Wenyuan Tang

Hierarchical Auction Mechanisms for Network Resource Allocation

Motivated by allocation of bandwidth, wireless spectrum and cloud computing services in secondary network markets, we introduce a hierarchical auction model for network resource allocation. A Tier 1 provider owns a homogeneous network resource and holds an auction to allocate this resource among Tier 2 operators, who in turn allocate the acquired resource among Tier 3 entities. The Tier 2 operators play the role of middlemen, since their utilities for the resource depend on the revenues gained from resale. We first consider static hierarchical auction mechanisms for indivisible resources. We study a class of mechanisms wherein each sub-mechanism is either a first-price or VCG auction, and show that incentive compatibility and efficiency cannot be simultaneously achieved. We also briefly discuss sequential auctions as well as the incomplete information setting. We then propose two VCG-type hierarchical mechanisms for divisible resources. The first one is composed of single-sided auctions at each tier, while the second one employs double-sided auctions at all tiers except Tier 1. Both mechanisms induce an efficient Nash equilibrium.

Game-theoretic analysis of the nodal pricing mechanism for electricity markets

Nodal pricing is a methodology for pricing electricity and managing transmission congestion that is widely used in deregulated electricity markets. We focus on the economic dispatch problem and consider the strategic behavior of both generators and consumers. For the case of no congestion, we prove the existence of an efficient Nash equilibrium; for the case of congestion, we give examples and counterexamples to demonstrate the complexity of the outcomes. As an alternative, we propose the Power Network Second Price (PNSP) mechanism that always induces an efficient Nash equilibrium.

Stochastic resource auctions for renewable energy integration

Among the many challenges of integrating renewable energy sources into the the existing grid, is the challenge of integrating renewable energy generators into the power systems economy. Electric markets currently are run in a way that participating generators must supply contracted amounts. And yet, renewable energy generators such as wind power generators cannot supply contracted amounts with certainty. Thus, alternative market architectures must be considered where there are “aggregator” entities who participate in the electricity market by buying power from the renewable energy generators, and assuming risk of any shortfall from contracted amounts. In this paper, we propose auction mechanisms that can be used by the aggregators for procuring stochastic resources, such as wind power. The nature of stochastic resources is different from classical resources in that such a resource is only available stochastically. The distribution of the generation is private information, and the system objective is to truthfully elicit such information. We introduce a variant of the VCG mechanism for this problem. We also propose a non-VCG mechanism with a contracted-payment-plus-penalty payoff structure. We show generalization of the mechanisms to general objective functions, as well as multiple winners. We then consider the setting where the generators need to fulfill any shortfall from the contracted amount by buying from the spot market.

Market Mechanisms for Buying Random Wind

The intermittent nature of wind power leads to the question of how wind power producers can participate in a deregulated electricity market. In the proposed auction paradigm, wind farms bid probability distributions of generation, instead of bidding cost functions as thermal units do. Our focus is to design incentive compatible mechanisms that elicit truthful information of strategic agents who supply stochastic resource. We first study the aggregators problem of how to select the wind farms, which have the most desirable distributions. We then study the independent system operators (ISOs) problem of how to price wind energy for stochastic economic dispatch.

Model and data analysis of two-settlement electricity market with virtual bidding

Systematic nonzero spreads, defined as the differences between day-ahead and real-time prices, are routinely observed in the wholesale electricity markets. Virtual bidding is a financial mechanism which aims to reduce the magnitude of spreads by allowing market participants to arbitrage on the spread. We follow a data-driven approach to develop a two-settlement market model, and consider a game-theoretic setting with virtual bidders as strategic players. We interpret the spread as a measure of the average forecast accuracy of the market and all the virtual bidders. The main results convey the implication that introducing more qualified virtual bidders into the market help the convergence of the spread.

Dynamic Economic Dispatch Game: The Value of Storage

We formulate a dynamic economic dispatch game in which each generator has its own electricity storage device. The operation of storage introduces time-coupling constraints. We focus on how the use of storage may affect the market structure and market outcomes in the locational marginal pricing mechanism. We first show that even when the independent system operation is unaware of the storage, there exists an efficient bid profile that induces the optimal dispatch. We then demonstrate that the use of storage does not increase the room for strategic play, but may improve the equilibrium outcomes. We provide sufficient conditions under which there exist efficient Nash equilibria. Furthermore, we propose the marginal contribution pricing mechanism that guarantees efficient outcomes.

Stochastic dynamic pricing: Utilizing demand response in an adaptive manner

Dynamic pricing to residential customers has been proposed recently, as extensions of static network utility maximization problems. Those deterministic models do not exploit the refined information as time advances. To address this issue, we formulate a stochastic dynamic pricing framework, in which we show the existence of an optimal price process that incentives the agents to choose the socially optimal decisions. We develop a distributed algorithm and investigate the information structure of the involved stochastic processes via a numerical example, which also illustrates the advantage of stochastic dynamic pricing over deterministic dynamic pricing.

Predictability, constancy and contingency in electric load profiles

Electric load profile forecasting is among the most important tasks in power system operation. This task has been performed reasonably well with minimal disruption from renewables over the past decades. The expected high penetration of renewables in the system is challenging this classical task. Moreover, the blossom of demand side management programs warrants the necessity of load profile forecasting even for individual (residential as well as industrial) consumers. In this paper, we seek to define predictability in a rigorous way from an information theoretic perspective, which shed light on comparing the predictability between different kinds of loads. Then, we identify two separable components of predictability - constancy and contingency. We further exploit the key parameters in deciding the predictability, which challenge the commonly-held beliefs. For example, does a finer granularity imply a lower predictability? To what degree does the law of large numbers help improve the predictability?

Hierarchical Auctions for Network Resource Allocation

Motivated by allocation of cloud computing services, bandwidth and wireless spectrum in secondary network markets, we introduce a hierarchical auction model for network resource allocation. The Tier 1 provider owns all of the resource, who holds an auction in which the Tier 2 providers participate. Each of the Tier 2 providers then holds an auction to allocate the acquired resource among the Tier 3 users. The Tier 2 providers play the role of middlemen, since their utility for the resource depends entirely on the payment that they receive by selling it. We first consider the case of indivisible resource. We study a class of mechanisms where each sub-mechanism is either a first-price or a second-price auction, and show that incentive compatibility and efficiency cannot be simultaneously achieved. We then consider the resource to be divisible and propose the hierarchical network second-price mechanism in which there exists an efficient Nash equilibrium with endogenous strong budget balance.

Pricing sequential forward power contracts

Pricing mechanisms for multistage power procurement under uncertainty are studied in this paper. We first consider the most natural pricing mechanism in which the power at each stage is priced uniformly at the temporal marginal price. Under the truth-telling assumption, we show that this mechanism is price equivalent, efficient and flexibility subsidizing. Motivated by the observation that this mechanism is vulnerable to misreporting, we propose an alternative mechanism termed dynamic marginal contribution pricing, for which periodic ex post incentive compatibility is proved. Case studies illustrate the theoretical results obtained in this paper.