Economy-wide Estimates of Rebound Effects: Evidence from Panel Data

Energy consumption and greenhouse emissions across many countries have increased overtime despite widespread energy efficiency improvements. One explanation offered in the literature is the rebound effect (RE), however there is a debate about the magnitude and appropriate model for estimating RE. Using a combined stochastic frontier analysis and two-stage dynamic panel data approach for 55 countries covering 1980-2010, we explore these two issues of magnitude and model. Our central estimates indicate that, in the short-run, 100% energy efficiency improvement is followed by 90% rebound in energy consumption, but in the long-run it leads to a 36% decrease in energy consumption. Overall, our estimated cross-country RE magnitudes indicate the need to consider or account for RE when energy forecasts and policy measures are derived from potential energy efficiency savings

Integration of the environmental management aspect in the optimization of the design and planning of energy systems

The increasing concerns regarding the environmental pollution derived from anthropogenic activities, such as the use of fossil fuels for power generation, has driven many interested parties to seek different alternatives, e.g. use of renewable energy sources, use of “cleaner” fuels and use of more effective technologies, in order to minimize and control the quantity of emissions that are produced during the life cycle of conventional energy sources. In addition to these alternatives, the use of an integrated procedure in which the environmental aspect will be taken into account during the design and planning of energy systems could provide a basis on which emissions reduction will be dealt with a life cycle approach. The work presented in this paper focuses on the examination of the possibilities of integrating the environmental aspects in the preliminary phase of the conventional design and planning of energy systems in conjunction with other parameters, such as financial cost, availability, capacity, location, etc. The integration of the environmental parameter to the design is carried out within a context where Eco-design concepts are applied. Due to the multi-parameter nature of the design procedure, the tools that are used are Life Cycle Analysis and Multi-criteria Analysis. The proposed optimization model examines and identifies optimum available options of the use of different energy sources and technologies for the production of electricity and/or heat by minimizing both the financial cost and the environmental impacts, with regard to a multiple objective optimization subject to a set of specific constraints. Implementation of the proposed model in the form of a case study for the island of Rhodes in Greece revealed that an optimized solution both cost and environmental-wise, would be an almost balanced participation of renewables and non-renewable energy sources in the energy mix

Comparative review of the Time-stepped Energy System Optimization Model (TESOM) and the IEA Market Allocation Model (MARKAL)

The two principal energy system models used in the National Center for Analysis of Energy Systems at Brookhaven National Laboratory are described and their important differences are contrasted

Demand elasticity representation: methodology and calibration

This paper describes the methodology incorporated within a version of the Brookhaven Energy System Optimization Model (BESOM) to yield first-order approximations of the response of a national energy system, in economic equilibrium, to changes in prices, quantity of fuel available, and changes in the technological structure of the energy-conversion devices - including efficiency changes. The methodology is not intended as a substitute for the comprehensive energy-economic analysis derivable from the BNL Dale Jorgenson Associates suite of models. It is intended as an inexpensive tool for performing firsr-order sensitivity of energy systems around an established energy-economic equilibrium point

Methods of mathematical programming to program planning and R and D strategies

This paper discusses how some methods of mathematical programming might effectively be used to guide R and D planning with respect to total budget; budget distribution between supply and demand technologies; budget distribution among competing technologies; and budget distribution in light of the need to diversify and avoid risk. The discussion is limited to special frameworks such as linear programming, mixed-integer programming, and quadratic programming since they are most characteristic of the state-of-the-art energy-system formulations. Market penetration, the treatment of vintage stock, and the introduction of uncertainty in these modeling frameworks are key features that lend credibility to the well-known techniques applied for technology assessment, cost-benefit analysis, and multi-criteria analysis. 21 references

Comparative assessment of five long-run energy projections.

This rport compares five major long-term forecasts prepared under similar assumptions by: Professor George Dantzig's PILOT Process Integrated Model/Welfare Equilibrium Model system (PILOT); Professor Alan S. Manne's ETA-MACRO energy-economy model system; The combined Brookhaven National Laboratory/Dale W. Jorgenson Associates (BNL/DJA) energy-economy model system; The FOSSIL2 energy model operated by the Office of Policy and Evaluation in the Department of Energy; The Long-range Energy Analysis Package energy model ARC-78 (LEAP), operated by the Energy Informaion Administration in the Department of Energy. After summarizing the method of preparation of each forecast, the report compares the results in detail and explains the differences both in terms of data assumptions and methodological approach