Optimal Day-Ahead Scheduling and Operation of the Prosumer by Considering Corrective Actions Based on Very Short-Term Load Forecasting

Jamal Faraji,Miadreza Shafie-Khah,Hamed Hashemi-Dezaki,Abbas Ketabi,Joao P S Catalao

doi:10.1109/access.2020.2991482

Jamal Faraji, Miadreza Shafie-Khah + Show 3 more

Open Access

https://doi.org/10.1109/access.2020.2991482

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Abstract

Energy management systems (EMSs) play an important role in the optimal operation of prosumers. As an essential segment of each EMS, the load forecasting (LF) block enhances the optimal utilization of renewable energy sources (RESs) and battery energy storage systems (BESSs). In this paper, a new optimal day-ahead scheduling and operation of the prosumer is proposed based on the two-level corrective LF. The proposed two-level corrective LF actions are developed through a very precise short-term LF. In the first level, a time-series LF is applied using multi-layer perceptron artificial neural networks (MLP-ANNs). In order to improve the accuracy of the forecasted load data at the first level, the second level corrective LF is applied using feed-forward (FF) ANNs. The second stage prediction is initiated when the LF results violate the pre-defined criteria. The proposed method is applied to a prosumer under different cases (based on the consideration of BESS operation behaviors and cost) and various scenarios (based on the accuracy of the load data). The obtained optimal day-ahead operation results illustrate the advantages of the proposed method and its corrective forecasting process. The comparison of the obtained results and those of other available ones show the effectiveness of the proposed optimal operation of the prosumers. The advantages of the proposed method are highlighted while the BESS costs are considered.

Highlights

Electric power systems and energy markets are facing changes such as redesigning and restructuring due to the utilization of renewable energy sources (RESs) and the deployment of communication technologies (blockchain, big data, and internet of things (IOTs))
OPTIMAL OPERATION RESULTS BASED ON THE PROPOSED TWO-LEVEL load forecasting (LF) UNDER VARIOUS CASES AND SCENARIOS The selected system for applying the proposed optimal operation has been assumed to be equipped with RESs and battery energy storage systems (BESSs)
Electricity price is considered according to south Korean electricity tariff, which is based on time-of-use (TOU) pricing [28]

Summary

Introduction

Electric power systems and energy markets are facing changes such as redesigning and restructuring due to the utilization of renewable energy sources (RESs) and the deployment of communication technologies (blockchain, big data, and internet of things (IOTs)). The formation of prosumers in emerging energy markets is another critical change in conventional power systems. The clean energy package by the European Union discussed the rules for prosumers in energy markets and let active consumers produce electricity as well as electricity sales [5]. In such energy markets, the heart of the system is consumers. The heart of the system is consumers They would be able to generate electricity by RESs and get their profits by selling the amount of produced electricity [6]. Due to low feed-in-tariffs (FiT), prosumers may not enjoy the ideal economic benefits of the market [7]

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Conclusion