The development of demand elasticity model for demand response in the retail market environment

Babar, Muhammad; Nguyen, Phuong H.; Ćuk, V.; Kamphuis, I.G.

doi:10.1109/ptc.2015.7232789

Cited by 25 publications

(26 citation statements)

References 8 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Suppliers or future market participants, such as an aggregator, can use historical data to estimate the effect of communicated prices on the power demand through price elasticity models on beforehand [7]. Another drawback with ToU pricing (or other linear pricing programs) is that the prices for the next day are known on beforehand, providing perfect knowledge about the future.…”

Section: Time Of Use Pricingmentioning

confidence: 99%

A cyber-physical systems perspective on decentralized energy management

Hoogsteen¹

View full text Add to dashboard Cite

Section: Time Of Use Pricingmentioning

confidence: 99%

A cyber-physical systems perspective on decentralized energy management

Hoogsteen¹

View full text Add to dashboard Cite

“…It has been found in [13] that price elasticity of demand can be successfully use for estimating agent's value-proposition (i.e., bid). Demand elasticity is defined as the change in demand ∂x k d,a at an interval k due to the change in the price ∂Γ k during the same interval.…”

Section: Energy Elasticity Learnermentioning

confidence: 99%

Energy Flexometer: Transactive Energy-Based Internet of Things Technology

et al. 2018

View full text Add to dashboard Cite

Effective Energy Management with an active Demand Response (DR) is crucial for future smart energy system. Increasing number of Distributed Energy Resources (DER), local microgrids and prosumers have an essential and real influence on present power distribution system and generate new challenges in power, energy and demand management. A relatively new paradigm in this field is transactive energy (TE), with its value and market-based economic and technical mechanisms to control energy flows. Due to a distributed structure of present and future power system, the Internet of Things (IoT) environment is needed to fully explore flexibility potential from the end-users and prosumers, to offer a bid to involved actors of the smart energy system. In this paper, new approach to connect the market-driven (bottom-up) DR program with current demand-driven (top-down) energy management system (EMS) is presented. Authors consider multi-agent system (MAS) to realize the approach and introduce a concept and standardize the design of new Energy Flexometer. It is proposed as a fundamental agent in the method. Three different functional blocks have been designed and presented as an IoT platform logical interface according to the LonWorks technology. An evaluation study has been performed as well. Results presented in the paper prove the proposed concept and design.

show abstract

“…As it is mentioned in Section 2.2, the appropriate demand elasticity model taking into account only the electrical energy price changes, has been proposed by Babar et al in [37] and extended in [4,67]. These extensions allow to implement in the model other important parameters changing in time (occupancy and number of persons in the room) and affecting the energy demand as well.…”

Section: An Event-based Control Strategy With a Demand Elasticity Modelmentioning

confidence: 99%

“…According to the problem formulation and developments of the demand elasticity model presented in [4,37], the demand elasticity has been defined as the change in demand at the given time interval due to the change in the electrical energy price during the same interval as well as other time intervals { ∈ ∶ ≠ }, and could be given mathematically as an elasticity coefficient: To tackle these challenges in practice, availability and real-time flow of data are pivotal for a proactive DSM mechanism in PMG. Therefore, the BACS with their event-driven control mechanisms as well as event-triggered control and monitoring functions are proposed in this paper to organize an active and flexible DSM platform.…”

Section: An Event-based Control Strategy With a Demand Elasticity Modelmentioning

confidence: 99%

“…This concept is supported by development of a demand elasticity model, implementing a market-based control mechanism (MCM), in which the DR and DSM programs of consumers or prosumers are traded as commodity in retail market. Since the introduction of smart energy meters and both mentioned earlier the ICT and the BACS advances have enabled the prosumers to bid easily against the energy at its disposal, the demand elasticity model presented in [37] and taking into consideration the electrical energy price changes, could be proposed to help in the development of future active RES control, energy manage and bidding mechanisms for BIPMG. An extended implementation of the demand elasticity model, including other important parameters (signals from the BACS representing events and affecting energy demand value, like the presence of persons-occupancy or number of persons in the room) in addition to the energy price has been presented and analyzed in [4].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

A New Concept of Active Demand Side Management for Energy Efficient Prosumer Microgrids with Smart Building Technologies

Ożadowicz

2017

Energies

View full text Add to dashboard Cite

Abstract:Energy efficient prosumer microgrids (PMGs) with active and flexible demand side management (DSM) mechanisms are considered to be crucial elements of future smart grids. Due to an increasing share of renewable energy and the growing power demand, appropriate tools to manage not only the loads but also small generation units, heating and cooling systems, storage units and electric vehicles should be provided for them. Therefore, this paper proposes an innovative approach to both physical and logical organization of an active DSM system for future building-integrated prosumer microgrids (BIPMGs), based on standard building automation and control systems (BACS) as well as Internet of Things (IoT) paradigm. New event-triggered control functions with developed universal, logical interfaces for open BACS and IoT network nodes are presented and their implementation in smart metering as well as fully integrated energy management mechanisms is analyzed. Finally, potential energy efficiency improvements with proposed BACS functions are discussed, based on BACS efficiency requirements defined in the EN 15232 standard.

show abstract

The development of demand elasticity model for demand response in the retail market environment

Cited by 25 publications

References 8 publications

A cyber-physical systems perspective on decentralized energy management

A cyber-physical systems perspective on decentralized energy management

Energy Flexometer: Transactive Energy-Based Internet of Things Technology

A New Concept of Active Demand Side Management for Energy Efficient Prosumer Microgrids with Smart Building Technologies

Contact Info

Product

Resources

About