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Distributed energy resources (DERs), such as rooftop solar panels, are growing rapidly and are reshaping power systems. To promote DERs, feed-in-tariff (FIT) is usually adopted by utilities to pay DER owners certain fixed rates for…

Systems and Control · Electrical Eng. & Systems 2020-02-24 Zibo Zhao , Andrew L. Liu

In response to the growing uptake of distributed energy resources (DERs), community batteries have emerged as a promising solution to support renewable energy integration, reduce peak load, and enhance grid reliability. This paper presents…

Machine Learning · Computer Science 2023-12-07 Jiarong Fan , Hao Wang

Peer-to-peer energy trading is emerging as a new paradigm that in the near future may disrupt conventional electricity markets and heavily affect energy exchanges in networks of microgrids. In this paper, a preference mechanism is…

Systems and Control · Electrical Eng. & Systems 2019-09-17 Li Bai , Dimitri Thomopulos , Emanuele Crisostomi

We explore the use of deep reinforcement learning to provide strategies for long term scheduling of hydropower production. We consider a use-case where the aim is to optimise the yearly revenue given week-by-week inflows to the reservoir…

Machine Learning · Computer Science 2020-12-14 Signe Riemer-Sorensen , Gjert H. Rosenlund

The evolution of smart microgrid and its demand-response characteristics not only will change the paradigms of the century-old electric grid but also will shape the electricity market. In this new market scenario, once always energy…

Systems and Control · Computer Science 2017-04-24 Mosaddek Hossain Kamal Tushar , Chadi Assi

Unprecedented high volumes of data are becoming available with the growth of the advanced metering infrastructure. These are expected to benefit planning and operation of the future power system, and to help the customers transition from a…

High penetration of renewable energy source makes microgrid (MGs) be environment friendly. However, the stochastic input from renewable energy resource brings difficulty in balancing the energy supply and demand. Purchasing extra energy…

Systems and Control · Computer Science 2017-03-21 Zhenyu Qiao , Bo Yang , Qimin Xu , Fei Xiong , Cailian Chen , Xinping Guan , Bei Chen

Unfair pricing policies have been shown to be one of the most negative perceptions customers can have concerning pricing, and may result in long-term losses for a company. Despite the fact that dynamic pricing models help companies maximize…

Machine Learning · Computer Science 2018-03-28 Roberto Maestre , Juan Duque , Alberto Rubio , Juan Arévalo

Peer-to-peer energy trading offers a promising solution for enhancing renewable energy utilization and economic benefits within interconnected microgrids. However, existing real-time P2P markets face two key challenges: high computational…

Systems and Control · Electrical Eng. & Systems 2025-10-06 Kaidi Huang , Lin Cheng , Yue Zhou , Fashun Shi , Yufei Xi , Yingrui Zhuang , Ning Qi

This paper presents the power management of the nanogrid clusters assisted by a novel peer-to-peer(P2P) electricity trading. In our work, unbalance of power consumption among clusters is mitigated by the proposed P2P trading method. For…

Systems and Control · Electrical Eng. & Systems 2022-07-21 Sangkeum Lee , Hojun Jin , Luiz Felipe Vecchietti , Junhee Hong , Ki-Bum Park , Dongsoo Har

The power consumption of households has been constantly growing over the years. To cope with this growth, intelligent management of the consumption profile of the households is necessary, such that the households can save the electricity…

Optimization and Control · Mathematics 2020-06-30 Hwei-Ming Chung , Sabita Maharjan , Yan Zhang , Frank Eliassen

Optimizing the energy management within a smart grids scenario presents significant challenges, primarily due to the complexity of real-world systems and the intricate interactions among various components. Reinforcement Learning (RL) is…

Machine Learning · Computer Science 2025-10-21 Julen Cestero , Carmine Delle Femine , Kenji S. Muro , Marco Quartulli , Marcello Restelli

We introduce the use of reinforcement learning for indirect mechanisms, working with the existing class of sequential price mechanisms, which generalizes both serial dictatorship and posted price mechanisms and essentially characterizes all…

Computer Science and Game Theory · Computer Science 2021-05-07 Gianluca Brero , Alon Eden , Matthias Gerstgrasser , David C. Parkes , Duncan Rheingans-Yoo

Power grids are moving towards 100% renewable energy source bulk power grids, and the overall dynamics of power system operations and electricity markets are changing. The electricity markets are not only dispatching resources economically…

Machine Learning · Computer Science 2023-09-13 Milan Jain , Xueqing Sun , Sohom Datta , Abhishek Somani

The rise in renewable energy is creating new dynamics in the energy grid that promise to create a cleaner and more participative energy grid, where technology plays a crucial part in making the required flexibility to achieve the vision of…

Machine Learning · Computer Science 2024-03-28 Nicolas Mauricio Cuadrado , Roberto Alejandro Gutierrez , Martin Takáč

Due to the proliferation of renewable energy and its intrinsic intermittency and stochasticity, current power systems face severe operational challenges. Data-driven decision-making algorithms from reinforcement learning (RL) offer a…

Systems and Control · Electrical Eng. & Systems 2021-10-20 Alexander Pan , Yongkyun Lee , Huan Zhang , Yize Chen , Yuanyuan Shi

Traditional bulk load flexibility options, such as load shifting and load curtailment, for managing uncertainty in power markets limit the diversity of options and ignore the preferences of the individual loads, thus reducing efficiency and…

Systems and Control · Electrical Eng. & Systems 2021-12-20 Majid Majidi , Deepan Muthirayan , Masood Parvania , Pramod P. Khargonekar

The power grid is a complex and vital system that necessitates careful reliability management. Managing the grid is a difficult problem with multiple time scales of decision making and stochastic behavior due to renewable energy…

Artificial Intelligence · Computer Science 2016-03-08 Gal Dalal , Elad Gilboa , Shie Mannor

This paper presents an automated peer-to-peer (P2P) negotiation strategy for settling energy contracts among prosumers in a Residential Energy Cooperative (REC) considering heterogeneous prosumer preferences. The heterogeneity arises from…

Multiagent Systems · Computer Science 2018-10-24 Shantanu Chakraborty , Tim Baarslag , Michael Kaisers

A continuous rise in the penetration of renewable energy sources, along with the use of the single imbalance pricing, provides a new opportunity for balance responsible parties to reduce their cost through energy arbitrage in the imbalance…

Systems and Control · Electrical Eng. & Systems 2024-05-01 Seyed Soroush Karimi Madahi , Gargya Gokhale , Marie-Sophie Verwee , Bert Claessens , Chris Develder