Multiagent-Based Transactive Energy Management Systems for Residential Buildings With Distributed Energy Resources

Nizami, Mohammad Sohrab Hasan; Hossain, M. J.

doi:10.1109/tii.2019.2932109

Cited by 116 publications

(67 citation statements)

References 27 publications

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“…A consensus-based methodology is presented in [26] for p-p local markets. Multi-agent-based methodologies for local energy trading or sharing are also adopted in [27] and [28]. Many researchers concentrated on the P-P energy transactions pricing mechanism [29] such as social-welfarebased optimization approach [30], mid-market rate (MMR) method [17], and SDR approach [12].…”

Section: A Literaturementioning

confidence: 99%

“…Most studies focused on the cost minimization for the consumers, which can introduce rebound peaks. Coordinated methods or active transactive trading can solve this issue [18], [27], however, such methods require a coordinating entity to oversee the transaction mechanisms.…”

Section: A Literaturementioning

confidence: 99%

“…Therefore, it is expected that the proposed peak demand management will help consumers to reduce their electricity costs, and the utilities to maintain reliable operation of their system. The proposed method is compared with the existing literature [27], [13] and [28]. Authors in [27] proposed a multi-agent based system that prevent the rebound peaks.…”

Section: Case Studiesmentioning

confidence: 99%

“…The proposed method is compared with the existing literature [27], [13] and [28]. Authors in [27] proposed a multi-agent based system that prevent the rebound peaks. It involves both P-P trading among peers and transactive trading between prosumers and grid operator to prevent transformer overloading.…”

Section: Case Studiesmentioning

confidence: 99%

“…The key findings (only aggregated results for the LV feeder) of the paper are listed in Table IV. The proposed method is compared with the findings in Table II, III and IV, and listed in Table V. Ref [27] Ref [13] Ref [ The peak demand reduction is higher in [27], however, it only reduces peak demand beyond maximum transformer loading. Therefore, it does not reduce demand peaks when aggregated transformer load is below its maximum capacity.…”

Section: Case Studiesmentioning

confidence: 99%

See 4 more Smart Citations

Multiple Home-to-Home Energy Transactions for Peak Load Shaving

Mahmud

Nizami

Ravishankar

et al. 2020

IEEE Trans. on Ind. Applicat.

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This paper proposes a new technique to manage the domestic peak load demand through peer-to-peer (P-P) energy transaction among multiple homes. In this process, the houses willing to sell energy are identified as the Parent, and the houses that require energy are identified as a Child. The parents having energy resources such as photovoltaics (PV), battery storage and electric vehicles (EVs) will utilize their resources to meet their peak power demand and sell the extra energy to a child. A mixed integer linear programming optimization is used to find the parent-child matching based on their energy availability, power demand and distances. After selecting the parent-child match, the power demand of a child is forecasted using two different techniques, i.e. autoregressive moving average and artificial neural networks, to identify to child's need in a day ahead of the actual operation. The proposed algorithm calculates the available energy of a parent to sell in real-time and the required energy of a child in a day-ahead, while ensuring to minimize the peak load demand. The proposed method, as confirmed by the presented analysis using data of a real Australian power distribution network, is able to significantly minimize the peak load demand, which in-turn is expected to minimize the electricity costs. The method also facilitates two agreed prosumers to transact energy between themselves without the involvement of a third party.

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Section: A Literaturementioning

confidence: 99%

Section: A Literaturementioning

confidence: 99%

Section: Case Studiesmentioning

confidence: 99%

Section: Case Studiesmentioning

confidence: 99%

Section: Case Studiesmentioning

confidence: 99%

See 3 more Smart Citations

Multiple Home-to-Home Energy Transactions for Peak Load Shaving

Mahmud

Nizami

Ravishankar

et al. 2020

IEEE Trans. on Ind. Applicat.

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Transactive energy management for microgrids considering techno‐economic perspectives of utility – a review

Kumar

Jain

Sharma

2022

Intl J of Energy Research

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In a power system, distributed energy resources, including renewables, are advantageous for reducing power transmission losses and environmental pollution. However, increasing penetration of distributed renewable energy sources is challenging as they may pose security issues to the grid and centralized control of quantum number of such sources is quite impossible. Microgrid based distribution system is facilitating integration of distributed renewable energy sources as they can supply the local loads and reduce burden on the grid. Moreover, distributed control mechanism of different microgrids enhances the functioning efficiency of the grid. However, intermittent and uncertain nature of renewables leads into demand-supply imbalance in a microgrid. Networked microgrids is new concept where the energy sharing between the microgrids may encourage renewable integration and reduce demand-supply imbalance. In order to manage such energy sharing among the different components in a microgrid or different microgrids in a networked structure, an appropriate energy management approach is necessitated. Transactive energy is an emerging technology for energy management in the distribution system, which uses market mechanisms for energy management. This paper discusses various types of market structures and market clearing approaches in transactive energy framework for energy management. Moreover, techno-economic perspectives of utility in transactive energy trading, such as network constraints and network usage charges, are elaborated.Finally, this review details the challenges and future scope in the transactive energy management of microgrids and networked microgrids.

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CPS-Based Transactive Energy Technology for Smart Grids

Daneshvar

Asadi

2020

Cyber-Physical Systems in the Built Environment

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Multiagent-Based Transactive Energy Management Systems for Residential Buildings With Distributed Energy Resources

Cited by 116 publications

References 27 publications

Multiple Home-to-Home Energy Transactions for Peak Load Shaving

Multiple Home-to-Home Energy Transactions for Peak Load Shaving

Transactive energy management for microgrids considering techno‐economic perspectives of utility – a review

CPS-Based Transactive Energy Technology for Smart Grids

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