The Demand Elasticity Impacts on the Strategic Bidding Behavior of the Electricity Producers

Due to the oligopoly structure of the electricity markets and to the constraints imposed by the transmission network, the producers may exert market power by strategically bidding higher than their marginal costs. This brings market performance far from the perfect competition equilibrium, with higher market clearing price and extra surpluses obtained by the producers. Demand elasticity can significantly affect the market performance contributing to mitigate the strategic bidding behavior of the producers. Compared to other commodity markets, demand elasticity in the electricity markets is low, but even a small increase can result in appreciable improvement of the market performance. The network constraints of the power system play a specific role in determining the oligopoly equilibrium of the gaming behavior of the electricity producers. The model of supply function equilibrium is first applied to a simple three-bus test system for a conceptual analysis and then to a standard IEEE 30-bus test system. The effects of an increase of demand elasticity are assessed, resorting to a set of proper quantitative indexes     

Network constraint impacts on the competitive electricity markets under supply-side strategic bidding

In a competitive electricity market, the oligopoly structure of the market and the network constraints may produce results far from the perfect competition. This paper presents a comprehensive approach to evaluate the performances of the electricity markets with network representation in presence of bidding behavior of the producers in a pool system. A supply function strategic bidding model for the producers is introduced, and then different scenarios in terms of bidding behavior and network constraints are studied and compared on the basis of a set of microeconomic metrics. The aim of the paper is to assess, throughout a set of proper indices, the level of competition in a network-constrained market considering strategic behavior of the producers. The approach proposed gives the possibility to assess the different weight of strategic behavior of the producers and of the network constraints in distorting the market performances from its perfect competition equilibrium. From such an analysis, the worsening of the market efficiency and performances, due to the joint effects of the nonperfect competition and the network constraints, may be assessed and quantified, providing information on the adequacy of the grid considered for accommodating a competitive market. The exploitation of the proposed metrics for the market analysis is shown with reference to the IEEE 30-bus test system with demand elasticity explicitly represented.     

Widely convergent method for finding solutions of simultaneous nonlinear equations

The authors propose a new approach for solving the nonlinear problem, based on a model-reference adaptive control (MRAC). The algorithm is composed of three parts: a plant containing unknown parameters, a reference model for compactly specifying the desired output and an adaptation mechanism for updating the adjustable parameters. The structure of the adaptation mechanism is explicitly designed so that the asymptotical stability is guaranteed according to Lyapunov theorem. The method reformulates the algebraic nonlinear equations into a set of ordinary differential equations, whose equilibrium point corresponds to the solution of the original nonlinear problems. The stability and region of attraction coincide with entire state space no matter whether the parameters reside in solvable region or unsolvable region.     

基于猜测供给函数的需求弹性对电力市场运行的影响

影响市场运行的一个重要因素是需求弹性。低需求弹性将导致市场出清价格高,市场运行效率低,经济效益分配不合理。由于电力商品的特殊性,目前电力市场本质上具有寡头竞争的特点。相对较完全的竞争市场,发电商的策略竟标行为将导致市场运行在低效率水平下,这一消极因素在低需求弹性下尤为突出。为此提出了一个能评估需求弹性对发电商策略竞标行为影响的模型。该模型将发电商的博弈行为模拟成猜测供给函数(conjiecture supply function,CSF)竞争,同时将交易市场中的用户需求弹性包含在数学模型中。通过对意大利电力市场的单时段交易的模拟,运用一系列指标来量化评估需求弹性对具有寡头竞争性质的市场运行的影响。     

Congestion management impacts on bilateral electricity markets under strategic negotiation

Congestion management design is key to a fair and efficient use of transmission facilities and an improvement of market efficiency. Emergence of bilateral electricity markets provides a more flexible, private and decentralized decision-making scenario, in which the self-interested players autonomously search for counterparts to negotiate profitable transactions. In competitive bilateral markets of imperfect and incomplete information and explicit consideration of the network constraints, which make the markets significantly complex, more sophisticated bargaining strategies and market evaluation tools are imperative to both players and regulators.In this paper, under an assumption of imperfect and incomplete information, evolutionary bipartite complex network theory is employed to develop quantities bidding strategies through a dynamic game, in which the players drive the evolution of the network while maximizing their own utilities with explicitly considering the congestion management results. Resorting to adjustment bids, two congestion management schemes, with and without balancing bilateral transactions, are considered.The approach is illustrated with an application to the IEEE30 test system, assessing the impact of different congestion management schemes on the negotiations, market equilibria, market performance and gaming opportunities for the market participants in congestion managements.     

INFLUENCE OF A NEGATIVE R RATIO ON THE CREEP-FATIGUE BEHAVIOUR OF THE N18 NICKEL BASE SUPERALLOY

Abstract— Crack growth rate measurements, performed on smooth specimens during creep-fatigue testing of the N18 nickel base superalloy at 650°C, reveal a strong detrimental effect of the compressive part of the loading cycle. This effect is attributed to the residual stresses in the wake of the crack, which promote early crack opening. A finite element analysis is conducted in order to predict the evolution of the opening stress level as a function of the stress ratio. Good agreement is found between numerical and experimental results. The influence of the constitutive equation of the material on the crack closure level is tested and the effects of kinematic hardening and viscosity are more specifically examined. An engineering simplified method is proposed to determine the opening stress intensity factor as a function of crack length, stress ratio and maximum stress. This method, developed for cracks in smooth specimens, is then applied to small cracks growing from a notch root. Good agreement is found between the results given by the engineering simplified method and the result of the finite element analysis.     

Synthesis Optimization and Catalytic Activity Screening of Industrially Relevant Ruthenium-Based Metathesis Catalysts

Olefin metathesis is a powerful catalytic reaction that has a huge potential in the pharmaceutical, polymer and specialty chemicals industries. Cost-effective industrial applications require large-scale availability of catalyst precursors which combine high activity, high selectivity and long life-time. Among the known numerous families of olefin metathesis catalysts, the Umicore M7-catalyst family represents a novel class of Hoveyda-type complexes showing excellent chemical stabilities and modular activity profiles. Relevant aspects related to their industrial synthesis as well as their catalytic performance in valuable olefin metathesis transformations are overviewed here.

     

基于自加强学习算法的发电商报价策略研究

电力市场中发电商的决策过程和多发电商的相互作用过程是个复杂动态问题,很难用传统的解析方法进行分析计算,这在考虑中长时间段交易时尤为突出,且多代理作用机制是个很好的补充。文中提出了一个能够模拟发电商在市场中进行策略性报价的中长期交易时间段决策过程模型,对多发电商交互作用导致的市场行为进行了仿真试验。该模型基于自加强Watkins’sQ(λ)学习算法并包含了可能对电力市场运行产生重要影响的网络阻塞因素。该模型可以形成发电商的最优策略以最大化中长期生产效益和可以找到中长期市场平衡点并据此评估市场中长期运行情况。通过在标准IEEE-14节点系统中进行仿真计算表明该模型的有效性和新颖性。     

Dynamic price forecast in a competitive electricity market

Price forecast is a key issue in competitive electricity markets. It provides useful information for the market players and the regulators, in both short and long run. Different approaches have been proposed and implemented. A new dynamic approach for forecasting the market price of electricity in the short term is proposed. The price dates are first clustered according to different types of daily profiles and then, given a proper function representing the trend in price, the set of unknown parameters are identified based on the zeroing of a Lyapunov function. The forecast can be dynamically updated with the latest data available. Higher weight can be attributed to this data in determining the future prices. The proposed approach is validated with reference to real systems in the form of the Italian, New England and New York electricity markets. In addition, an extensive price forecast is provided for the Italian market, an example of a young market that is rather difficult to predict patterns for.