تجزیه و تحلیل پویا ایجادکنندگان سیاست برای بازار کالا انرژی زیستی

Biomass is increasingly being considered as a feedstock to provide a clean and renewable source of energy in the form of both liquid fuels and electric power. In the United States, the biofuels and biopower industries are regulated by different policies and have different drivers, which impact the maximum price the industries are willing to pay for biomass. This article describes a dynamic computer simulation model that analyzes future behavior of bioenergy feedstock markets given policy and technical options. The model simulates the long-term dynamics of these markets by treating advanced biomass feedstocks as a commodity and projecting the total demand of each industry, as well as the market price over time. The model is used for an analysis of the United States bioenergy feedstock market that projects supply, demand, and market price given three independent buyers: domestic biopower, domestic biofuels, and foreign exports. With base-case assumptions, the biofuels industry is able to dominate the market and meet the federal Renewable Fuel Standard (RFS) targets for advanced biofuels. Further analyses suggest that United States bioenergy studies should include estimates of export demand in their projections, and that GHG-limiting policy would partially shield both industries from export dominance.

The use of biomass as a feedstock for energy production is one option to provide a clean, renewable, and domestic source of energy. Although biomass is a renewable resource, the amount that can be grown sustainably and accessed economically is limited (US Department of Energy (DOE), 2011a). In the United States (US), growth in the use of biomass feedstocks for energy production is increasingly being driven by governmental policies such as Renewable Fuels Standard (RFS) for biofuels production and Renewable Portfolio Standards (RPS) for biopower production (Sorda et al., 2010 and US Department of Energy (DOE), 2010). However, the future size and strength of the bioenergy industry in the US is uncertain in the face of high values for biomass overseas that may drive up domestic prices for processed bioenergy feedstocks. Additionally, the potential for greenhouse gas (GHG)-limiting legislation creates uncertainty for investors in bioenergy and could disproportionately change the value of biomass for biopower compared to biofuel. The US Department of Energy (DOE) is investigating the utility of a commoditized uniform format for bioenergy feedstocks, which would expand access to many biomass industries and biomass resources, help minimize market volatility, and reduce risk to both biorefineries and biomass producers (Hess et al., 2009 and Searcy and Hess, 2010). While the uniform format removes some risk and limits to growth of bioenergy, it may enhance direct competition for bioenergy feedstocks among biopower, biofuels, and exporters. Therefore, as government and industry focus on the use of biomass as a commoditized feedstock for clean and renewable energy production, a need arises for techno-economic analysis regarding the effect of policies and strategies on the sustainability of multiple bioenergy industry sectors. This study analyzes the emerging bioenergy industry by investigating patterns in the behavior of bioenergy feedstock markets given a range of technical and policy options. The article begins with a review of bioenergy technologies and policies that are creating a commodity market for bioenergy feedstocks. The core of the article presents the Bioenergy Market Model, which simulates the primary causes of growth in bioenergy feedstock markets and furthermore presents simulated scenarios that describe the effect of technologies and policies on three bioenergy industries: biopower, biofuels, and exports. This model also presents a graphical method of analyzing the dynamic allocation of commodities to multiple buyers given a revenue-maximizing supplier and allowing for supply or demand-limiting conditions. This is a new approach to dynamic market allocation that attempts to quantify instantaneous demand vs. price curves for potential buyers. Scenarios are presented that show a wide range of behaviors for the bioenergy feedstock market based on assumptions about the implementation of current bioenergy policy, the strength of export markets, the bioenergy technologies used, and the effects of greenhouse gas (GHG)-limiting legislation.