Stochastic optimization of energy hub operation with consideration of thermal energy market and demand response

Vahid-Pakdel, M.J.; Nojavan, Sayyad; Mohammadi‐Ivatloo, Behnam; Zare, Kazem

doi:10.1016/j.enconman.2017.04.074

Cited by 241 publications

(95 citation statements)

References 20 publications

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“…The study concludes that demand response has a similar effect to energy storage and thus demand response can be modeled as an equivalent energy storage unit. The optimal operation of integrated energy systems considering wind farms, electric heat storage systems, demand response, electricity market and thermal energy market is studied in [87]. A stochastic programming method is adopted to model the uncertainties of demands, market prices, wind speed, etc.…”

Section: Integrated Energy Systemsmentioning

confidence: 99%

From demand response to integrated demand response: review and prospect of research and application

Huang

Zhang

Chen

et al. 2019

Prot Control Mod Power Syst

216

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In the traditional power system demand response, customers respond to electricity price or incentive and change their original power consumption pattern accordingly to gain additional benefits. With the development of multienergy systems (MES) in which electricity, heat, natural gas and other forms of energy are coupled with each other, all types of energy customers are able to participate in demand response, leading to the concept of integrated demand response (IDR). In IDR, energy consumers can response not only by reducing energy consumption or opting for off-peak energy consumption but also by changing the type of the consumed energy. Taking the traditional demand response in power system as a starting point, the studies of the fundamental theory, framework design and potential estimation of demand response in power system are reviewed, and the practical cases and software development of demand response are introduced. Finally, the current theoretical research and application of IDR are assessed.

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Section: Integrated Energy Systemsmentioning

confidence: 99%

From demand response to integrated demand response: review and prospect of research and application

Huang

Zhang

Chen

et al. 2019

Prot Control Mod Power Syst

216

View full text Add to dashboard Cite

show abstract

“…The convergence of information and communications technologies (ICTs) with power system engineering allows new levels of automation. DSM in this context is usually formulated as optimization problems, which may be solved by various approaches [10][11][12][13][14][15][16][17]. These approaches are also moving towards a new paradigm where the consumer is the center of the grid and goes from being a passive element that only consumes to an active element involved in the management [18].…”

Section: Introductionmentioning

confidence: 99%

SwarmGrid: Demand-Side Management with Distributed Energy Resources Based on Multifrequency Agent Coordination

et al. 2018

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This paper focuses on a multi-agent coordination for demand-side management in electrical grids with high penetration rates of distributed generation, in particular photovoltaic generation. This coordination is done by the use of swarm intelligence and coupled oscillators, proposing a novel methodology, which is implemented by the so-call SwarmGrid algorithm. SwarmGrid seeks to smooth the aggregated consumption by considering distributed and local generation by the development of a self-organized algorithm based on multifrequency agent coordination. The objective of this algorithm is to increase stability and reduce stress of the electrical grid by the aggregated consumption smoothing based on a frequency domain approach. The algorithm allows not only improvements in the electrical grid, but also increases the penetration of distributed and renewable sources. Contrary to other approaches, this objective is achieved anonymously without the need for information exchange between the users; it only takes into account the aggregated consumption of the whole grid.

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“…Besides, the energy hub output side represents customers' demand, which can be a known quantity. The energy saving, low economic cost and higher energy efficiency have been presented at the same time through running whole system under optimum operation rules [6][7][8].…”

Section: Introductionmentioning

confidence: 99%

Modelling and Simulation of a Building Energy Hub

Bayod-Rújula

Yuan

Martínez-Gracia

et al. 2018

The 2nd International Research Conference on Sustainable Energy, Engineering, Materials and Environment

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The development of technologies such as efficient multi-generation system, lead to realizing the benefits of integrated energy infrastructure such as electricity, natural gas, and heating networks, and thus a rapid movement toward multi-energy systems (MES). In such systems, different energy carriers and systems interact together in a synergistic way. An Energy hub (EH) can be defined as the place where the production, conversion, storage and consumption of different energy carriers takes place, is a promising option for integrated management of MES. In this work we present the hourly Schedule along a year of a building energy hub, with local generation of heat and power, energy storage and electrical and thermal loads. We include PVT systems and a CHP system in the local generation of heat and power, and a gas boiler. A battery is considered as electrical storage and a water tank as thermal storage. The system is connected to the mail grids of power and gas. The typical thermal and electrical load of a building has been considered, with a heat pump that is considered as a deferral load. The model for all the components has been developed, and a yearly simulation has been carried out in which prices of electricity and gas have been considered.

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Stochastic optimization of energy hub operation with consideration of thermal energy market and demand response

Cited by 241 publications

References 20 publications

From demand response to integrated demand response: review and prospect of research and application

From demand response to integrated demand response: review and prospect of research and application

SwarmGrid: Demand-Side Management with Distributed Energy Resources Based on Multifrequency Agent Coordination

Modelling and Simulation of a Building Energy Hub

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