Marginal cost and congestion in the Italian electricity market: An indirect estimation approach

In this paper we construct an indirect measure of the supply marginal cost function for the main generators from the observed bid data in the Italian electricity market in the period 2004–2007. We compute the residual demand function for each generator, taking explicitly into account the issue of transmission line congestion. This procedure allows recovering correct zonal Lerner index and the implied measure of the marginal cost function. We find evidence of a stable U-shaped marginal cost function for three main Italian generators, but a flat function for ENEL, the former national monopolist. The policy relevance of our approach lies in the possibility to offer some empirical knowledge of the marginal cost function of each generator to the regulator to design appropriate policy measures geared to the promotion of competitive market conditions. We propose a new market surveillance mechanism, which is based on the principle of sanctioning excessive deviations from the estimated measure of the marginal cost function presented in this work.     

遗传算法在期货市场创新决策中的应用

研究了遗传算法在期货市场创新决策中的应用问题，在期货市场的保值者和投资者数目以及期货合约结构模型的基础上，设计了期货市场创新的染色体表达和遗传操作并进行了仿真研究。     

Small-scale CDM projects in a competitive electricity industry: How good is a simplified baseline methodology?

Setting baseline emissions is one of the principal tasks involved in awarding credits for greenhouse gas emission (GHG) mitigation projects under the Clean Development Mechanism (CDM). An emission baseline has to be project-specific in order to be accurate. However, project-specific baseline calculations are subject to high transaction costs, which disadvantage small-scale projects. For this reason, the CDM-Executive Board (CDM-EB) has approved simplified baseline methodologies for selected small-scale CDM project categories. While the simplified methods help reduce the transaction cost, they may also result in inaccuracies in the estimation of emission reductions from CDM projects. The purpose of this paper is to present a rigorous economic scheduling method for calculating the GHG emission reduction in a hypothetical competitive electricity industry due to the operation of a renewable energy-based power plant under CDM and compare the GHG emission reduction derived from the rigorous method with that obtained from the use of a simplified (i.e., standardized) method approved by the CDM-EB. A key finding of the paper is that depending upon the level of power demand, prices of electricity and input fuels, the simplified method can lead to either significant overestimation or substantial underestimation of emission reduction due to the operation of renewable energy-based power projects in a competitive electricity industry.     

期货市场促进“铜冠”牌阴极铜创国际品牌

文章介绍了期货交易所由于其特殊的机制,而对其注册上市产品的质量提高有显著的促进作用,同时介绍了“铜冠”牌阴极铜在LME注册成功,取得进入国际市场通行证中的一些情况。     

石油价格机制改革之对策

文章在阐述我国石油价格形成机制的演变过程的基础上,针对我国目前石油定价机制所导致的诸如石油价格变动滞后以及由此带来的市场信号失灵等问题思考了相应的改革对策,提出了调整政府价格管理职能、建立平等竞争的市场规则、完善稳定油价的调控体系以及加快建立石油战略储备等7个方面的建议。     

The Influence of Immigration on Global City Housing Markets: The Canadian Perspective

Current demographic trends in Canada include population aging and declining household growth. These trends generally result in falling housing demand and stable or declining house prices. Housing markets in Canada's major cities, however, have been characterized by increases in demand and prices in recent years; due in large part to the influence of arriving immigrants. The destinations of 76 percent of international immigrants to Canada are the three global cities—Toronto, Vancouver and Montreal—where they have a very significant effect on housing demand, particularly as under current immigration policy many of those arriving come with considerable wealth. Their influence, however, is much broader and includes the growth of exclusive, prosperous immigrant neighbourhoods, new architectural designs and other neighbourhood changes. Not all immigrants, however, arrive with wealth. Many are poor, live in less attractive neighbourhoods and pay unrealistic amounts of their inadequate incomes for poor quality housing. Some end up homeless on the street. The role of immigrants in housing markets is an important consideration for urban and housing policy.     

Multiobjective invasive weed optimization: Application to analysis of Pareto improvement models in electricity markets

This paper presents a proposal for multiobjective Invasive Weed Optimization (IWO) based on nondominated sorting of the solutions. IWO is an ecologically inspired stochastic optimization algorithm which has shown successful results for global optimization. In the present work, performance of the proposed nondominated sorting IWO (NSIWO) algorithm is evaluated through a number of well-known benchmarks for multiobjective optimization. The simulation results of the test problems show that this algorithm is comparable with other multiobjective evolutionary algorithms and is also capable of finding better spread of solutions in some cases. Next, the proposed algorithm is employed to study the Pareto improvement model in two complex electricity markets. First, the Pareto improvement solution set is obtained for a three-player oligopolistic electricity market with a nonlinear demand function. Then, the IEEE 30-bus power system with transmission constraints is considered, and the Pareto improvement solutions are found for the model with deterministic cost functions. In addition, NSIWO algorithm is used to analyze this system with stochastic cost data in a risk management problem which maximizes the expected total profit but minimizes the profit risk in the market.     

Local distributions of electricity demand

A simple model for how electricity use might be distributed over space is developed and solved. The model depends on a simple characterization of “heat islands”, and considers summer cooling use in particular. Various technological changes to allow for electric grid use of renewable energy and other technologies, such as energy efficiency and hydrogen or electric vehicles, change the outcome of this model, and produce a “saddle”, not necessarily a “duck curve”. Inequality in income and wealth drives these results, and policies to ameliorate or remove these effects will have to be and be seen as fair to those of various income levels and locations.     

Geomorphic diversity as a river management tool and its application to the Ganga River,India

Understanding of geomorphic processes and the determination of geomorphic diversity in catchments are prerequisites for the sustainable rehabilitation of river systems and for reach‐scale assessment of river health. The Ganga River system in India is a large, complex system consisting of several long tributaries, some >1,000 km, originating from 2 distinct hinterlands—the Himalaya to the north and the cratons to the south. Traversing through a diverse climatic regime across the Plain and through precipitation zones ranging from 600 mm/year near Delhi to 1,200 mm/year in the eastern plains, the Ganga River system has formed very diverse landform assemblages in 3 major geomorphic domains. We have recognized 10 different river classes for the trunk river from Gangotri (source) to Farakka (upstream of its confluence with the Brahmaputra) based on (a) landscape setting, (b) channel and active floodplain properties, and (c) channel planform parameters. The mountainous stretch is characterized by steep valleys and bedrock channels and is dominated by large‐scale sediment production and transport through hill slope processes. The alluvial part of the river is characterized by 8 different river classes of varying reach lengths (60–300 km) many of which show sharp transitions in landscape setting. We have highlighted the application of this approach for the assessment of habitat suitability, environmental flows, and flood risk all of which have been significantly modified during the last few decades due to large‐scale anthropogenic disturbances. We suggest that the diversity embedded in this geomorphic framework can be useful for developing a sustainable river management programme to “work with” the contemporary character and behaviour of rivers.     

Evaluation of two alternative carbon capture and storage technologies: A stochastic model

In this paper we evaluate two alternative CCS technologies at a coal-fired power plant from an investor's point of view. The first technology uses CO₂ for enhanced oil recovery (EOR) paired with storage in deep saline formations (DSF) and the second merely stores CO₂ in DSF. The paper updates and improves on an earlier publication by Tzimas et al. (2005). For projects of this type there are many sources of risk, three of which stand out: the price of electricity, the price of oil and the price of carbon allowances. In this paper we develop a general stochastic model that can be adapted to other projects such as enhanced gas recovery (EGR) or industrial plants that use CO₂ for either EOR or EGR with CCS. The model is calibrated with UK data and applied to help understand the conditions that generate the incentives needed for early investments in these technologies. Additionally, we analyse the risks of these investments. Investments with EOR and secondary DSF storage can only be profitable (NPV > 0) when there is a high long-term equilibrium price for oil of more than $56.38/barrel. When the investment decision can be made at any time, i.e. there is an option value, then the trigger value for optimal investment is significantly higher.