Seamless Service Provisioning for Mobile Crowdsensing: Towards Integrating Forward and Spot Trading Markets

The challenge of exchanging and processing of big data over Mobile Crowdsensing (MCS) networks calls for the new design of responsive and seamless service provisioning as well as proper incentive mechanisms. Although conventional onsite spot trading of resources based on real-time network conditions and decisions can facilitate the data sharing over MCS networks, it often suffers from prohibitively long service provisioning delays and unavoidable trading failures due to its reliance on timely analysis of complex and dynamic MCS environments. These limitations motivate us to investigate an integrated forward and spot trading mechanism (iFAST), which entails a new hybrid service trading protocol over the MCS network architecture. In iFAST, the sellers (i.e., mobile users with sensing resources) can provide long-term or temporary sensing services to the buyers (i.e., sensing task owners). iFast enables signing long-term contracts in advance of future transactions through a forward trading mode, via analyzing historical statistics of the market, for which the notion of overbooking is introduced and promoted. iFAST further enables the buyers with unsatisfying service quality to recruit temporary sellers through a spot trading mode, upon considering the current market/network conditions. We analyze the fundamental blocks of iFAST, and provide a case study to demonstrate its superior performance as compared to existing methods. Finally, future research directions on reliable service provisioning for next-generation MCS networks are summarized

Matching-based Hybrid Service Trading for Task Assignment over Dynamic Mobile Crowdsensing Networks

By opportunistically engaging mobile users (workers), mobile crowdsensing (MCS) networks have emerged as important approach to facilitate sharing of sensed/gathered data of heterogeneous mobile devices. To assign tasks among workers and ensure low overheads, a series of stable matching mechanisms is introduced in this paper, which are integrated into a novel hybrid service trading paradigm consisting of futures trading mode and spot trading mode to ensure seamless MCS service provisioning. In the futures trading mode, we determine a set of long-term workers for each task through an overbooking-enabled in-advance many-to-many matching (OIA3M) mechanism, while characterizing the associated risks under statistical analysis. In the spot trading mode, we investigate the impact of fluctuations in long-term workers' resources on the violation of service quality requirements of tasks, and formalize a spot trading mode for tasks with violated service quality requirements under practical budget constraints, where the task-worker mapping is carried out via onsite many-to-many matching (O3M) and onsite many-to-one matching (OMOM). We theoretically show that our proposed matching mechanisms satisfy stability, individual rationality, fairness and computational efficiency. Comprehensive evaluations also verify the satisfaction of these properties under practical network settings, while revealing commendable performance on running time, participators' interactions, and service quality

Transforming Energy Networks via Peer to Peer Energy Trading: Potential of Game Theoretic Approaches

Peer-to-peer (P2P) energy trading has emerged as a next-generation energy management mechanism for the smart grid that enables each prosumer of the network to participate in energy trading with one another and the grid. This poses a significant challenge in terms of modeling the decision-making process of each participant with conflicting interest and motivating prosumers to participate in energy trading and to cooperate, if necessary, for achieving different energy management goals. Therefore, such decision-making process needs to be built on solid mathematical and signal processing tools that can ensure an efficient operation of the smart grid. This paper provides an overview of the use of game theoretic approaches for P2P energy trading as a feasible and effective means of energy management. As such, we discuss various games and auction theoretic approaches by following a systematic classification to provide information on the importance of game theory for smart energy research. Then, the paper focuses on the P2P energy trading describing its key features and giving an introduction to an existing P2P testbed. Further, the paper zooms into the detail of some specific game and auction theoretic models that have recently been used in P2P energy trading and discusses some important finding of these schemes.Comment: 38 pages, single column, double spac

From wholesale energy markets to local flexibility markets: structure, models and operation

Most energy markets (EMs) across Europe are based on a design framework involving day-ahead, intraday, and bilateral markets, operating together with balancing markets. This framework was set out, however, when the vast majority of generation units were controllable and fuel-based. The increasing levels of renewable generation create unique challenges in the operation of EMs. In this context, flexibility markets are starting to be recognized as a promising and powerful tool to adequately valorize demand-side flexibility. This chapter describes the models underlying both centralized and bilateral markets, analyzes the operation of several European markets, introduces some energy management tools, analyzes the pressing issue of flexibility in system operation, and describes various pioneering flexibility platforms.info:eu-repo/semantics/publishedVersio

Blockchain and internet of things for electrical energy decentralization: A review and system architecture

Decentralization in electrical power grids has gained increasing importance, especially in the last two decades, since transmission system operators (TSO), distribution system operators (DSO) and consumers are more aware of energy efficiency and energy sustainability issues. Therefore, globally, due to the introduction of energy production technologies near the consumers, in residential and industrial sectors, new scenarios of decentralized energy production (DEP) are emerging. To guarantee an adequate power management in the electrical power grids, incorporating producers, consumers, and producers-consumers, commonly designated as prosumers together, it is important to adopt intelligent systems and platforms that allow the provision of information on energy consumption and production in real time, as well as for obtaining the price for the sale and purchase of energy. In this research the literature is analysed to identify the appropriate solutions to implement a decentralized electrical power grid based on sensors, blockchain and smart contracts, evaluating the current state of the art and pilot projects already in place. A conceptual model for a power grid model is presented, with renewable energy production, combining Internet of Things (IoT), blockchain and smart contracts.A descentralização nas redes elétricas ganhou importância crescente, especialmente nas últimas duas décadas, uma vez que os operadores da rede de transporte (ORT), operadores da rede de distribuição (ORD) e consumidores estão mais conscientes das questões de eficiência energética e sustentabilidade energética. Globalmente, devido à introdução de tecnologias de produção de energia junto dos consumidores, nos setores residencial e industrial, estão a surgir novos cenários de produção de energia descentralizada. Para garantir uma adequada gestão de energia nas redes elétricas, integrando produtores, consumidores e produtores-consumidores, vulgarmente designados por prosumers, é importante adotar sistemas e plataformas inteligentes que permitam fornecer informações sobre consumo e produção de energia em tempo real, bem como para obter o preço de compra e venda de energia. Nesta pesquisa, a literatura é analisada para identificar as soluções adequadas para implementar uma rede elétrica descentralizada baseada em sensores, blockchain e contratos inteligentes, avaliando o estado da arte atual e projetos piloto já em curso. É apresentado um modelo conceptual para um modelo de rede elétrica, com produção de energia renovável, combinando Internet das Coisas (IoT), blockchain e contratos inteligentes

Digitalisation and New Business Models in Energy Sector

This paper reviews digitalisation in energy sector by looking at the business models of 40 interesting new start-up energy companies from around the world. These start-ups have been facilitated by the rise of distributed generation, much of it intermittent in nature. We review Artificial Intelligence (AI), Machine Learning, Deep Learning and Blockchain applications in energy sector. We discuss the rise of prosumers and small-scale renewable generation, highlighting the role of Feed-in-Tariffs (FITs), the Distribution System Platform concept and the potential for Peer-to-Peer (P2P) trading. Our aim is to help energy regulators calibrate their support new business models

Data Assets: Tokenization and Valuation

Your Data (new gold, new oil) is hugely valuable (est. $13T globally) but not a 'balance-sheet' asset. Tokenization- used by banks for payments and settlement- lets you manage, value, and monetize your data. Data is the ultimate commodity industry. This position paper outlines our vision and a general framework for tokenizing data, managing data assets and data liquidity to allow individuals and organizations in the public and private sectors to gain the economic value of data, while facilitating its responsible and ethical use. We will examine the challenges associated with developing and securing a data economy, as well as the potential applications and opportunities of the decentralised data-tokenized economy. We will also discuss the ethical considerations to promote the responsible exchange and use of data to fuel innovation and progress