Unlocking the value of flexibility of behind-the-meter prosumers: An overview of mechanisms to esteemed trends

Yazdani, Hassan; Doostizadeh, Meysam; Aminifar, Farrokh

doi:10.1016/j.tej.2022.107126

Cited by 4 publications

(3 citation statements)

References 36 publications

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“…In particular, short-term forecasts of behind-the-metre pure demand and generation, which cannot be measured directly, are essential for efficient local energy self-sufficiency, as they provide dominant information for optimising controllable DERs and power demand. For example, Yazdani et al [10] and Erdener et al [11] have discussed the significance of estimating and utilising behindthe-metre pure demand and generation. From the viewpoint of the distribution scale, Erdener et al [11] have suggested that forecasts of site-level behind-the-metre PV can be used for virtual power plant bidding and operation, and for operational forecasting of demand within a distribution service area.…”

Section: Introduction 1| Motivationmentioning

confidence: 99%

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Forecast of area‐scale behaviours of behind‐the‐metre solar power and load based on smart‐metering net demand data

et al. 2023

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Local energy self‐sufficiency, in which the supply and demand of electricity are controlled such that the generated power from distributed energy resources (DERs) is consumed locally based on a power supply‐and‐demand forecast, mitigates the burden on the power system and contributes to the efficient use of DERs in smart cities. However, widely available smart metres cannot measure behind‐the‐metre pure demand and generation from prosumers. Pure demand and generation forecasts without additional metering contribute to advanced supply‐and‐demand control in smart cities, including demand response. This study proposes a method of forecasting spatio‐temporal behaviours of behind‐the‐metre pure demand and generation by focussing on the information of net demand distribution observable from the smart metres; the proposed method initially predicts the spatio‐temporal net demand distribution with a combined forecaster based on the persistence and non‐parametric regression models, and then separately estimates the behind‐the‐metre pure demand and generation by using demand forecast result of neighbouring pure‐consumers extracted by considering the area‐scale behaviours of the smart metering data. The simulation results demonstrate that the proposed method provides accuracy comparable to forecasts conducted by directly measuring pure demand and generation, without requiring the installation of additional metres.

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Section: Introduction 1| Motivationmentioning

confidence: 99%

“…For example, Yazdani et al. [10] and Erdener et al. [11] have discussed the significance of estimating and utilising behind‐the‐metre pure demand and generation.…”

Section: Introductionmentioning

confidence: 99%

Forecast of area‐scale behaviours of behind‐the‐metre solar power and load based on smart‐metering net demand data

et al. 2023

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“…Among the existing markets apt for accommodating prosumers, peer‐to‐peer (P2P) trading has proven to be effective in pushing the operators and asset owners towards energy flexibility and emission reduction. By operating within this framework, prosumers can optimally manage their assets, power transactions, and ancillary services provisioning while gaining profit [3]. Lifting the regulatory barriers will transform the P2P trading concept from a pilot program to a commercial framework.…”

Section: Introductionmentioning

confidence: 99%

Forecast‐aided power and flexibility trading of prosumers in peer to peer markets

Yazdani

Doostizadeh

Aminifar

2022

IET Renewable Power Gen

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The ever‐evolving electricity distribution network calls for new effective, transparent and fair market procedures to be implemented. This paper offers a systematic framework for real‐time trading in prosumer communities. A data‐driven robust optimization model that deals with uncertainty is proposed using the flexibility requirement envelope concept. Using machine learning techniques, high quality point and quantile forecasts are prepared to form the envelope. Next, this data is fed into the optimization problem to match the peers and the distribution grid, trading power, and flexibility in a short‐term look‐ahead horizon. To increase the quality of forecasts, a clustering approach accompanied by a pattern recognition machine is proposed to determine the cluster to which the recently observed net‐load data belongs. To provide forecasts, a forecasting machine is developed using a hybrid of tree‐based ensemble learning models, which provides intuitive, robust, and accurate results. Finally, the peer matching is done in a decentralized fashion using the alternating direction method of multipliers (ADMM), while each agent calculates its battery storage aging cost. Case studies demonstrate the hybrid model's capability in providing high quality power and flexibility forecasts compared to single models and ARIMA models and its positive impact on reducing the overall cost of the system.

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Quantifying power system flexibility for the energy transition in Colombia

González-Dumar,

Arango-Aramburo,

Correa-Posada

2024

International Journal of Electrical Power & Energy Systems

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Unlocking the value of flexibility of behind-the-meter prosumers: An overview of mechanisms to esteemed trends

Cited by 4 publications

References 36 publications

Forecast of area‐scale behaviours of behind‐the‐metre solar power and load based on smart‐metering net demand data

Forecast of area‐scale behaviours of behind‐the‐metre solar power and load based on smart‐metering net demand data

Forecast‐aided power and flexibility trading of prosumers in peer to peer markets

Quantifying power system flexibility for the energy transition in Colombia

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