CO2 emissions trading planning in combined heat and power production via multi-period stochastic optimization

The EU emissions trading scheme (ETS) taking effect in 2005 covers CO₂ emissions from specific large-scale industrial activities and combustion installations. A large number of existing and potential future combined heat and power (CHP) installations are subject to ETS and targeted for emissions reduction. CHP production is an important technology for efficient and clean provision of energy because of its superior carbon efficiency. The proper planning of emissions trading can help its potential into full play, making it become a true “winning technology” under ETS. Fuel mix or fuel switch will be the reasonable choices for fossil fuel based CHP producers to achieve their emissions targets at the lowest possible cost. In this paper we formulate CO₂ emissions trading planning of a CHP producer as a multi-period stochastic optimization problem and propose a stochastic simulation and coordination approach for considering the risk attitude of the producer, penalty for excessive emissions, and the confidence interval for emission estimates. In test runs with a realistic CHP production model, the proposed solution approach demonstrates good trading efficiency in terms of profit-to-turnover ratio. Considering the confidence interval for emission estimates can help the producer to reduce the transaction costs in emissions trading. Comparisons between fuel switch and fuel mix strategies show that fuel mix can provide good tradeoff between profit-making and emissions reduction.     

Does EU ETS instigate Air Cargo network reconfiguration? A model-based analysis

From 2012 on aviation is included in the European Emissions Trading Scheme (EU ETS) and operators have to hold one allowance per tonne of CO₂ emitted on every flight departing from and/or arriving at an airport within the EU. Now two questions are of interest: Is it profitable for airlines to reconfigure their routes to reduce EU-related emissions and costs, and, will the scheme be successful in the sense that emissions are reduced significantly. Here the potential for and the consequences of reconfiguration are different for the passenger and cargo business, respectively. In this paper we present a model-based evaluation of network (re-)configuration/optimization at cargo airlines under different EU ETS scenarios and we discuss the results with respect to the two issues raised above.     

The emissions trading paradox

This article considers the price history of CO₂ allowances in the EU Emission Trading Scheme. Since European Emissions Trading started in 2005, the prices of allowances have varied between less than one and thirty Euro per ton of CO₂. This previously unpredicted volatility and, more notably, a significant price crash in May 2005 led to the hypothesis that electricity producers might use their market power to influence the prices of allowances. Besides market power, the combination of information asymmetry and price interdependencies (between prices of primary goods – especially electricity – and allowances) plays an important role in explaining the emissions trading paradox. The model presented will show that banking can lead to such a price crash if market participators act rationally. Furthermore, in such a scenario banking can be profitable for sellers at the cost of buyers.     

ENERGY‐USE CHOICES AND ALLOWANCE TRADING UNDER THE PERSONAL CARBON TRADING SCHEME

Carbon emissions caused by the household sector have become a major contributor to total emissions. Personal carbon trading (PCT), although untested in practice, could potentially be a powerful tool to induce change in consumer behavior. In this paper, we present an optimization model to determine the energy use choices and allowance trading, and a market equilibrium model to obtain the total supply and demand functions of allowances and then to derive the equilibrium allowance price. It is shown that the level of allocated allowance, energy price, emission rate, and transaction costs could influence the equilibrium allowance price and traded volume. Furthermore, the allowance price is affected negatively and slightly by changes in energy prices, so the total energy price variations will be lessened relatively in the PCT scheme. To further demonstrate these relationships, numerical simulations are conducted. On the basis of the simulation results, the implications of this study are discussed and suggestions for future study are provided.     

Price dynamics in the European Union Emissions Trading System and evaluation of its ability to boost emission-related investment decisions

The price of permits in the European Union Emissions Trading System (EU ETS) has historically been highly sensitive and prone to jumps. We consider different stochastic processes to model the price of permits, and show that the Variance Gamma (VG) model provides the best fit for the price distribution, among a selection of infinite activity processes. Using this result as a starting point, we assess the effects of the EU ETS in delivering low-carbon investments at the firm level, by modeling a price taker electricity producer subject to the EU ETS jurisdiction. We compute, via Least Squares Monte Carlo, the value of the real option the greenhouse gas emitter has, consisting in the opportunity to switch from its current high-carbon technology to a cleaner one. We use a VG specification for carbon prices, and a mean-reverting (Brennan–Schwartz) process for the price of fuel. Moreover, we further analyze the investment decision problem, in case of a CO₂ price stabilization mechanism in the form of a price floor, by explicitly computing the expected value of the investment project by means of Fourier methods. Our results show that the introduction of the price stabilization mechanism significantly affects the timing of the investment decision, and supports emission-related investments.     

欧盟碳市场期货价格分布特征分析

市场价格的收益率特征是研究市场特点的出发点.从各类常见分布入手,检验了欧盟碳市场的真实分布特性,最终发现稳态分布最适宜于描述碳市场的收益率分布.据此,讨论了欧盟碳市场的信息传递与风险评价特点.     

基于Copula的QDII与排放权资产的投资组合构建

本文介绍了欧盟温室气体排放权交易市场,选择欧洲气候交易所(ECX)推出的欧盟配额(EUA)期货合约作为温室气体排放权资产(即碳资产)的代表,利用Copula函数得到了国内一支QDII基金-南方全球精选基金与该资产收益率的联合分布,并进一步据此得到了两种资产任一组合的收益率的分布函数,然后在不同的显著性水平下确定了具有最小VaR的最优组合系数。对最优组合的分析发现,本文构建的投资组合在收益率高于原QDII基金收益率的同时,其VaR值在各种显著性水平下均低于原QDII基金的VaR,并且最优的组合系数对于特定的VaR水平的敏感度不高,组合策略具有可操作性。     

On the Modeling of CO2 EUA and CER Prices of EU‐ETS for the 2008–2012 Period

Increased consumption of fossil fuels in industrial production has led to a significant elevation in the emission of greenhouse gases and to global warming. The most effective international action against global warming is the Kyoto Protocol, which aims to reduce carbon emissions to desired levels in a certain time span. Carbon trading is one of the mechanisms used to achieve the desired reductions. One of the most important implications of carbon trading for industrial systems is the risk of uncertainty about the prices of carbon allowance permits traded in the carbon markets. In this paper, we consider stochastic and time series modeling of carbon market prices and provide estimates of the model parameters involved, based on the European Union emissions trading scheme carbon allowances data obtained for 2008–2012 period. In particular, we consider fractional Brownian motion and autoregressive moving average–generalized autoregressive conditional heteroskedastic modeling of the European Union emissions trading scheme data and provide comparisons with benchmark models. Our analysis reveals evidence for structural changes in the underlying models in the span of the years 2008–2012. Data‐driven methods for identifying possible change‐points in the underlying models are employed, and a detailed analysis is provided. Our analysis indicated change‐points in the European Union Allowance (EUA) prices in the first half of 2009 and in the second half of 2011, whereas in the Certified Emissions Reduction (CER) prices three change‐points have appeared, in the first half of 2009, the middle of 2011, and in the second half of 2012. These change‐points seem to parallel the global economic indicators as well. Copyright © 2016 John Wiley & Sons, Ltd.     

Unit commitment in electricity pool markets

We consider an electricity generator making offers of energy into an electricity pool market over a horizon of several trading periods (typically a single trading day). The generator runs a set of generating units with given start-up costs, shut-down costs and operating ranges. At the start of each trading period the generator must submit to the pool system operator a new supply curve defining quantities of offered energy and the prices at which it wants these dispatched. The amount of dispatch depends on the supply curve offered along with the offers of the other generators and market demand, both of which are random, but do not change in response to the actions of the generator we consider. After dispatch the generator determines which units to run in the current trading period to meet the dispatch. The generator seeks a supply function that maximizes its expected profit. We describe an optimization procedure based on dynamic programming that can be used to construct optimal offers in successive time periods over a fixed planning horizon.     

Timing and eco(nomic) efficiency of climate-friendly investments in supply chains

Emission trading schemes such as the European Union Emissions Trading System (EUETS) attempt to reconcile economic efficiency with ecological efficiency by creating financial incentives for companies to invest in climate-friendly innovations. Using real options methodology, we demonstrate that under uncertainty, economic and ecological efficiency continue to be mutually exclusive. This problem is even worse if a climate-friendly project depends on investing in of a whole supply chain. We model a sequential bargaining game in a supply chain where the parties negotiate over implementation of a carbon dioxide (CO₂) saving investment project. We show that the outcome of their bargaining is not economically efficient and even less ecologically efficient. Furthermore, we show that a supply chain becomes less economically efficient and less ecologically efficient with every additional chain link. Finally, we make recommendations for how managers or politicians can improve the situation and thereby increase economic as well as ecological efficiency and thus also the eco-efficiency of supply chains.     

Evaluating the impact of average cost based contracts on the industrial sector in the European emission trading scheme

The inception of the emission trading scheme in Europe has contributed to power price increases. Energy intensive industries have reacted by arguing that this may affect their competitiveness and will induce them to leave Europe. Taking up a proposal of these industrial sectors, we explore the possible application of special contracts, where electricity is sold at average generation cost to mitigate the impact of CO₂ cost on power prices. The model supposes fixed generation capacities. We first consider a reference model representing a perfectly competitive market where all consumers (industries and the rest of the market) are price-takers and buy electricity at short-run marginal cost. We then change the market design by assuming that energy intensive industries pay power either at a regional or at a zonal average cost price. The analysis is conducted with simulation models applied to the Central Western European power market. The models are implemented in GAMS/PATH. This work has been financially supported by the Chair Lhoist Berghmans in Environmental Economics and Management and by the Italian project PRIN 2006, Generalized monotonicity: models and applications, whose national responsible is Prof. Elisabetta Allevi.     

Environmentally friendly facility location with market competition

Many traditional facility location models assume spatial monopoly where market competition is ignored. Since facility locations affect the firm’s market exposure and subsequently its profit, accounting for the impact of the location decisions on customers while anticipating the reaction of competitor firms is essential. In this paper, we introduce a competitive facility location problem where market prices and production costs are determined through the economic equilibrium while explicitly considering competition from other firms. In order to accommodate for the growing efforts on limiting carbon emissions, the presented model includes constraints on the amount of carbon emissions that are due to transportation, while allowing carbon trading. The problem is formulated as a mixed integer non-linear model. Through numerical examples, we illustrate the effect of market competition on the location decisions and discuss the impact of emission limits and carbon trading on customers.     

A stochastic model for investments in different technologies for electricity production in the long period

We present a single stage stochastic mixed integer linear model for determining the optimal mix of different technologies for electricity generation, ranging from coal, nuclear and combined cycle gas turbine to hydroelectric, wind and photovoltaic, taking into account the existing plants, the cost of investment in new plants, maintenance costs, purchase and sale of ${CO}_2$ emission trading certificates and green certificates, in order to satisfy regulatory requirements. The power producer is assumed to be a price-taker. Stochasticity of future fuel prices, which affect the generation variable costs, is included in the model by means of a set of scenarios. The main contribution of the paper, beyond considering stochasticity in the future fuel prices, is the introduction of CVaR risk measure in the objective function in order to limit the possibility of low profits in bad scenarios with a fixed confidence level.     

Real options analysis of investment in carbon capture and sequestration technology

Among a comprehensive scope of mitigation measures for climate change, CO₂ capture and sequestration (CCS) plays a potentially significant role in industrialised countries. In this paper, we develop an analytical real options model that values the choice between two emissions-reduction technologies available to a coal-fired power plant. Specifically, the plant owner may decide to invest in either full CCS (FCCS) or partial CCS (PCCS) retrofits given uncertain electricity, CO₂, and coal prices. We first assess the opportunity to upgrade to each technology independently by determining the option value of installing a CCS unit as a function of CO₂ and fuel prices. Next, we value the option of investing in either FCCS or PCCS technology. If the volatilities of the prices are low enough, then the investment region is dichotomous, which implies that for a given fuel price, retrofitting to the FCCS (PCCS) technology is optimal if the CO₂ price increases (decreases) sufficiently. The numerical examples provided in this paper using current market data suggest that neither retrofit is optimal immediately. Finally, we observe that the optimal stopping boundaries are highly sensitive to CO₂ price volatility.     

Environmental considerations on the optimal product mix

Several types of regulations limit the amount of different emissions that a firm may create from its production processes. Depending on the emission, these regulations could include threshold values, penalties and taxes, and/or emission allowances that can be traded. However, many firms try to comply with these regulations without a systematic plan, often leading not only to emission violations and high penalties, but also to high costs. In this paper, we present two mathematical models that can be used by firms to determine their optimal product mix and production quantities in the presence of several different types of environmental constraints, in addition to typical production constraints. Both models are comprehensive and incorporate several diverse production and environmental issues. The first model, which assumes that each product has just one operating procedure, is a linear program while the second model, which assumes that the firm has the option of producing each product using more than one operating procedure, is a mixed integer linear program. The solutions of both models identify the products that the firm should produce along with their production quantities. These models can be used by firms to quickly analyze several “what if” scenarios such as the impact of changes in emission threshold values, emission taxes, trading allowances, and trading transaction costs.     

Australian electricity market and price volatility

Australian Electricity Market has experienced high price volatility since the deregulation in early 1990s. In this exploratory and preliminary analysis of 2010 data from South Australian electricity market we identify and exhibit a number of phenomena which, arguably, contribute to (A) high cost of electricity supply to consumers and (B) volatility in spot prices. These phenomena include: (i) Distinct bidding patterns of some generators occurring in trading intervals corresponding to periods of low, medium and high spot prices, (ii) Low correlation between electricity demand and spot prices on days when spot price spikes are observed, (iii) Failure of the lottery model and associated Markowitz-type optimisation approaches to adequately explain the shifting structure of generators’ bids and (iv) Unexpectedly high contribution to the consumers costs and risks from the relatively small number of trading intervals where spot price spikes were observed.     

Predicting ships' CO2 emissions using feature‐oriented methods

Shipping companies are forced by the current EU regulation to set up a system for monitoring, reporting, and verification of harmful emissions from their fleet. In this regulatory background, data collected from onboard sensors can be utilized to assess the ship's operating conditions and quantify its CO₂ emission levels. The standard approach for analyzing such data sets is based on summarizing the measurements obtained during a given voyage by the average value. However, this compression step may lead to significant information loss since most variables present a dynamic profile that is not well approximated by the average value only. Therefore, in this work, we test two feature‐oriented methods that are able to extract additional features, namely, profile‐driven features (PdF) and statistical pattern analysis (SPA). A real data set from a Ro‐Pax ship is then considered to test the selected methods. The data set is segregated according to the voyage distance into short, medium, and long routes. Both PdF and SPA are compared with the standard approach, and the results demonstrate the benefits of employing more systematic and informative feature‐oriented methods. For the short route, no method is able to predict CO₂ emissions in a satisfactory way, whereas for the medium and long routes, regression models built using features obtained from both PdF and SPA improve their prediction performance. In particular, for the long route, the standard approach failed to provide reasonably good predictions.     

Supporting hydrogen based transportation: case studies with Global MARKAL Model

Steadily growing prices of oil and emissions coming from conventional vehicles, might force a switch to an alternative and less polluting fuel in the coming future. In this article we analyze the potential influence of selected factors for successful market penetration of hydrogen fuel cell vehicles in hydrogen based private transportation economy. Using a world scale, full energy system, bottom-up, optimization model (Global MARKAL Model—GMM) we address the possibility of supporting the fuel cell vehicle technology to become competitive in the markets. In a series of optimizations we evaluate the potential influence of governmental supports and the internalization of externalities related to CO₂ and local pollution emissions originating from the transportation sector, as well as preferential crediting options and demonstration projects promoting fuel cell vehicles. The results suggest that the crucial element is the price of fuel cells and their further potential to reduce costs. This reduction of costs may be triggered by governmental support such as direct subsidies to fuel cells, preferential crediting options for the buildup of hydrogen infrastructure as well as penalization of emitters of CO₂ and/or local pollutants.     

Two-period pricing and decision strategies in a two-echelon supply chain under price-dependent demand

This paper presents a two-period supply chain model which is comprised of one manufacturer and one retailer who are involved in trading a single product. The demand rate in each period is dependent on the selling prices of the current period and the previous period. We assume that the manufacturer acts as the Stackelberg leader and declares wholesale price(s) to the retailer who follows the manufacturer’s decision and sets his selling prices for two consecutive periods. The manufacturer adopts one of the two pricing options: (1) setting the same wholesale price to both the selling periods (2) setting different wholesale prices to two different selling periods. Based on these pricing options, we develop four decision strategies of the manufacturer and the retailer and compare them. For a numerical example, we study the effects of these decision strategies on the optimal results of the supply chain. Further, we graphically analyze under what circumstances a particular decision strategy plays a dominant role.     

电力行业碳排放权资源影子价格模型:以海南为例

在电力行业碳排放受限情况下,碳排放权成为电力企业生产必须获取的一种资源。碳排放权资源影子价格可以成为排放权交易定价机制构建和碳税税率制订的重要参考。本文构建了以系统发电总成本最小化为目标的电力系统数学规划模型,利用对偶原理求解碳排放权的影子价格。以海南电网为案例,得到电力系统碳排放权的影子价格并分析了其主要影响因素。研究结果表明,碳排放权影子价格随着碳排放总量上限的降低呈现阶梯状增长走势。碳排放强度高的煤电和排放强度低的风电对排放权的影子价格影响截然相反。