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.     

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.     

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.     

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.     

Prices

Assessed or estimated prices and values for the major types of crude oils traded on spot markets. Updated on a monthly basis. Official sales prices (except as otherwise noted) and are generally market-related, subject in some cases to retroactive adjustment. Updated on a monthly basis.     

Territorial targeting in EU private law

In a series of rulings given in the last few years, the Court of Justice of the European Union (EU) has made use of the concept of targeting by a trader of a particular territorial market as a device for determining the scope of European legislation on private law. The concept is of particular importance in the context of trading activities conducted by means of the Internet, though its significance is not confined to such activities. In particular, the European Court has used the concept of targeting for the purpose of restricting the substantive ambit of intellectual property rights created or harmonised by EU legislation. On the other hand, it has avoided use of the concept of targeting in the context of EU legislation allocating jurisdiction between the courts of the Member States, even in respect of disputes involving intellectual property, except where a legislative text specifically invokes such a concept. The instant paper endeavours to review the position as currently established by the European case-law, and to predict the likely further developments.     

Trust in consumer-to-consumer electronic commerce

We developed a model of consumer-to-consumer (C2C) e-commerce trust and tested it. We expected that two influences: internal (natural propensity to trust [NPT] and perception of web site quality [PWSQ]) and external (other's trust of buyers/sellers [OTBS] and third party recognition [TPR]) would affect an individual's trust in C2C e-commerce. However contrary to studies of other types of e-commerce, support was only found for PWSQ and TPR; we therefore discussed possible reasons for this contradiction. Suggestions are made of ways to help e-commerce site developers provide a trustworthy atmosphere and identify trustworthy consumers.     

VirtuE: a formal model of virtual enterprises for information markets

A vital part of a modern economy is an information market. In this market, information products are being traded in countless ways. Information is bought, modified, integrated, incorporated into other products, and then sold again. Often, the manufacturing of an information product requires the collaboration of several participants. A virtual enterprise is a community of business entities that collaborate on the manufacturing of complex products. This collaboration is often ad hoc, for a specific product only, after which the virtual enterprise may dismantle. The virtual enterprise paradigm is particularly appealing for modeling collaborations for manufacturing information products, and in this paper we present a new model, called VirtuE, for modeling such activities. VirtuE has three principal components. First, it defines a distributed infrastructure with concepts such as members, products, inventories, and production plans. Second, it defines transactions among members, to enable collaborative production of complex products. Finally, it provides means for the instrumentation of enterprises, to measure their performance and to govern their behavior.