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A Motivational Game-Theoretic Approach for Peer-to-Peer Energy Trading in the Smart Grid
Wayes Tushar, Tapan Kumar Saha, Chau Yuen, Thomas Morstyn, Malcolm D. McCulloch, H. Vincent Poor, Kristin L. Wood
TL;DR
The paper asks how prosumers can be encouraged to participate sustainably in trustless P2P energy trading. It applies motivational psychology and cooperative game theory to design and assess a trading scheme, finding that the coalition is stable and the outcomes satisfy the discussed motivational models.
Problem
Existing studies address trading design but leave open how to create prosumer-centric community trading that ensures widespread and sustainable engagement without a central controller.
Method
The paper introduces a motivational psychology framework and uses cooperative game theory to design a P2P energy-trading scheme, then studies its properties and numerical cases.
Results
The developed scheme has a stable coalition, and its outcomes satisfy all discussed motivational psychology models.
Takeaways & Limitations
Game theory is presented as a strong candidate for modeling P2P trading when prosumer participation is a concern.
Abstract
from arXiv · showhide
Peer-to-peer trading in energy networks is expected to be exclusively conducted by the prosumers of the network with negligible influence from the grid. This raises the critical question: how can enough prosumers be encouraged to participate in peer-to-peer trading so as to make its operation sustainable and beneficial to the overall electricity network? To this end, this paper proposes how a motivational psychology framework can be used effectively to design peer-to-peer energy trading to increase user participation. To do so, first, the state-of-the-art of peer-to-peer energy trading literature is discussed by following a systematic classification, and gaps in existing studies are identified. Second, a motivation psychology framework is introduced, which consists of a number of motivational models that a prosumer needs to satisfy before being convinced to participate in energy trading. Third, a game-theoretic peer-to-peer energy trading scheme is developed, its relevant properties are studied, and it is shown that the coalition among different prosumers is a stable coalition. Fourth, through numerical case studies, it is shown that the proposed model can reduce carbon emissions by 18.38% and 9.82% in a single day in Summer and Winter respectively compared to a feed-in-tariff scheme. The proposed scheme is also shown to reduce the cost of energy up to 118 cents and 87 cents per day in Summer and Winter respectively. Finally, how the outcomes of the scheme satisfy all the motivational psychology models is discussed, which subsequently shows its potential to attract users to participate in energy trading.
I. INTRODUCTION
The paper addresses the challenge of sustaining prosumer participation in trustless P2P energy trading by applying motivational psychology to scheme design. It combines a literature review, motivational framework, cooperative game-theoretic design, and numerical validation.
- Motivation: Widespread DER benefits depend on extensive prosumer participation, making sustainable engagement a central energy-market requirement.The paper emphasizes prosumer-centric techniques that demonstrate participation benefits and avoid inefficient outcomes associated with disengagement.
- Motivation: P2P energy trading can let prosumers buy surplus energy from peers and earn more from excess generation than under FiT.The approach is presented as a decentralized alternative with potential benefits for both buyers and sellers.
- Research gap: Existing P2P studies address trading algorithms, prices, incentives, network constraints, and business contracts, but leave prosumer-centric sustainable engagement insufficiently addressed.The stated gap concerns designing community trading that encourages peers to trust and cooperate without a central controller.
- Contributions: Motivational psychology is introduced as a design tool for encouraging extensive prosumer participation in P2P energy trading.The framework is intended to connect motivational models with the design of energy-trading schemes.
- Contributions: A systematic classification reviews existing P2P energy-trading literature, while numerical case studies corroborate whether the developed scheme satisfies the motivational models.The paper also positions these analyses within a broader review of current research and ongoing pilot projects.
- Contributions: Cooperative game theory is used to design a P2P trading scheme whose properties are studied and whose coalition stability is validated.The outcomes are then compared with motivational models to assess whether the scheme has the potential to support widespread participation.
II. PRELIMINARIES
This section introduces P2P energy networks and motivational psychology as concepts that can be integrated to design sustainable, prosumer-centric energy trading.
- II. PRELIMINARIES: The section provides a detailed overview of P2P energy networks and motivational psychology.Its objective is to establish how the two concepts could potentially be integrated for future scheme design.
- II. PRELIMINARIES: The section is intended to give readers a clear understanding of the relationship between these concepts.
- II. PRELIMINARIES: The intended integration targets a sustainable, prosumer-centric P2P energy trading scheme.The passage frames this as a potential direction for future design.
A. P2P Energy Network
A P2P energy network enables members to share energy-related resources and information directly, using virtual trading and physical transfer layers. Its literature is organized into three broad categories based on prosumer interaction.
- Network definition: The network supports direct peer communication and can add or remove peers without changing its operational structure.
- Network definition: A P2P energy network lets members share resources and information to pursue objectives such as renewable-energy maximization, cost reduction, and peak-load shaving.Members may act as providers, receivers, or both.
- Virtual energy trading layer: The virtual layer operates as a local electricity market where peers exchange resource type, amount, and unit price, then match orders and complete payment.A secured information system provides equal access, while smart-meter data supports order creation.
- Physical energy transfer layer: The physical layer is a distribution grid that transfers electricity between peers after virtual-layer transactions initiate renewable-energy delivery.It may use a traditional distribution network, a separate microgrid, or both.
- Literature classification: Existing P2P energy-trading literature is divided into three general categories according to how prosumers interact over the network.The supplied passage introduces the classification but does not enumerate all three categories.
1) Microgrid-to-Microgrid energy trading:
Microgrid-to-microgrid P2P trading mechanisms address supply-demand mismatch and can reduce bills while supporting smoother power flows and more resilient grid operation.
- 1) Microgrid-to-Microgrid energy trading:: Microgrid-to-microgrid mechanisms handle energy supply-demand mismatch by improving renewable-resource utilization.
- 1) Microgrid-to-Microgrid energy trading:: These mechanisms can reduce electricity bills for participating microgrids through P2P energy trading.
- 1) Microgrid-to-Microgrid energy trading:: P2P trading can smooth microgrid power generation by regulating grid power flow despite stochastic load demand.
- 1) Microgrid-to-Microgrid energy trading:: Security-aware P2P trading supports distributed energy resources and flexible demands for a more resilient grid in normal and emergency conditions.
- 1) Microgrid-to-Microgrid energy trading:: The passage identifies an example study in this category without describing its specific mechanism or findings.
2) Intra-microgrid P2P energy trading:
Intra-microgrid P2P energy-trading studies address energy exchange within microgrids through differentiated products, financial allocation, demand response, battery optimization, and network-aware analysis.
- P2P energy may be treated as a heterogeneous product whose value depends on generation technology, network location, and owner reputation.
- Existing studies include consensus-based trading with product differentiation and price-based demand response for microgrid energy sharing.
- Battery-system optimization and sensitivity analysis have been used to optimize rooftop-solar use and assess whether P2P transactions violate network constraints.
- Table I summarizes different types of P2P energy-trading schemes available in the literature.
III. OVERVIEW OF A MOTIVATIONAL PSYCHOLOGY SUPPORTED P2P ENERGY TRADING
The proposed framework considers grid-connected households with rooftop solar and no batteries that exchange electricity as peers while retaining grid interaction when P2P trading leaves surplus or deficiency. Because this interaction is strategic, the scheme is developed using game theory.
- The framework targets P2P energy-trading outcomes that satisfy motivational psychology models.
- The scenario consists of community households connected to the grid through grid-connected solar systems without batteries.
- Households traditionally trade with the grid through a feed-in-tariff scheme, but in a P2P network they exchange electricity with one another as peers.
- After P2P trading, households may still interact with the grid if they have remaining energy surplus or deficiency.
- The interactive trading process motivates using a game-theoretic approach to develop the P2P trading scheme.
1) Non-cooperative game:
The paper distinguishes non-cooperative and cooperative games, then uses a canonical coalition game to study whether prosumers can form and maintain a stable trading coalition. Stability requires incentives that prevent prosumers from leaving.
- Non-cooperative game: A non-cooperative game models independent players with potentially conflicting interests whose decisions affect the outcome.
- Non-cooperative game: Static non-cooperative games involve one action per player, whereas dynamic games involve repeated actions and greater information about other players’ choices.
- Non-cooperative game: The Nash equilibrium is a stable action vector from which no player benefits by unilaterally deviating given the other players’ actions.
- Cooperative game: The canonical coalition-game framework studies grand-coalition stability, coalition gains, and fair gain distribution.
- Cooperative game: P2P trading is modeled as prosumers cooperating to pursue global objectives such as reducing CO2 emissions and local objectives such as reducing electricity costs.
- Cooperative game: The grand coalition is stable when its core is non-empty and each prosumer’s revenue allocation provides no incentive to leave.
- Cooperative game: For P2P energy trading, stability additionally requires a superadditive coalition value function and revenues for each prosumer that lie within the core.
2) Development of the trading scheme:
The trading scheme models rooftop-solar prosumers as sellers or buyers in a canonical coalition game, with P2P exchanges prioritized before residual interaction with the central power station. A mid-market-rate mechanism sets the trading price between grid buying and selling prices.
- The assumed network contains rooftop-solar prosumers without batteries connected to a central power station and linked through secure smart-meter communication.
- Each prosumer has solar surplus or energy deficiency; surplus is sold to peers first, while deficiency is bought from peers first.
- After peer exchanges, prosumers sell remaining excess to or buy remaining deficient energy from the central power station when necessary.
- The canonical coalition game defines sellers, buyers, and the coalition value as the monetary benefit prosumers achieve from P2P participation.
- The coalition value function is concave and superadditive, supporting the stability condition used for the trading game.
- The mid-market-rate mechanism sets P2P prices between the grid’s buying and selling prices, which can motivate prosumers to trade with one another.
- Figure 5 specifies the P2P price range as [pg,b, pg,s], with grid prices chosen according to electricity prices in Brisbane, Australia.
3) Setting trading price through mid-market rate:
The proposed scheme sets P2P prices using the mid-market rate across scenarios defined by the balance between surplus energy and demand. Its pricing and coalition properties support cooperation while the evaluation emphasizes prosumer cost and CO2 benefits.
- Trading scenarios: The scheme considers scenarios based on whether total surplus energy is zero, exceeds demand, or is insufficient to meet demand.These cases determine whether prosumers trade among themselves, sell residual energy to the CPS, or require CPS energy.
- Mid-market pricing: When surplus equals demand, prosumers need not trade with the CPS, and both P2P prices equal the average of grid selling and buying prices.The mid-market rate is expressed as ps = pb = (pg,s + pg,b)/2.
- Trading scenarios: When surplus exceeds demand, prosumers meet peer demand and sell remaining energy to the CPS, while the buying price remains as in Scenario 1.The selling price changes because surplus energy is also sold to the CPS.
- Coalition stability: The developed scheme ensures a stable coalition because its value function is concave and superadditive, giving the canonical coalition game a non-empty core.This supports stable revenue distributions among participating prosumers.
- Coalition stability: Mid-market pricing gives buyers a price below the grid selling price and sellers a price above the grid buying price, keeping allocations within the game core.The resulting incentives make prosumers interested in cooperating in P2P trading.
- Scope of evaluation: The analysis focuses on prosumer cost and CO2 reduction rather than all P2P objectives because those two benefits are used to encourage participation.CO2 reduction is treated as resulting from renewable-energy use rather than analyzed as a separate objective.
C. How the proposed energy trading scheme can psychologically motivate prosumers
The paper evaluates whether the proposed P2P scheme can motivate prosumers through economic and environmental benefits using solar and residential-demand data. Compared with FiT, the scheme consistently reduces costs and CO2 during the evaluated scenarios, supporting the motivational framework and potential participation.
- Simulation setup: The numerical study uses publicly available solar-generation and residential-demand data for a grid-tied system without storage, comparing the proposed scheme with FiT.Each residential consumer is assumed to have a 3 kWp solar panel, with 15-minute data recorded in December 2013.
- Economic benefits: The study considers five prosumers and measures their savings from P2P trading against an FiT scheme in Summer and Winter.Table II reports the savings available to each participating prosumer.
- Economic benefits: P2P consistently lowers prosumer energy costs relative to FiT across the evaluated Summer and Winter cases.The paper reports average cost reductions of 6.8%, 6.6%, 6.3%, 5.2%, 4%, 6.1%, and 3.9% across different days.
- Environmental benefits: During sunshine hours, P2P improves CO2 performance, but without storage it cannot outperform FiT outside sunshine hours.CO2 production is the same for both schemes outside sunshine hours.
- Environmental benefits: P2P trading reduces CO2 production by 18.38% in Summer and 9.82% in Winter compared with FiT.The reduction is attributed to meeting deficient peer demand with network surplus before drawing from fossil-fuel-based grid generation.
- Evaluation scope: The evaluation emphasizes prosumer cost and CO2 reduction rather than other P2P objectives, which are described as relevant to the grid.Renewable-energy use is not discussed separately because CO2 reduction is treated as its result.
- Motivational implications: The authors conclude that the scheme satisfies the discussed motivational psychology models and has potential to enable extensive prosumer participation.The claimed motivational support includes attitude, rational economic, and positive reinforcement models.
- Network-scale effects: As the network grows from 5 to 25 prosumers, total cost reduction rises from $4.45 to $26.07 in Summer and from $2.89 to $15.63 in Winter.The paper also reports a steady increase in total CO2 reduction as the number of prosumers increases.
IV. CONCLUSION
The paper concludes that motivational psychology can guide prosumer-centric P2P energy-trading design, with cooperative game theory providing the scheme’s modeling framework. Numerical case studies demonstrate that the scheme’s outcomes satisfy the motivational models and could support widespread prosumer participation.
- The study combines a motivational psychology framework with a canonical coalition game to design a P2P energy-trading scheme.
- Numerical case studies demonstrate that the developed scheme’s outcomes satisfy the introduced motivational psychology models.
- The framework targets sustainable prosumer participation as a requirement for operating P2P trading within an energy system.
- Motivational psychology models can be applied to design trading schemes that encourage prosumers’ sustainable participation.
- Game theory is presented as a strong candidate for modeling P2P trading when prosumer participation is a concern.
- Motivational psychology could inform policy design for introducing P2P energy trading into existing electricity markets.