paper-with-me

Papers

LCOE-based Pricing for DLT-enabled Local Energy Trading Platforms

2022-01-24 · Marthe Fogstad Dynge, Ugur Halden, Gro Klæboe, Umit Cali

Support schemes like the Feed-in-Tariff (FiT) have for many years been an important driver for the deployment of distributed energy resources, and the transition from consumerism to prosumerism. This democratization and decarbonization of the energy system has led to both challenges and opportunities for the system operators, paving the way for emerging concepts like local energy markets. The FiT approach has often been assumed as the lower economic bound for a prosumer's willingness to participate in such markets but is now being phased out in several countries. In this paper, a new pricing mechanism based on the Levelized Cost of Electricity is proposed, with the intention of securing profitability for the prosumers, as well as creating a transparent and fair price for all market participants. The mechanism is designed to function on a Distributed Ledger Technology-based platform and is further set up from a holistic perspective, defining the market framework as interactions in a Cyber-Physical-Social-System. Schemes based on both fixed and variable contracts with the wholesale supplier are analyzed and compared with both the conventional FiT and to its proposed replacement options. The results show a cost reduction for the consumers and a slight loss in revenue for the prosumers compared to the FiT scheme. Comparing it to the actual suggested replacements to the FiT, however, it is clear that the pricing mechanism proposed in this study provides a substantial increase of benefits for both prosumers and consumers.

📄 PDF Abstract BibTeX arXiv:2201.09707

Code (0)

등록된 구현이 없습니다.

Tasks

energy trading

Similar Papers 제목 키워드 기반

Global LCOEs of decentralized off-grid renewable energy systems

2022-12-24 · Jann Michael Weinand, Maximilian Hoffmann, Jan Göpfert, Tom Terlouw 외

Recent global events emphasize the importance of a reliable energy supply. One way to increase energy supply security is through decentralized off-grid renewable energy systems, for which a growing number of case studies…

Incentive-Aligned Vehicle-to-Vehicle Energy Trading via Nash-Integrated Multi-Agent Reinforcement Learning

2026-05-21 · Yujin Lin, Yue Yang, Hao Wang arxiv

Vehicle-to-vehicle (V2V) energy trading enables decentralized peer-to-peer energy exchange among electric vehicles (EVs), reducing grid dependency while monetizing surplus capacity. However, coordinating self-interested …

Multi-agent Reinforcement Learning

Prospect Theory-inspired Automated P2P Energy Trading with Q-learning-based Dynamic Pricing

2022-08-26 · Ashutosh Timilsina, Simone Silvestri

The widespread adoption of distributed energy resources, and the advent of smart grid technologies, have allowed traditionally passive power system users to become actively involved in energy trading. Recognizing the fac…

energy tradingQ-Learning

VAE-GAN Based Price Manipulation in Coordinated Local Energy Markets

2025-07-26 · Biswarup Mukherjee, Li Zhou, S. Gokul Krishnan, Milad Kabirifar 외 arxiv

This paper introduces a model for coordinating prosumers with heterogeneous distributed energy resources (DERs), participating in the local energy market (LEM) that interacts with the market-clearing entity. The proposed…

Reinforcement Learning

Loss-aware Pricing Strategies for Peer-to-Peer Energy Trading

2025-03-30 · Varsha N. Behrunani, Philipp Heer, Roy S. Smith, John Lygeros

Peer-to-peer(P2P) energy trading may increase efficiency and reduce costs, but introduces significant challenges for network operators such as maintaining grid reliability, accounting for network losses, and redistributi…

energy trading