Journal of Energy Engineering

This paper analyzes the effects of allocating $\mathrm{C}{\mathrm{O}}_2$ permits to new power plants free of charge within a tradable permit system. We demonstrate that these free allocations distort investments. Furthermore, we distinguish the effects of a uniform benchmark from a fuel specific benchmark, as both are common elements in EU member states’ national allocation plans. An empirical model for the European market is used to quantify the effects in a realistic framework.

The European Union has implemented the European Union emission trading scheme (EU ETS) as an instrument to facilitate greenhouse gas (GHG) emission abatement stipulated in the Kyoto protocol. Empirical data show that in the early stages of the EU ETS, the value of a ton of ${\mathrm{CO}}_2$ has already led to emission abatement through switching from coal to gas in the European electric power sector. In the second part of this paper, an electricity generation simulation model is used to perform simulations on the switching behavior in both the first and the second trading periods of the EU ETS. In 2005, the reduction in GHG emissions in the electric power sector due to EU ETS is estimated close to $88\mathrm{Mton}$ . For the second trading period, a European Union allowance (EUA) price dependent GHG reduction curve has been determined. The obtained switching potential turns out to be significant, up to $300\mathrm{Mton}$ /year, at sufficiently high EUA prices.

The paper considers high and differentiated uncertainties associated with greenhouse gas inventories in the context of compliance evaluation in an emission trading program. One common approach adopted in the literature is to discount tradable permits for uncertainty. Following this general idea, we derive exact rules for markets using such permits—we call them effective permits. First, permit allocation to each market participant is adjusted based on the inventory uncertainty and the acceptable risk of noncompliance. Second, original emission permits are recalculated into effective permits, reflecting individual inventory uncertainty and the risk of noncompliance as well. We then illustrate emission adjustments and effective permits to two trading schemes. Since the derived market rules assume nonstochastic distribution of uncertainty, we also discuss the choice of the risk level, which accounts for stochastic uncertainty distribution.

This study conducted a life-cycle inventory analysis of wind energy utilization in Taiwan. Life-cycle stages of wind turbine manufacturing, foundation construction, as well as operation and disposal of the systems are considered. The functional unit is defined as per kWh of electricity generated by the wind power systems. In 2006, the electricity generated from wind power systems stands at 0.124% of the total electricity supply in Taiwan. Moreover, the estimated potential capacity of wind energy inland falls within the range of $\mathrm{1,656}\text{to}\mathrm{6,624}\mathrm{MW}$ . The resource inputs resulting from the life-cycle inventory analysis are: Steel $1.847\mathrm{g}$ , aluminum $0.043\mathrm{g}$ , copper $0.043\mathrm{g}$ , sands $0.045\mathrm{g}$ , glass $0.067\mathrm{g}$ , plastics $0.068\mathrm{g}$ , petrochemical products $0.024\mathrm{g}$ , and concrete $6.515\mathrm{g}$ (per kWh of electricity generated). The intensities of energy consumption and $\mathrm{C}{\mathrm{O}}_2$ emission amount to about $0.05\mathrm{MJ}∕\mathrm{kWh}$ and $3.6\mathrm{g}∕\mathrm{kWh}$ , respectively. Furthermore, the payback time of energy input is estimated as $1.3\text{months}$ .

Introduction of photovoltaic (PV) systems, also known as solar cell systems, reduces greenhouse gasses (GHGs) emission, by substituting a part of the GHG intensive generation with GHG-free generation during effective daylight hours. Because power is generated from different kinds of power plants operated with momentarily changing proportion, consideration of resulting changes in the power mix is needed to correctly estimate the reduction potential of a large scale introduction scenario. In this paper, a linear mathematical programming model is constructed to simulate a power mix for a given power demand under a cost minimization objective. Using the model, GHG emission reduction potentials at different scales of PV introduction were calculated assuming an ideal solar irradiation. A comparison of daily power generation before and after the introduction indicates that reduction potentials calculated with averaged GHG emission factor could result in errors, because PV systems neither replace averaged nor the single kind of power generations, but affects the entire power mix and reduces fossil fuel consumption. It is shown that the GHG emission reduction per kWh of power generated by PV differs at different capacities of installation. Namely, for the initial introduction stage, reduction would be close to fossil fuel fired power plant average for an introduction range less than $1\mathrm{GWp}$ .

Cost-effective policy on renewable energy could be made based on information of renewable energy industry development and carbon dioxide control strategy. To analyze the interaction of renewable energy policy with ${\mathrm{CO}}_2$ control strategy, we developed a recursive linear planning model. The year 2004 is set as the base year. The target years are 2015, 2025, 2035, and 2045. Fujian province in China is selected as a case for the study. Calculation results show that in some instances, renewable energy subsidy policy and clean development mechanism incentive could not drive the market as policy makers expected. Careful design is required for renewable energy policy and carbon dioxide control policy, especially for developing countries. This study shows that a recursive linear program could be applied to an integrated study of renewable energy policy and carbon dioxide control policy.

This paper critically reviews the current requirement for a 10% offset of carbon emission that should be obtained from on-site renewable and other carbon-saving energy sources installed in new office buildings in London built environment. Carbon saving effects of several currently available renewable-based generation technologies for use in contemporary office developments are calculated and compared in the paper. In order to allow direct and transparent comparison, the paper proposes a new index, expressed as the ratio of the total carbon dioxide offset with the total cost of technology, calculated over the lifetime period of use. The presented results include sensitivity analysis of the following parameters and factors of influence: Capital costs of technologies, availability of primary energy sources, system efficiencies, and system losses. The paper also provides a discussion of the possible changes in the current carbon offset legislation and future carbon mitigation policy implications.