Progressive Second Price Auction Research Articles

An Online Continuous Progressive Second Price Auction for Electric Vehicle Charging

In this paper, we address the issue of the energy trading in the scenario of electric vehicles (EVs) charging in the smart grid. The EVs energy trading problems have attracted growing attention with the popularity of EVs. As the traditional first-reserve-first-serve scheme in the energy trading market impairs the benefits of both buyers and seller, we consider an auction scheme, called progressive second price (PSP), which has been proved to be an efficient way to conduct resource allocation in the trading market. Compared with other auction schemes, the PSP scheme can achieve both incentive compatibility and Nash equilibrium, which are important properties for the market. Nonetheless, the PSP auction scheme is not designed for online auction and it cannot guarantee that the seller can provide an enough number of charging piles to satisfy the demand of winners. To tackle these issues, in this paper we propose a novel online continuous PSP-based auction scheme, which is capable of not only achieving the property of online energy trading but also guaranteeing that the number of winners is limited to be no more than the number of charging piles. Further, we prove that our auction scheme achieves incentive compatibility and Nash equilibrium. The extensive experimental results demonstrate that our auction scheme achieves good performance with respect to social welfare, the seller satisfaction ratio, the buyer satisfaction ratio, as well as computation overhead.

Bandwidth-sharing in LHCONE, an analysis of the problem

The LHC experiments have traditionally regarded the network as an unreliable resource, one which was expected to be a major source of errors and inefficiency at the time their original computing models were derived. Now, however, the network is seen as much more capable and reliable. Data are routinely transferred with high efficiency and low latency to wherever computing or storage resources are available to use or manage them.Although there was sufficient network bandwidth for the experiments’ needs during Run-1, they cannot rely on ever-increasing bandwidth as a solution to their data-transfer needs in the future. Sooner or later they need to consider the network as a finite resource that they interact with to manage their traffic, in much the same way as they manage their use of disk and CPU resources.There are several possible ways for the experiments to integrate management of the network in their software stacks, such as the use of virtual circuits with hard bandwidth guarantees or soft real-time flow-control, with somewhat less firm guarantees. ly, these can all be considered as the users (the experiments, or groups of users within the experiment) expressing a request for a given bandwidth between two points for a given duration of time. The network fabric then grants some allocation to each user, dependent on the sum of all requests and the sum of available resources, and attempts to ensure the requirements are met (either deterministically or statistically).An unresolved question at this time is how to convert the users’ requests into an allocation. Simply put, how do we decide what fraction of a network's bandwidth to allocate to each user when the sum of requests exceeds the available bandwidth? The usual problems of any resourcescheduling system arise here, namely how to ensure the resource is used efficiently and fairly, while still satisfying the needs of the users.Simply fixing quotas on network paths for each user is likely to lead to inefficient use of the network. If one user cannot use their quota for some reason, that bandwidth is lost. Likewise, there is no incentive for the user to be efficient within their quota, they have nothing to gain by using less than their allocation.As with CPU farms, some sort of dynamic allocation is more likely to be useful. A promising approach for sharing bandwidth at LHCONE is the ’Progressive Second-Price auction’, where users are given a budget and are required to bid from that budget for the specific resources they want to reserve. The auction allows users to effectively determine among themselves the degree of sharing they are willing to accept based on the priorities of their traffic and their global share, as represented by their total budget. The network then implements those allocations using whatever mix of technologies is appropriate or available.This paper describes how the Progressive Second-Price auction works and how it can be applied to LHCONE. Practical questions are addressed, such as how are budgets set, what strategy should users use to manage their budget, how and how often should the auction be run, and how do we ensure that the goals of fairness and efficiency are met.

Auction-based distributed efficient economic operations of microgrid systems

This paper studies the economic operations of the microgrid in a distributed way such that the operational schedule of each of the units, like generators, load units, storage units, etc., in a microgrid system, is implemented by autonomous agents. We apply and generalise the progressive second price (PSP) auction mechanism which was proposed by Lazar and Semret to efficiently allocate the divisible network resources. Considering the economic operation for the microgrid systems, the generators play as sellers to supply energy and the load units play as the buyers to consume energy, while a storage unit, like battery, super capacitor, etc., may transit between buyer and seller, such that it is a buyer when it charges and becomes a seller when it discharges. Furthermore in a connected mode, each individual unit competes against not only the other individual units in the microgrid but also the exogenous main grid possessing fixed electricity price and infinite trade capacity; that is to say, the auctioneer assigns the electricity among all individual units and the main grid with respect to the submitted bid strategies of all individual units in the microgrid in an economic way. Due to these distinct characteristics, the underlying auction games are distinct from those studied in the literature. We show that under mild conditions, the efficient economic operation strategy is a Nash equilibrium (NE) for the PSP auction games, and propose a distributed algorithm under which the system can converge to an NE. We also show that the performance of worst NE can be bounded with respect to the system parameters, say the energy trading price with the main grid, and based upon that, the implemented NE is unique and efficient under some conditions.

Analysis of Quantized Double Auctions with Application to Competitive Electricity Markets

In recently proposed electricity markets, price-based competitive behaviours of power suppliers (i.e., generators), energy service providers and large users (i.e., consumers) have been formulated using various auction algorithms (see Post et al., 1995; Wolfram, 1998; Dekrajangpetch and Shebl, 2000; Nicolaisen et al., 2001; Swider and Weber, 2007). In this paper, quantized Progressive Second Price (PSP) auction algorithms are presented for competitive electricity systems, especially for short-run electric power markets. In Jia and Caines (2008, 2010), two quantized PSP auction algorithms were introduced and analyzed for demand markets, which are called, respectively, the Aggressive-Defensive Quantized PSP (ADQ-PSP) algorithm and the Unique-limit Quantized PSP (UQ-PSP) algorithm. Here we first present an algorithm combined with ADQ-PSP and UQ-PSP features, and apply it to a double power auction system where competition on both power generators and energy service providers (and/or large users) is considered. Double auctions are formulated in this work as two single-sided quantized auctions which depend upon joint market quantities and price constraints. The extended algorithm inherits the performance properties of ADQ-PSP and UQ-PSP in terms of both the social welfare maximization and the rapid convergence rate.

On the rapid convergence of a class of decentralized decision processes: quantized progressive second-price auctions

A progressive second price (PSP) auction mechanism was proposed in (Semret, Liao, Campbell & Lazar 2000) for network bandwidth allocation. In this paper a quantized version of this mechanism (Q-PSP) is analyzed where the agents have similar demand functions and submit bids synchronously. It is shown that the non-linear dynamics induced by this mechanism are such that the prices bid by the various agents and the quantities allocated to these agents converge in at most five iterations or oscillate indefinitely; this behaviour is not only independent of the number of agents involved but is also independent of the number of quantization levels.

A note on some properties of an efficient network resource allocation mechanism

We present some limiting properties of a network resource allocation mechanism known as the Progressive Second Price (PSP) auction. This mechanism aims at efficiently allocate network resources, such as bandwidth or buffer capacity, in an environment characterized by competing users; the PSP auction seeks to solve or at least to ameliorate congestion in a network demanding a low signalling burden between the auctioneer and the users, and solving the allocation problem of an (theoretically) infinitely divisible resource. The allocation rule is inspired in the second price (Vickrey) auction. Our analysis of the PSP auction explores its limiting properties, namely, how the allocation changes in the presence of a polarized set of users. A polarized set of users is a mixture of users of two types: high valuation, low demand users and low valuation, high demand users. Mechanisms such as auctions are becoming increasingly popular to handle the resource allocation problem in networks facing congestion, such as the access to Internet-based services.