Forrest D. Holland

U.S. Agricultural Policy and Gasohol: A Policy Simulation

This research uses a stochastic simulation model to evaluate the implications of alternative gasohol programs for a large segment of the food and agricultural sector-corn and soybean producers, consumers, and taxpayers. The impacts on corn and soybean prices, production, acreage planted, carryover stocks, exports, and commodity program expenditures are presented. The research findings indicate that alcohol production levels below 2.0 billion gallons do not result in serious dislocations in the agricultural sector. As the level of alcohol production increases and more grain is required, corn prices rise significantly, stocks fall to extremely low levels, exports decline, and government expenditures increase greatly.

A large oligopoly competition model with an application to the Midwest electricity markets

This paper presents a large spatial gaming model with price caps for the Midwest electricity markets. Price caps are enforced in several deregulated regional electricity markets in the USA, a logical step is to reflect this reality in imperfect competition modeling. Unfortunately, most current gaming models have not included any price cap formulation. This paper is one of the first to address the issue. A transportation formulation is used for representing the spatial nature of an electrical network. An algorithm is proposed to find a Nash equilibrium under the enforcement of price caps based on the Kuhn-Tucker vector optimization theorem. Case studies show the successful application of the model. The conclusion is that, given appropriate price caps, market power impact can be reduced in the short run.

Modeling Regional CO2 Control in Energy Production with Cap & Trade Regulation

This paper describes the modeling of CO2 cap & trade among coal power plants. A regional approach is used to include CO2 emission restriction (or cap) and trade in electrical power production. The model accommodates multiple nodes, each with its own demand growth, existing capacity, transmission lines connecting the nodes, and sequestration sites. Technologies for CO2 capture are assumed available to all nodes at the same price tag. Mixed integer programming (MIP) is used: binary variables are used for new construction of either power plants, or transmission, or CO2 pipelines, while continuous variables are used for representing others such as power production, CO2 generation, etc. The objective is to minimize regional cost of meeting nodal demands under assumed CO2 cap & trade regulation and other practical constraints.

CO/sub 2/ capture cost estimates from a state perspective: part I - regulation on GHG emissions & technologies

These are two joint papers on CO2 capture cost and price estimates for new power plants. Part I of the joint papers first discusses recent regulatory development in green house gasses (GHG) emissions. It shows that regional CO2 cap & trade systems may be in place in a few years in the US despite the fact that the US federal government has failed to pass any law on the issue. It then reviews current technologies for CO2 emissions control, especially those for new coal power plants. Capital and O&M cost estimates are also provided. Part II provides the estimates of electricity cost for the state of Indiana under various assumptions

The projected impacts of NOx emissions reductions on electricity prices: a case study for the State of Indiana

Abstract This paper examines the impact of various nitrogen oxides (NOx) emission control scenarios on the price of electricity. Specifically, various scenarios are presented to illustrate the price impacts for the state of Indiana. The scenarios represent different methods for reducing NOx emissions levels to either 0.15 or 0.25 lb/mmBtu. The analyses were performed using a traditional regulation forecasting model that equilibrates between price and demand. Thus, the effects of price changes on demand levels were captured. Price impacts are presented at an overall average level as well as by customer class. The impacts of various assumptions made in the selection of the scenarios are analyzed.