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

Feed-in tariffs for promoting solar PV: progressing from dynamic to allocative efficiency

The International Energy Association has observed that nearly all countries now offer or are planning feed-in tariffs (FiTs) for solar PV but debate has shifted from ‘if or how to implement a FiT’ to ‘how to move to a self-sustaining market post FiT’. The aim of this paper is to explain how a sustainable FiT can be designed for residential solar PV installations, focusing on the case of ‘solar rich’ Australia. Solar PV is approaching price parity at the retail level where the electricity price charged includes both transmission and distribution costs, in addition to the wholesale price. So the economic rationale for paying a FiT premium above market rates to achieve dynamic efficiency is no longer warranted. Socially, FiTs can be a problem because they tend to exacerbate social inequality by providing a transfer of wealth from poorer to richer households. Environmentally, FiTs can also fall short of their full potential to cut emissions if they lack ‘time of day’ price signals that reflect movements in the wholesale price. In this paper, we provide a framework in which a sustainable FiT can be designed that positively addresses all three areas of concern: social, environmental and economic. This framework identifies the market failures that exist in the residential solar PV electricity market, which include exacerbating inequity, poorly targeting myopic investment behaviour, inadequate transmission and distribution investment deferment price signals and inappropriate infant industry assistance. We argue that these market failures require addressing before the market can operate in an allocatively efficient manner. The sustainable FiT that we propose would lead to improvements in environmental, social and economic factors. The resultant transmission and distribution investment deferment would meet both environmental and economic objectives. Directly providing finance for solar PV installations would address both social equity and investment myopia. We argue that introducing appropriate pricing signals for solar PV installations via would be in the ongoing interest of all stakeholders. It is time to progress from FiTs focused on dynamics efficiency to a sustainable FiT that emphasises allocative efficiency as an explicit goal

Self-Tuning Service Provisioning for Decentralised Cloud Applications

Cloud computing has revolutionized service delivery by providing on-demand invocation and elasticity. To reap these benefits, computation has been displaced from client devices and into data centers. This partial centralization is undesirable for applications that have stringent locality requirements, e.g., low latency. This problem could be addressed with large numbers of smaller cloud resources closer to users. However, as cloud computing diffuses from within data centers and into the network, there will be a need for cloud resource allocation algorithms that operate on resource-constrained computational units that serve localized subsets of customers. In this paper, we present a mechanism for service provisioning in distributed clouds where applications compete for resources. The mechanism operates by enabling execution zones to assign resources based on Vickrey auctions and provides high-quality probabilistic models that applications can use to predict the outcomes of such auctions. This allows applications to use knowledge of the locality distribution of their clients to accurately select the number of bids to be sent to each execution zone and their value. The proposed mechanism is highly scalable, efficient, and validated by extensive simulations

Incentive-driven QoS in peer-to-peer overlays

A well known problem in peer-to-peer overlays is that no single entity has control over the software, hardware and configuration of peers. Thus, each peer can selfishly adapt its behaviour to maximise its benefit from the overlay. This thesis is concerned with the modelling and design of incentive mechanisms for QoS-overlays: resource allocation protocols that provide strategic peers with participation incentives, while at the same time optimising the performance of the peer-to-peer distribution overlay. The contributions of this thesis are as follows. First, we present PledgeRoute, a novel contribution accounting system that can be used, along with a set of reciprocity policies, as an incentive mechanism to encourage peers to contribute resources even when users are not actively consuming overlay services. This mechanism uses a decentralised credit network, is resilient to sybil attacks, and allows peers to achieve time and space deferred contribution reciprocity. Then, we present a novel, QoS-aware resource allocation model based on Vickrey auctions that uses PledgeRoute as a substrate. It acts as an incentive mechanism by providing efficient overlay construction, while at the same time allocating increasing service quality to those peers that contribute more to the network. The model is then applied to lagsensitive chunk swarming, and some of its properties are explored for different peer delay distributions. When considering QoS overlays deployed over the best-effort Internet, the quality received by a client cannot be adjudicated completely to either its serving peer or the intervening network between them. By drawing parallels between this situation and well-known hidden action situations in microeconomics, we propose a novel scheme to ensure adherence to advertised QoS levels. We then apply it to delay-sensitive chunk distribution overlays and present the optimal contract payments required, along with a method for QoS contract enforcement through reciprocative strategies. We also present a probabilistic model for application-layer delay as a function of the prevailing network conditions. Finally, we address the incentives of managed overlays, and the prediction of their behaviour. We propose two novel models of multihoming managed overlay incentives in which overlays can freely allocate their traffic flows between different ISPs. One is obtained by optimising an overlay utility function with desired properties, while the other is designed for data-driven least-squares fitting of the cross elasticity of demand. This last model is then used to solve for ISP profit maximisation

Impact of Braess's Paradox and Simultaneous Imposition of Non-Coincidental Transmission Outages on FTR Auctions

This thesis identifies and resolves an issue caused by Braess's paradox in Financial Transmission Right (FTR) auctions. Braess's paradox in power systems is the situation where adding a new transmission line can reduce the transmission system capacity, and vice-versa. FTRs are auctioned by Regional Transmission Organizations (RTOs) to market parties who wish to hedge uncertain transmission costs. The issue can cause the RTO to over-allocate FTRs and become revenue inadequate which leaves the RTO the dilemma of how to recover the deficit. An auction process called the simultaneous feasibility test (SFT) limits the FTR awarded to ensure that sufficient congestion rents are collected by the RTO to pay the FTR holders. The problem stems from an SFT approximation coined in this thesis the Simultaneous Imposition of Non-coincidental Transmission Outages (SINTO) that models planned transmission outages concurrently rather than as scheduled. When Braess's paradox applies to FTR auctions, the SFT approximation defies the intuitive assumption that removing transmission lines will reduce transmission system capacity. Thus, two methods are proposed to mitigate the effects of Braess's paradox in FTR auctions. The first is the Chronological Imposition of Planned Transmission Outages (CHIMPO), which ideally models the transmission outages as scheduled but also considerably increases the auction's computational cost. The second method, called the Normally-Operated – SINTO (NO-SINTO), is a robust and computationally inexpensive approximation that adds a single set of transmission constraints to the SINTO model. The five contributions of this thesis are described through simple examples and case study simulation using actual historical FTR auction data. The first establishes, using the SINTO SFT approximation, that the existence of Braess's paradox can lead to revenue inadequacy in FTR auctions. The second demonstrates that modeling SINTO in FTR auctions may aggravate the impact of the paradox. The third offers two alternative FTR auction models (CHIMPO, NO-SINTO) to reduce the risk of revenue inadequacy from Braess's paradox. The fourth demonstrates that the ideal CHIMPO allocation of FTRs is better approximated by the NO-SINTO model than the SINTO model. The fifth indicates that RTOs may practically implement the NO-SINTO approximation on a realistically sized power networks

Robust and cheating-resilient power auctioning on Resource Constrained Smart Micro-Grids

The principle of Continuous Double Auctioning (CDA) is known to provide an efficient way of matching supply and demand among distributed selfish participants with limited information. However, the literature indicates that the classic CDA algorithms developed for grid-like applications are centralised and insensitive to the processing resources capacity, which poses a hindrance for their application on resource constrained, smart micro-grids (RCSMG). A RCSMG loosely describes a micro-grid with distributed generators and demand controlled by selfish participants with limited information, power storage capacity and low literacy, communicate over an unreliable infrastructure burdened by limited bandwidth and low computational power of devices. In this thesis, we design and evaluate a CDA algorithm for power allocation in a RCSMG. Specifically, we offer the following contributions towards power auctioning on RCSMGs. First, we extend the original CDA scheme to enable decentralised auctioning. We do this by integrating a token-based, mutual-exclusion (MUTEX) distributive primitive, that ensures the CDA operates at a reasonably efficient time and message complexity of O(N) and O(logN) respectively, per critical section invocation (auction market execution). Our CDA algorithm scales better and avoids the single point of failure problem associated with centralised CDAs (which could be used to adversarially provoke a break-down of the grid marketing mechanism). In addition, the decentralised approach in our algorithm can help eliminate privacy and security concerns associated with centralised CDAs. Second, to handle CDA performance issues due to malfunctioning devices on an unreliable network (such as a lossy network), we extend our proposed CDA scheme to ensure robustness to failure. Using node redundancy, we modify the MUTEX protocol supporting our CDA algorithm to handle fail-stop and some Byzantine type faults of sites. This yields a time complexity of O(N), where N is number of cluster-head nodes; and message complexity of O((logN)+W) time, where W is the number of check-pointing messages. These results indicate that it is possible to add fault tolerance to a decentralised CDA, which guarantees continued participation in the auction while retaining reasonable performance overheads. In addition, we propose a decentralised consumption scheduling scheme that complements the auctioning scheme in guaranteeing successful power allocation within the RCSMG. Third, since grid participants are self-interested we must consider the issue of power theft that is provoked when participants cheat. We propose threat models centred on cheating attacks aimed at foiling the extended CDA scheme. More specifically, we focus on the Victim Strategy Downgrade; Collusion by Dynamic Strategy Change, Profiling with Market Prediction; and Strategy Manipulation cheating attacks, which are carried out by internal adversaries (auction participants). Internal adversaries are participants who want to get more benefits but have no interest in provoking a breakdown of the grid. However, their behaviour is dangerous because it could result in a breakdown of the grid. Fourth, to mitigate these cheating attacks, we propose an exception handling (EH) scheme, where sentinel agents use allocative efficiency and message overheads to detect and mitigate cheating forms. Sentinel agents are tasked to monitor trading agents to detect cheating and reprimand the misbehaving participant. Overall, message complexity expected in light demand is O(nLogN). The detection and resolution algorithm is expected to run in linear time complexity O(M). Overall, the main aim of our study is achieved by designing a resilient and cheating-free CDA algorithm that is scalable and performs well on resource constrained micro-grids. With the growing popularity of the CDA and its resource allocation applications, specifically to low resourced micro-grids, this thesis highlights further avenues for future research. First, we intend to extend the decentralised CDA algorithm to allow for participants’ mobile phones to connect (reconnect) at different shared smart meters. Such mobility should guarantee the desired CDA properties, the reliability and adequate security. Secondly, we seek to develop a simulation of the decentralised CDA based on the formal proofs presented in this thesis. Such a simulation platform can be used for future studies that involve decentralised CDAs. Third, we seek to find an optimal and efficient way in which the decentralised CDA and the scheduling algorithm can be integrated and deployed in a low resourced, smart micro-grid. Such an integration is important for system developers interested in exploiting the benefits of the two schemes while maintaining system efficiency. Forth, we aim to improve on the cheating detection and mitigation mechanism by developing an intrusion tolerance protocol. Such a scheme will allow continued auctioning in the presence of cheating attacks while incurring low performance overheads for applicability in a RCSMG

Coordination in Service Value Networks - A Mechanism Design Approach

The fundamental paradigm shift from traditional value chains to agile service value networks (SVN) implies new economic and organizational challenges. This work provides an auction-based coordination mechanism that enables the allocation and pricing of service compositions in SVNs. The mechanism is multidimensional incentive compatible and implements an ex-post service level enforcement. Further extensions of the mechanism are evaluated following analytical and numerical research methods