P2P Exchanges Research Articles

EnergyShare AI: Transforming P2P energy trading through advanced deep learning

Peer-to-peer (P2P) energy trading is an innovative concept poised to transform energy demand management and utilization. EnergyShare AI is a powerful peer-to-peer energy exchange system that operates on a P2P model that integrates advanced machine learning with distributed energy sharing. This paper presents EnergyShare AI, a technology that connects consumers and prosumers through solar arrays, energy storage systems (ESS), and electric vehicles (EVs). Using Deep Reinforcement Learning (DRL) algorithms, Energy Share AI significantly improves energy management efficiency and substantially reduces costs. Our approach offers several advantages over traditional linear integer programming models, particularly in optimizing bidirectional energy transfer involving EVs and highlighting the critical role of ESS and photovoltaic (PV) systems in facilitating efficient P2P energy trading. Our research results show that successful P2P exchange can lead to significant cost savings and improved sustainability, thereby increasing the amount of energy transferred between different household profiles and stages of human development.

Peer-to-peer energy trading under distribution network constraints with preserving independent nature of agents

In recent years, the use of distributed energy resources has accelerated to deal with global warming. As these resources are decentralized, the current centralized energy market must be modified to accommodate their characteristics. Advances in information technology have made it possible to implement peer-to-peer (P2P) markets. However, completely removing the distribution system operator from P2P exchanges can risk the network's security. Conversely, establishing network security only by the operator can decline the independence of agents. This paper proposes a decentralized framework for implementing the P2P market based on the alternating direction method of multipliers, which maintains the distribution system's constraints, considering the agents' independent nature. The agents reach convergence with minimal exchange of information while maintaining the network constraints, including voltage and current limits. The network constraints are included using a proposed sensitivity approach in the sub-problem of each agent. In this approach, by calculating the sensitivity coefficients of voltage and current, the network security can be evaluated with the changes of active and reactive powers by agents. The simulation results demonstrate that the proposed framework can efficiently maintain network constraints. The short running time of the P2P trading with the proposed framework makes it feasible for practical applications.

Peer-to-peer trading in smart grid with demand response and grid outage using deep reinforcement learning

With the price of green energy now more reasonable, users can now produce enough electricity to meet their needs and make a profit by selling the surplus on the underground P2P energy market. For households, energy trading and demand management can reduce electricity costs. However, consumers generally obtain market offers based on their expectations and the forecasts of other households. However, the P2P exchange system is not able to quantify the gap between these offers and the best market. The objective of this paper is to apply deep reinforcement learning techniques to optimal energy trading and demand response (DR) methods within a peer-to-peer (P2P) market. The main objective is to maximize cost reductions. The best approach to achieve this objective was investigated as part of this project. The complexity of domestic energy trading and energy recovery is formally characterized as a partially observable Markov decision process (POMDP). Through decentralized training and performance-based learning, the strategy maximizes policy and value functions. In order to identify the most effective proactive solutions, a comparative analysis is carried out between the two parties. Based on the simulation results, it was observed that implementing the recommended reinforcement learning strategy to optimize peer-to-peer (P2P) energy exchange can lead to a significant improvement in the average household reward. Specifically, the average household reward can be increased by 7.6% and 12.08% by employing the aforementioned approach.

P2P market coordination methodologies with distribution grid management

As prosumers and energy communities gain prominence in power systems, energy trading between prosumers in local P2P markets is paramount. Within this novel market design, peers can directly exchange energy with each other, leading to economic advantages while supporting the decarbonization of the sector. To ensure that voltage and congestion issues are properly addressed, a thorough coordination between the P2P market and the Distribution System Operator is required. This paper presents and compares three mutual-benefit coordination methods. The first method entails applying product differentiation on an iterative basis to avoid exceeding the lines thermal limits, which is performed through penalties on P2P exchanges that may be overloading the network. The second method uses the P2P market with an AC-OPF, ensuring network operation through a flexibility market via upward and downward flexibility. The last one proposes an integrated operation of the P2P market with AC-OPF. All methods are assessed in a typical distribution network with high prosumers integration. The results show that the second method is the one that, fulfilling the network constraints, presents greater social welfare.

Operating peer-to-peer electricity markets under uncertainty via learning-based, distributed optimal control

Towards the global endeavor of clean energy transition, there is a rapid development of distributed energy resources installed in the premises of residential or commercial users, enabling them to act as flexible energy prosumers. Empowering prosumers is envisioned as a catalytic development for modern energy economies, with recent research, as well as innovation and policy actions, pointing to the promising direction of decentralized energy markets, where active energy prosumers exchange energy in a decentralized fashion. Despite the vast amount of recent research on prosumer-centric peer-to-peer (p2p) energy markets, only a small subset of studies accounts for managing the inherent uncertainty of prosumers’ flexible demands.In this paper, we consider the problem of controlling the decisions of energy prosumers’ within a p2p exchange network. The multi-bilateral economic dispatch is formulated as an optimal control problem. The proposed solution is based on a direct lookahead policy, effectively addressing the issues of dimensionality and local constraint satisfaction. Experimental simulations demonstrate the method’s efficiency and the system’s behavior. The proposed formulation and method is shown to effectively address the operation of p2p markets under uncertainty, closely tracking the performance of the (full information) optimal-in-hindsight benchmark.

How economic system justification shapes demand for peer‐to‐peer providers

AbstractWith the proliferation of peer‐to‐peer (P2P) exchanges in the marketplace, understanding which consumer factors drive demand for P2P providers is important. We examine the role of consumers' economic system justification (ESJ) beliefs (about the fairness of existing economic arrangements and outcomes), which, despite their growing salience in the marketplace, have been overlooked in extant P2P research. We show that high (vs. low) ESJ increases consumers' interest in purchasing from P2P providers because it heightens perceptions of these providers' entrepreneurial spirit. The effect emerges in the laboratory and in the field with measured and manipulated ESJ, and it is attenuated for traditional commercial providers. The findings offer novel insights and implications for practice and emerging research on P2P exchanges, system justification, and ideological consumption more broadly.

Distributed Network-Constrained P2P Community-Based Market for Distribution Networks

Energy communities have been designed to empower consumers while maximizing the self-consumption of local renewable energy sources (RESs). Their presence in distribution systems can result in strong modifications in the operation and management of such systems, moving from a centralized operation to a distributed one. In this scope, this work proposes a distributed community-based local energy market that aims at minimizing the costs of each community member, accounting for the technical network constraints. The alternating direction method of multipliers (ADMM) is adopted to distribute the market, and preserve, as much as possible, the privacy of the prosumers’ assets, production, and demand. The proposed method is tested on a 10-bus medium voltage radial distribution network, in which each node contains a large prosumer, and the relaxed branch flow model is adopted to model the optimization problem. The market framework is proposed and modeled in a centralized and distributed fashion. Market clearing on a day-ahead basis is carried out taking into account actual energy exchanges, as generation from renewable sources is uncertain. The comparison between the centralized and distributed ADMM approach shows an 0.098% error for the nodes’ voltages. The integrated OPF in the community-based market is a computational burden that increases the resolution of the market dispatch problem by about eight times the computation time, from 200.7 s (without OPF) to 1670.2 s. An important conclusion is that the proposed market structure guarantees that P2P exchanges avoid the violation of the network constraints, and ensures that community agents’ can still benefit from the community-based architecture advantages.

What is the value of peer-to-peer energy trading? A discrete choice experiment with residential electricity users in Colombia

Peer-to-peer (P2P) energy trading is the electricity exchange between end-users with distributed energy resources, mainly photovoltaic panels. In P2P exchanges, electricity supply options can be differentiated by new energy attributes traced with smart meters and digital applications. Given the new range of supply options, energy users' preferences are crucial for designing P2P energy trading business models that engage consumers and advance the energy transition. This work identifies the preferences of a Colombian energy users' segment towards energy attributes in P2P trading. Contributing to a substantial evidence gap in the application of P2P energy trading in Latin America, we conducted a choice experiment with 1101 residential energy end-users in the Aburrá Valley (Medellín, Colombia). We evaluated the following energy attributes: generation source, ownership, location, and destination of profits. The results confirm a differentiated valuation of energy attributes among respondents across population segments. The perceived value of each attribute is represented as marginal willingness-to-pay over the usual energy bill—calculated by analysing choice data with a Mixed Logit Model. The average respondent is willing to pay the most for getting 100 % solar power, followed by a power supply where generation profits go to a social cause. Next in order of importance are energy from cooperative ownership, regional location, and neighbourhood location. Respondents would be willing to pay less for energy owned by an anonymous individual. This article contributes to understanding end-users' values around P2P energy trading and unveiling a potential market segment and preference structure. The results intend to pave the way for further research and the development of P2P energy models, especially in the Global South.

Techno-economic impacts of peer-to-peer in distribution networks with multiple sources of user-driven flexibility

In flexible energy communities, participants cooperate towards the valorization of local flexibility. This flexibility can be activated by optimizing the use of locally sourced renewable production with the coupled use of different types of flexible energy assets, which include a wide range of home and building appliances – demand-side flexibility. One way to leverage this community flexibility pool to generate internal techno-economic benefits is by engaging in intra-community trading, or peer-to-peer. However, the nuanced peer-to-peer trading impacts of different flexible demand profiles and tariff structures in the presence of renewable energy production are not well understood. This paper tackles these problems by implementing and simulating a P2P exchange model applied to the conditions of a pilot energy community of the FleXunity H2020 project, with participants in Spain and Portugal. The simulation results suggest that the trading of renewable energy and activated demand-side flexibility could induce substantial system load reduction impacts, as well as collective financial savings of a relevant extent.

Do economic crises cause trading in Bitcoin?

PurposeThe paper provides new evidence for Bitcoin’s safe-haven property by examining the relationship between currency price, return and Bitcoin trading volume.Design/methodology/approachA unique dataset from a person-to-person (p2p) exchange is used to investigate association between Bitcoin trading volume and currency prices. Currency returns are used to identify local economic crises, the 8 crisis affected currencies are Venezuela Bolivar (VES), Iranian Rial (IRR), Ukrainian Hryvnia (UAH), Argentine Peso (ARS), Egyptian Pound (EGP), Nigerian Naira (NGN), Turkish Lira (TRY) and Kazakhstani Tenge (KZT).FindingsThe paper demonstrates that local economic crises are positively associated with increased Bitcoin trading. There is a negative association between trading volume and currency value (and return), suggesting low currency price and currency depreciation are accompanied with increased Bitcoin trading. The results not only hold for the crisis affected currencies but also currencies of advanced economies. Granger causality test also reinforces the negative association results.Originality/valueThe finding indicates some forms of flight-to-safety have occurred during local market crises when capital flight from domestic markets to Bitcoin, strengthening Bitcoin’s hedging asset status. However, total global trading volume declines after the start of the COVID pandemic, suggesting that Bitcoin is still regarded as a speculative asset. Overall, the findings show that Bitcoin is a hedging asset to protect against local currency depreciation, but not a safe-haven asset for the global crisis.

Peculiarities of countering legalization of criminal income with the help of virtual assets: legislative regulation and practical implementation

PurposeThe purpose of this paper is to define and characterize peculiarities of countering the legalization of criminal income with the help of virtual assets.Design/methodology/approachThe analysis of the legislative delineation and the realities of the practical implementation of the features of combating the legalization of criminal proceeds with the help of virtual assets in Ukraine was carried out with the help of general scientific methods of cognition. The systematic method helped identify the main ways to legalize criminal proceeds with the help of virtual assets. Using legal techniques, proposals will be formulated to amend draft legislation on legislative regulation of the concept of “virtual assets”. The generalization method was used to develop ways to combat the legalization of criminal proceeds with the help of virtual assets. The method of legal forecasting was used to substantiate the proposed areas of combating money laundering with the help of virtual assets. The method of extrapolation will be used to determine the possibility of implementing foreign experience in domestic practice to combat money laundering with the help of virtual assets.FindingsOne of the relatively new and increasingly popular ways of money laundering is to commit this act with the help of virtual assets. Methods of money laundering through virtual assets include services for the conversion of virtual assets, P2P exchange, gambling sites, virtual asset mixers and the use of fictitious internet sites selling digital goods. The difficulty of counteracting the legalization of criminal proceeds with the help of virtual assets is primarily due to the lack of legislative regulation of the concept of “virtual assets” in Ukraine. Yes, the draft law is currently being finalized. Besides, even the current edition is not evaluated by the authors as perfect. After all, the issue of the content of the concept of “virtual assets” and its relationship with virtual securities, cryptocurrency and virtual property remains unresolved.Originality/valueOne of the relatively new and increasingly popular ways of money laundering is to commit this act with the help of virtual assets. Methods of money laundering through virtual assets include services for the conversion of virtual assets, P2P exchange, gambling sites, virtual asset mixers and the use of fictitious internet sites selling digital goods. It is essential to intensify financial monitoring by financial control bodies over the activities of conversion service centers. Moreover, given the transnational nature of legalizing criminal proceeds, especially those committed through virtual assets, international cooperation in combating this crime is vital. The authors have proposed specific measures to ensure that a coherent consolidation of efforts can be built.

Power dynamics in peer-to-peer accommodation: Insights from Airbnb hosts.

This study explores power dynamics in peer-to-peer (P2P) accommodation by examining how they manifest in the host-guest relationship. In so doing, it advances understanding on the role of hosts in the P2P practice and contributes insights on the factors conditioning the reciprocity of the P2P exchange. Drawing from power theories, the study uncovers how the interdependencies among hosts, guests and platforms influence power constellations emanating from P2P accommodation growth and reflexively redefine host practice. Specifically, the study illustrates how hosts are attempting to resist power imbalances characterising the exchange and how the dynamic environment of P2P accommodation leads to distinct representations of host types. The study makes explicit a conceptual framework that captures the power shifts noticeable in P2P accommodation that may be of theoretical and practical value to academics and policymakers alike.

Collaborative consumption, social distance and the extended self

PurposeThis paper aims to look at the exchange context of peer-to-peer (P2P) collaborative consumption (e.g. Uber and Airbnb). Specifically, the paper examines the effect that the sharing of a personal possession, such as a car or apartment, may have on the consumer.Design/methodology/approachTwo studies were conducted via online surveys. The surveys used vignettes that asked participants to imagine service experiences in either a P2P or a business-to-consumer (B2C) context. The participants then answered questions, including their perceptions of social closeness to the service provider, as well as willingness to pay (Study 1) and expectations of satisfaction (Study 2). The analysis used bootstrapping regression models to examine the relationships.FindingsIn both studies, the participants in the P2P conditions reported significantly greater perceived social closeness to the service provider than did those in the B2C condition. The P2P condition also resulted in significant indirect effects (i.e. mediated by social closeness) on willingness to pay (Study 1) and expectations of satisfaction (Study 2).Originality/valueThis paper extends the work on social distance to show that the effects are activated by the P2P exchange context. Also demonstrated here is that social closeness acts as an important mediator in the P2P context, affecting outcomes in the consumption and pre-consumption stages. Finally, construal level effects are extended to show that trend interpretation can be influenced by social distance.

No one rides for free! Three styles of collaborative consumption

PurposeThis paper aims to focus on collaborative consumption, that is, the peer-to-peer (P2P) exchange of goods and services facilitated by online platforms. Anchored in the access paradigm, collaborative consumption (e.g. accommodation rental and ridesharing services) differs from commercial services offered by firms (e.g. business-to-customer [B2C] carsharing). The aim of this study is to examine the nuanced styles of collaborative consumption in relation to market-mediated access practices and socially mediated sharing practices.Design/methodology/approachFollowing the general research trend on mobility services, the context of long-distance ridesharing is chosen. Data collection was conducted using participant observation as peer service provider, 11 ethnographic interviews of consumers and a netnographic study of digital artifacts.FindingsUsing practice theory, ten ridesharing activities were identified. These activities and the nuances in the procedures, understandings and engagements in the ridesharing practice led to the distinction of three styles of collaborative consumption: communal collaborative consumption, which is when participants seek pro-social relationships in belonging to a community; consumerist collaborative consumption, performed by participants who seek status and convenience in the access lifestyle; and opportunistic collaborative consumption, when participants seek to achieve monetary gain or personal benefits from abusive activities.Originality/valueBy taking a phenomenological approach on collaborative consumption, this study adds to the understanding of the sharing economy as embedded in both a utilitarian/commercial economic system and a non-market/communal social system. The three styles of collaborative consumption propose a framework for future studies differentiating P2P exchanges from other practices (i.e. B2C access-based services and sharing).

A typology for P2P access based exchanges in marketplaces

Different business models, products and services that are introduced with the advances in digital technologies and Internet gave rise to alternative modes of consumption. Along with this shift from ownership-based to an access based consumption, a stream of scholarly research has focused on different aspects of alternative modes of consumption such as sharing, gift giving, collaborative consumption, etc. to explain the emerging phenomena. Although several conceptualizations can be found in the literature, there is still a gap in the academic knowledge about peer-to-peer (P2P) sharing and its content. Products and services subject to sharing may vary from a car that is shared for a ride by the owner with a passenger in return for an economic benefit -so called ridesharing-, or a house that is owned by an individual and made available for rental of other people -as in Airbnb-. As the notion of exchange differs significantly between various business models based on access based P2P exchanges, this creates new possibilities to redefine the concept. This study compares access based P2P exchanges with market-mediated access-based consumption (Bardhi and Eckhardt, 2012) and sharing (Belk, 2007), and offers a typology based on the level of transfer of ownership and economic nature of perceived value. Real life business models are presented based on this typology and further research directions are suggested to better understand the main motivations of consumers for choosing an access based P2P model rather than conventional options available in the market.

Digital Trust and Peer-to-Peer Collaborative Consumption Platforms: A Mediation Analysis

This paper investigates the nature of digital trust in the context of P2P collaborative consumption platforms. We have analyzed data from the website Trustpilot.com (N=5,606), survey data from users of the online sharing platform Airbnb (N=232), and data retrieved from an online experiment conducted among current non-users of a fictitious online sharing platform (N=462). The findings reveal that trust in P2P collaborative consumption platforms (Airbnb, Lyft, and Uber) is lower than trust in P2P exchange first generation platforms (Ebay), as well as large online retail services and non-P2P platforms (Walmart, Zappos, Amazon). Furthermore, we find that the three trust-building management measures: ‘reliable insurance cover’, ‘simultaneous reviews’, and a ‘large network: many offers worldwide’ had a positive effect on ‘trust in the platform provider’. The findings confirm the hierarchical nature of the two-fold trust construct, meaning that ‘trust in the platform provider’ has a positive effect on the ‘trust in peers’ sharing on this platform. A mediation analysis reveals that ‘trust in the platform’ fully mediates all statistically significant effects of trust-building measures on the ‘trust in peers’ variable.

Exploring commitment in peer-to-peer exchanges: the case of timebanks

ABSTRACTDespite the growing trend of peer-to-peer (P2P) exchanges, there is a lack of studies that examine the determinants of the relationship between exchanging partners and the role of commitment in particular. This is especially necessary as P2P exchanges enact a different type of reciprocity from that of ‘business-to-consumers’. Thus, exploring P2P exchanges allows a better understanding of the drivers of commitment and the relationship of commitment with reciprocity. This qualitative and exploratory study examines the case of timebanks (TBs). Drawing from 40 in-depth interviews with TB managers and users along with participant observation, this study finds that commitment is a complex and multidimensional construct that may vary drastically depending on the distinct foci of commitment, the dual roles that users perform (as providers or as recipients), the type of exchange system and the notion of reciprocity underlying the exchange system.

La tutela administrativa de la propiedad intelectual en la sociedad de la información

Se trata de un riguroso y completo estudio que analiza la nueva tutela administrativa de la propiedad intelectual en la sociedad de la información, nacida ante las insuficiencias de la vía penal y civil. La primera, por la exigencia de ánimo de lucro, entendido como lucro comercial, y no como el “ahorro” del usuario privado no autorizado, así como por no abarcar el tipo penal la conducta consistente en enlazar a páginas no autorizadas. La segunda, por cuanto no es uniforme en la jurisprudencia la consideración de los enlaces a obras protegidas o el intercambio P2P como una ilegalidad. Además, se ha encontrado obstáculos en la protección de datos. Por una parte, porque la Agencia Española de Protección de Datos, de forma discutible, ha considerado ilegal la recogida inconsentida de datos de tráfico de direcciones IP por las entidades de gestión de derechos de autor.

Legal Issues Concerning P2P Exchange of Educational Materials and Their Impact on E-Learning Multi-Agent Systems

In current eLearning models and implementations (e.g. Learning Management Systems-LMS) there is a lack of engagement between formal and informal activities. Furthermore, the online methodology focuses on a standard set of units of learning and learning objects, along with pre-defined tests, and collateral resources like, i.e. discussion fora and message wall. They miss the huge potential of learning via the interlacement of social networks, LMS and external sources. Thanks to user behaviour, user interaction, and personalised counselling by a tutor, learning performance can be improved. We design and develop an adaptation eLearning model for restricted social networks, which supports this approach. In addition, we build an eLearning module that implements this conceptual model in a real application case, and present the preliminary analysis and positive results.

Quantifying paedophile activity in a large P2P system

Increasing knowledge of paedophile activity in P2P systems is a crucial societal concern, with important consequences on child protection, policy making, and internet regulation. Because of a lack of traces of P2P exchanges and rigorous analysis methodology, however, current knowledge of this activity remains very limited. We consider here a widely used P2P system, eDonkey, and focus on two key statistics: the fraction of paedophile queries entered in the system and the fraction of users who entered such queries. We collect hundreds of millions of keyword-based queries; we design a paedophile query detection tool for which we establish false positive and false negative rates using assessment by experts; with this tool and these rates, we then estimate the fraction of paedophile queries in our data; finally, we design and apply methods for quantifying users who entered such queries. We conclude that approximately 0.25% of queries are paedophile, and that more than 0.2% of users enter such queries. These statistics are by far the most precise and reliable ever obtained in this domain.