Bidding strategy with forecast technology based on support vector machine in the electricity market

The participants in the electricity market are concerned very much with the market price evolution. Various technologies have been developed for price forecasting. The SVM (Support Vector Machine) has shown its good performance in market price forecasting. Two approaches for forming the market bidding strategies based on SVM are proposed. One is based on the price forecasting accuracy, with which the rejection risk is defined. The other takes into account the impact of the producer’s own bid. The risks associated with the bidding are controlled by the parameter settings. The proposed approaches have been tested on a numerical example.     

Electricity Storage With High Roundtrip Effciency in a Reversible Solid Oxide Cell Stack

We theoretically investigate the electricity storage/generation in a reversible solid oxide cell stack. The system heat is for the first time tentatively stored in a phase-change metal when the stack is operated to generate electricity in a fuel cell mode and then reused to store electricity in an electrolysis mode. The state of charge (H₂ frication in cathode) effectively enhances the open circuit voltages (OCVs) while the system gas pressure in electrodes also increases the OCVs. On the other hand, a higher system pressure facilitates the species diffusion in electrodes that therefore accordingly improve electrode polarizations. With the aid of recycled system heat, the roundtrip efficiency reaches as high as 92% for the repeated electricity storage and generation.     

Dynamics of electricity market correlations

Electricity market participants rely on demand and price forecasts to decide their bidding strategies, allocate assets, negotiate bilateral contracts, hedge risks, and plan facility investments. However, forecasting is hampered by the non-linear and stochastic nature of price time series. Diverse modeling strategies, from neural networks to traditional transfer functions, have been explored. These approaches are based on the assumption that price series contain correlations that can be exploited for model-based prediction purposes. While many works have been devoted to the demand and price modeling, a limited number of reports on the nature and dynamics of electricity market correlations are available. This paper uses detrended fluctuation analysis to study correlations in the demand and price time series and takes the Australian market as a case study. The results show the existence of correlations in both demand and prices over three orders of magnitude in time ranging from hours to months. However, the Hurst exponent is not constant over time, and its time evolution was computed over a subsample moving window of 250 observations. The computations, also made for two Canadian markets, show that the correlations present important fluctuations over a seasonal one-year cycle. Interestingly, non-linearities (measured in terms of a multifractality index) and reduced price predictability are found for the June-July periods, while the converse behavior is displayed during the December-January period. In terms of forecasting models, our results suggest that non-linear recursive models should be considered for accurate day-ahead price estimation. On the other hand, linear models seem to suffice for demand forecasting purposes.     

原子核强度电势和原子价层电量对元素电负性的标度

根据万有引力势与电势的关系式和系统的对比质电比(单位电量的质量)的物理意义, 定义了系统的强度电势——单位质量的电势. 研究表明, 元素电负性XSc与原子核在原子边界面上的强度电势Vic和价层电子电量qcj成线性关系. 采用回归分析法, 对周期表中除零族、氢及放射性元素之外的77种元素的Pauling电负性(XP)进行回归分析, 得到了一个无量纲的综合性的电负性计算公式, 相关系数(R=0.9844)和回归方程F检验的显著性水平(Sig.=0.0000)表明, XSc与Vic和qcj密切相关, 77种元素的拟合值与XP十分接近, 平均绝对误差仅为0.084; 并预测出较为合理的稀有气体元素的电负性. 用该式可以方便而更准确地计算除氢以外的所有元素的电负性; 同时也给出一条获取离子电负性和基团电负性的新途径.     

Heavy-tails and regime-switching in electricity prices

In this paper we first analyze the stylized facts of electricity prices, in particular, the extreme volatility and price spikes which lead to heavy-tailed distributions of price changes. Then we calibrate Markov regime-switching (MRS) models with heavy-tailed components and show that they adequately address the aforementioned characteristics. Contrary to the common belief that electricity price models ‘should be built on log-prices’, we find evidence that modeling the prices themselves is more beneficial and methodologically sound, at least in case of MRS models.     

直流电压等离子体点火器点火特性研究

使用自行设计的等离子体点火装置,对极间电流随进口氩气压力的变化规律以及不同进口氩气压力和工作电流条件下等离子体点火器出口射流特性进行了实验研究。利用四通道CCD光谱仪测量了点火器出口处的发射光谱特征,并计算了等离子体的电子温度。结果表明,极间电流随进口氩气压力的增大而逐渐减小,等离子体点火器的射流长度随进口氩气流量的增大先增大后减小,随工作电流的增大而增大,等离子体点火器的工作电流随进口氩气流量的增大而减小,随电源输出电流增大而增大,等离子体射流的电子温度随氩气流量的增大而降低,随工作电流的增大而升高。所得结果对等离子体点火系统在航空发动机的实际应用具有一定的指导意义和参考价值。     

树枝状纳米银颗粒的制备与电活性

在Ag(NH3)2+溶液中,在钛基体上电沉积出树枝状纳米银颗粒,研究了沉积电位对树枝状纳米银颗粒形成的影响,探讨了这种树枝状纳米银颗粒形成的机理,并研究了这种钛基树枝状纳米银电极(Ag/Ti)在碱性溶液中对甲醛氧化的电催化活性。结果表明,在30 mmol/LAg(NH3)2+以及沉积电位在-1.8～-1.2 V(vsAg)时,形成了形态为树枝状的纳米银颗粒。在沉积电位为-1.6 V(vs Ag),Ag(NH3)2+浓度为30 mmol/L的溶液中,电沉积制备的这种树枝状纳米银电极(Ag/Ti)对甲醛氧化具有强的电催化活性。循环伏安曲线表明,在0.1 mol/LNaOH溶液中以及甲醛的浓度范围在0～40 mmol/L,甲醛浓度和它的氧化峰电流密度呈现良好的线性关系,检测下限达到0.662 mmol/L,这种新型的树枝状纳米银电极有望作为甲醛检测的传感器。     

Markov switching of the electricity supply curve and power prices dynamics

Regime-switching models seem to well capture the main features of power prices behavior in deregulated markets. In a recent paper, we have proposed an equilibrium methodology to derive electricity prices dynamics from the interplay between supply and demand in a stochastic environment. In particular, assuming that the supply function is described by a power law where the exponent is a two-state strictly positive Markov process, we derived a regime switching dynamics of power prices in which regime switches are induced by transitions between Markov states.In this paper, we provide a dynamical model to describe the random behavior of power prices where the only non-Brownian component of the motion is endogenously introduced by Markov transitions in the exponent of the electricity supply curve. In this context, the stochastic process driving the switching mechanism becomes observable, and we will show that the non-Brownian component of the dynamics induced by transitions from Markov states is responsible for jumps and spikes of very high magnitude. The empirical analysis performed on three Australian markets confirms that the proposed approach seems quite flexible and capable of incorporating the main features of power prices time-series, thus reproducing the first four moments of log-returns empirical distributions in a satisfactory way.     

Investment in electricity networks with transmission switching

We consider the application of Dantzig-Wolfe decomposition to stochastic integer programming problems arising in the capacity planning of electricity transmission networks that have some switchable transmission elements. The decomposition enables a column-generation algorithm to be applied, which allows the solution of large problem instances. The methodology is illustrated by its application to a problem of determining the optimal investment in switching equipment and transmission capacity for an existing network. Computational tests on IEEE test networks with 73 nodes and 118 nodes confirm the efficiency of the approach.     

A market-based approach for enabling inter-area reserve exchange

Considering the sequential clearing of energy and reserves in Europe, enabling inter-area reserve exchange requires optimally allocating inter-area transmission capacities between these two markets. To achieve this, we provide a market-based allocation framework and derive payments with desirable properties. The proposed min-max least core selecting payments achieve individual rationality, budget balance, and approximate incentive compatibility and coalitional stability. The results extend the works on private discrete items to a network of continuous public choices.