Using AURORAxmp to Meet Renewable Portfolio Standards (RPS)

According to the National Renewable Energy Laboratory (NREL), a renewable portfolio standard (RPS) is a “regulatory mandate to increase production of energy from renewable sources such as wind, solar, biomass and other alternatives to fossil and nuclear electric generation.” In 1983, Iowa became the first US state to adopt a renewable portfolio standard. In the last two decades, over half of the states in the country have adopted some form of RPS. Below is a chart displaying renewable capacity additions by state between 2000 and 2015:


Source: Lawrence Berkeley National Laboratory

Though RPS can be enforced in several ways, the mandates typically require utilities to provide some level of electric supply with renewable energy. The federal government, and sometimes state & local governments, provides financial incentives, often in the form of tax credits or rebates, to encourage investment in renewable energy. According to the Lawrence Berkeley National Laboratory, 60% of renewable electricity generation and 57% of renewable capacity builds since 2000 are tied to RPS mandates. The ultimate goal of these policies is to migrate away from fossil fuel generation in an attempt to reduce carbon and other various emissions.

AURORAxmp provides the flexibility to model various state RPS mandates and can be used to measure the impact of RPS standards on system cost, zonal prices, and emission reductions. The built-in constraint logic is used to easily specify the minimum amount of electric generation needed to meet any specified fleet of resources. Multiple parameters apply the constraint geographically as well; for example, RPS constraints can be applied on a local, state, and national level, and the model will solve all of them in the same run.

RPS constraints can also be defined in the form of renewable capacity rather than electric generation. For example, the Clean Power Plan (CPP), proposed by the EPA last year, contains several intricate details that specify how conventional fuel generators will be required to operate, both individually and as a group. Any capacity or generation constraints can be used in conjunction with a variety of other defined limits, such as emission rates, restrictions on fuel usage, and limitations on capacity factors. Additionally, these constraints are fluidly incorporated into various types of studies, such as long-term capacity expansion, risk, and scenario analysis. Below is a chart created using AURORAxmp to estimate the total system cost of different programs:


Generation attributed to RPS is expected to double by 2030 in the United States. As we look into the future, it is evident that the integration of renewable energy will continue to be a major point of interest in power markets. AURORAxmp offers an easy, reliable, and robust tool to analyze the impact of additional renewable generation on resources, the environment, and the electric grid.

Filed under: Renewable Portfolio StandardsTagged with: , , ,