An internal pricing method for a local energy market with P2P energy trading
Through facilitating direct energy transfer between producers and consumers and lowering intermediary expenses, peer-to-peer (P2P) energy trading presents notable advantages for individual prosumers. Moreover, peer-to-peer trading permits proactive consumers to economically conduct their energy tran...
Saved in:
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-03-01
|
| Series: | Energy Strategy Reviews |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2211467X25000367 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Summary: | Through facilitating direct energy transfer between producers and consumers and lowering intermediary expenses, peer-to-peer (P2P) energy trading presents notable advantages for individual prosumers. Moreover, peer-to-peer trading permits proactive consumers to economically conduct their energy transactions, taking advantage of an equitable pricing mechanism within microgrids. In this study, an internal pricing model in a market integrated with P2P energy trading has been proposed. In this regard, in the first step, the market structure consisting of three blocks of members was modeled: block A including prosumers with photovoltaic (PV) and energy storage, block B with prosumers only equipped with PV systems, and finally block C including energy consumers. Market members manage P2P energy trade through a Local Market Organizer (LMO). Besides, in the second step, an energy pricing model is proposed in the P2P market based on the supply-demand ratio (SDR). The problem was implemented and solved in the form of a Mixed-Integer Non-Linear Programming (MINLP) model in GAMS, where its final goal was to minimize the total costs of the market members. The results showed that by switching from peer-to-grid (P2G) to P2P mode, the cost of peers decreased around 8 % in summer day and almost 2 % in winter day. The accuracy and robustness of the proposed pricing method was validated with a typical pricing method. So that the difference of the objective function values in two pricing methods was only 0.26 and 0.09 % in summer and winter day, respectively. |
|---|---|
| ISSN: | 2211-467X |