a given time t can be defined as a set of aggregated loads as follows:…”

Section: A Home Agentmentioning

confidence: 99%

“…Using the methodology introduced in [34], the probability of using an appliance sh, at a timeslot t was estimated as a variable K,L MK for different clusters of households, similar to the approach presented in [34]. The proposed methodology has considered the appliance ownership, frequency usage, household characteristics as well as technical aspects of operating an appliance, such as energy constraints, in predicting the K,L MK within each cluster.…”

Section: Mkmentioning

confidence: 99%

“…The role of each LTA is limited to sending the information regarding the available flexible loads from the associated HAs to DRPA through DSPA. Using the approach in [34], the available flexible demand from HAs over time is estimated. Since one operating appliance sh is considered at each given timeslot, the probability of maximum shiftable appliances from each HA is averaged.…”

Section: B Local Transformer Agentmentioning

confidence: 99%

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Implementation of a novel multi-agent system for demand response management in low-voltage distribution networks

2019

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In this era of advanced distribution automation technologies, demand response is becoming an important tool for electricity network management. The available flexible loads can efficiently help in alleviating the network constraints and achieving demand-supply balance. Therefore, this forms the rationale behind this paper, which aims to implement a multi-agent system framework in order to achieve flexible price-based demand response. A genetic algorithm-based multi-objective optimization technique is applied to determine the optimal locations and the amount of required demand reduction in order to keep the network within statutory limits. The methodology is based on probabilistic estimation of the granularity of total available flexible demand from shiftable home appliances in each low-voltage feeder. Moreover, an optimal decision making for the start time of appliances upon receiving a real-time price signal is proposed. This is accomplished by considering the willingness to participate as well as price demand elasticity of the different clusters of customers. To fully demonstrate the feasibility and effectiveness of the proposed framework, a modified IEEE 69 bus distribution network comprising 1824 low voltage residential customers has been implemented and analyzed.

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“…Tumble Dryer (TD). The model of each controllable appliance is described in [34]. The total loads l ",$ at a given time t can be defined as a set of aggregated loads as follows:…”

Section: A Home Agentmentioning

confidence: 99%

Section: Mkmentioning

confidence: 99%

Section: B Local Transformer Agentmentioning

confidence: 99%

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Implementation of a novel multi-agent system for demand response management in low-voltage distribution networks

2019

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“…Generally, the aim of demand response programs can be categorised as load shedding which refers to overall load reduction overt time and load shifting which encourages customers to shift their power usage to nonpeak periods. We have used the proposed methodologies in [11] and [12] in order to find the probability of shifting/shedding demand and consequently the available DR from each cluster of customers during a typical day.…”

Section: Potential Of Demand Responsivenessmentioning

confidence: 99%

Novel model for defining electricity tariffs using residential load profile characterisation

Davarzani

Pisică

Lipan

2018

IJRET

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In recent years, great attention towards enabling future smart grid functionalities in distribution networks creates significant changes in electricity load profiles. These changes require a new advanced paradigm in electricity pricing and tariffs definition aiming to increase the potential of responsiveness demand. This paper aims to propose a new model for designing residential electricity tariffs using their load profile clustering and characterization, taking into account social, technical and educational factors alongside the financial incentives. The methodology is based on estimation of the potential of demand responsiveness to dynamic pricing over time for different cluster of households with similar electricity consumption patterns. In this regard, different time of use pricing bands has been considered and compared with fixed price tariffs. Moreover, a baseline demand for each cluster of households has been determined based on the elasticity of demand to different static tariffs. The results show that the proposed model can provide distribution network operators (DNOs) and suppliers with a basic and general outline of defining more effective dynamic pricing schemes that reflect intermittent nature of residential demand.

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“…Moreover, it predicts the expected demand and estimates the potential of demand responsiveness during DR event for each group of customers. The detailed process of calculation DR potential and clustering has been discussed further in section III and [10]. ...…”

Section: Dr Algorithm and Agents Behaviuoursmentioning

confidence: 99%

Development of a novel multi-agent system for residential voltage control using demand response based on customer behaviour

Davarzani

Pisică

2017

2017 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe)

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Aggregation of demand during peak load periods can cause local overloading in distribution networks. Quantifying the available peak demand reduction at a local level enables flexible and dynamic management of variable power flows on a distribution network. Since domestic loads coupled with distributed generation are intermittent and uncertain in nature, a detailed analysis of domestic load profiles is an essential step to achieve flexible demand response. This paper introduces and develops a novel multiagent system approach to provide domestic demand response over time. This new approach is based on customer elasticity when considering different parameters including social, technical and financial aspects of customer behaviour .

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A Novel Methodology for Predicting Potential Responsiveness in Residential Demand

Cited by 4 publications

References 0 publications

Implementation of a novel multi-agent system for demand response management in low-voltage distribution networks

Implementation of a novel multi-agent system for demand response management in low-voltage distribution networks

Novel model for defining electricity tariffs using residential load profile characterisation

Development of a novel multi-agent system for residential voltage control using demand response based on customer behaviour

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