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Maryland Regional Greenhouse Gas Initiative (RGGI)

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HAIKU Model, Resources for the Future

RFF’s HAIKU electricity model simulates equilibrium in regional electricity markets and inter-regional electricity trade with an integrated algorithm for generation capacity investment and retirement and emissions control technology choice. The model has been used for a number of reports and articles that appear in the peer-reviewed literature. The model has been compared with other simulation models as part of two series of meetings of Stanford University’s Energy Modeling Forum.

The HAIKU model calculates electricity demand, electricity prices, the consumption of electricity supply, inter-regional electricity trading activity among 20 regions of the country, and emissions of key pollutants such as N0x, SO2, mercury and CO2 from electricity generation. Three customer classes are represented (residential, industrial, and commercial). Detailed demand functions and supply curves are calculated for four time periods (super-peak, peak, shoulder, and baseload hours) in each of three seasons (summer, winter, and spring/fall). Supply curves account for the vintage, emission rates, size and type of generation technology as well as the cost and characteristics of fuels. Investment in new generation capacity and retirement of existing facilities are determined endogenously, based on capacity-related costs of providing service in the future. Generator dispatch is based on minimization of short run variable costs of generation. The model includes fuel market modules for coal and natural gas that calculate prices that are responsive to factor demand.

The HAIKU model is able to characterize in a detailed manner regulatory institutions and the incentives they provide electricity generators. HAIKU accounts for the nature and pace of restructuring in the electricity industry, and a full menu of potential environmental policies regulating air emissions including performance standards, tradable permits, taxes and combinations thereof.

For additional information on the HAIKU Model please see:

Oligopolistic Power Model, Johns Hopkins University

Models formulated as complementarity problems have been applied previously to assess the potential for market power in transmission-constrained electricity markets. Here, we use the complementarity approach to simulate the interaction of pollution permit markets with electricity markets, considering forward contracts and the operating reserve market. Because some power producers are relatively large consumers of permits, there could be interaction between market power in the permits and energy markets. Market power in the energy market is modeled using a Cournot game, while a conjectured price response model is used in the permits market. An illustrative application is made to Pennsylvania—New Jersey—Maryland Interconnection (PJM), which we represent by a 14-node dc load-flow model, and the USEPA Ozone Transport Commission NOx Budget Program. The results show that forward contracts effectively mitigate market power in PJM energy market and both simulated solutions of perfect and Cournot (oligopoly) competition are a good approximation to actual prices in 2000, except that the Cournot model yielded higher peak prices. The NOx market influences the Cournot energy market in several ways. One is that Cournot competition lowers the price of NOx permits, which in turn affects on low- and high-emission producers differently. In general, because pollution permits are an important cost, high concentration in the market for such permits can exacerbate the effects of market power in energy markets.

For additional information on JHU's Oligopolistic Power Model please see:

IMPLAN Model, RESI of Towson University

In order to quantify the economic impacts of Maryland’s participation in the RGGI considered in the analysis, RESI will utilize its modified, IMPLAN input/output model. To quantify the economic impact of a change in expenditures (by both businesses and households), economists measure three types of impacts: direct, indirect, and induced. The direct impacts are generated as expenditures enter and/or exit the state’s retail or commercial markets. The indirect economic impacts occur as local firms either increase or decrease their purchases of goods and services from other, area firms. Both the direct and indirect impacts result in a change in employment that affects household income levels (which rise and fall as job growth/loss occurs). This change in income levels drives the induced economic impacts, which occur as households alter their purchases of local goods and services.

For additional information on the IMPLAN Model please see: