[Paper Review] Exchange of Renewable Energy among Prosumers using Blockchain with Dynamic Pricing

Arnob Ghosh, Vaneet Aggarwal+1 more|arXiv (Cornell University)|Apr 22, 2018

Smart Grid Energy Management18 references18 citations

TL;DR

This paper proposes a blockchain-based dynamic pricing mechanism for peer-to-peer energy trading among prosumers—households with solar panels and storage—using a game-theoretic model to achieve optimal energy exchange. The platform sets dynamic exchange prices to minimize conventional grid energy use, and a distributed algorithm converges to a unique generalized Nash equilibrium, reducing peak load and improving social welfare by up to 25% compared to non-trading scenarios.

ABSTRACT

We consider users which may have renewable energy harvesting devices, or distributed generators. Such users can behave as consumer or producer (hence, we denote them as prosumers) at different time instances. A prosumer may sell the energy to other prosumers in exchange of money. We consider a demand response model, where the price of conventional energy depends on the total demand of all the prosumers at a certain time. A prosumer depending on its own utility has to select the amount of energy it wants to buy either from the grid or from other prosumers, or the amount of excess energy it wants to sell to other prosumers. However, the strategy, and the payoff of a prosumer inherently depends on the strategy of other prosumers as a prosumer can only buy if the other prosumers are willing to sell. We formulate the problem as a coupled constrained game, and seek to obtain the generalized Nash equilibrium. We show that the game is a concave potential game and show that there exists a unique generalized Nash equilibrium. We consider that a platform will set the price for distributed interchange of energy among the prosumers in order to minimize the consumption of the conventional energy. We propose a distributed algorithm where the platform sets a price to each prosumer, and then each prosumer at a certain time only optimizes its own payoff. The prosumer then updates the price depending on the supply and demand for each prosumer. We show that the algorithm converges to an optimal generalized Nash equilibrium. The distributed algorithm also provides an optimal price for the exchange market.

Motivation & Objective

• To address the challenge of uncertain renewable energy supply and peak demand in power grids by enabling direct energy exchange among prosumers.
• To design a dynamic, real-time pricing mechanism that reduces reliance on conventional grid energy and minimizes peak load.
• To model prosumer behavior as a strategic game where each prosumer optimizes self-interest while accounting for others’ actions.
• To develop a distributed algorithm that enables convergence to a generalized Nash equilibrium without requiring full knowledge of others’ utilities.
• To demonstrate that energy exchange via dynamic pricing significantly improves social welfare and system efficiency.

Proposed method

• Formulates the energy exchange problem as a coupled constrained game with a generalized Nash equilibrium framework.
• Models the system as a concave potential game, ensuring existence and uniqueness of the equilibrium.
• Introduces a dynamic pricing mechanism where a central platform adjusts exchange prices based on supply and demand across prosumers.
• Proposes a distributed algorithm where each prosumer optimizes its own energy strategy (buy, sell, store) based on current prices and prior actions.
• Uses a linear price function for conventional energy that depends on total system demand, reflecting real-time grid pricing.
• Employs iterative price updates by the platform, ensuring convergence to the optimal equilibrium and minimizing conventional energy consumption.

Experimental results

Research questions

• RQ1 How can dynamic pricing be designed to incentivize prosumers to trade excess renewable energy among themselves while minimizing conventional grid usage?
• RQ2 What game-theoretic equilibrium structure emerges when prosumers act selfishly but are interdependent in supply and demand?
• RQ3 Can a distributed algorithm converge to the optimal generalized Nash equilibrium without requiring global knowledge of prosumer utilities?
• RQ4 How does the inclusion of a local energy exchange market affect overall system efficiency and social welfare compared to a centralized grid-only model?
• RQ5 What is the impact of varying the conventional energy price parameter on social welfare and peak load reduction?

Key findings

• The proposed game admits a unique generalized Nash equilibrium due to the existence of a concave potential function.
• The distributed algorithm converges to the optimal generalized Nash equilibrium, enabling efficient and scalable energy trading.
• The exchange market reduces conventional energy consumption and peak load, with social welfare improved by at least 25% compared to scenarios without peer-to-peer trading.
• When storage capacity increases, the benefit of exchange is most pronounced, but diminishes beyond a threshold as prosumers become self-sufficient.
• The optimal exchange price is dynamically set by the platform based on real-time supply and demand, leading to reduced grid dependency.
• The social welfare remains higher with exchange for all values of the conventional energy price parameter γt, especially when γt is low, indicating strong market efficiency.