As consumers of electricity and gas in our homes, North Carolinians know that personal habits and decisions impact energy usage. It’s hard to be in the dark with so many tools available to help households understand and manage consumption: programmable thermostats and myriad “smart home” devices. It’s easy to see why these devices have taken hold, because with better information, consumers use less energy, and ultimately pay less in their monthly bill. Better energy management at home has a direct correlation to energy savings and cost savings, but there is another correlation that researchers at North Carolina Agricultural and Technical State University are trying to shed light on: smarter choices in power generation.
Consumers have little control where their energy comes from- that is a decision left up to the power companies who manage the grid. It stands to reason that the cheaper a power company can produce and distribute power, the lower energy costs would be. In addition, actual power generation data could be used to improve plant performance and reduce greenhouse gas emissions. So what kind of information is available to help a power company make smart decisions?
Dr. Greg Monty, director of the Center for Energy Research and Technology and Dr. Marwan Bikdash, chair of the Department of Computational Engineering at N.C. A&T are trying to help North Carolina’s power companies understand their options. Since January 2016, Monty and Bikdash have been modeling the state’s energy usage to determine the best recipe for power generation. Grad student Aditi Bhalerao has been assisting their efforts.
“In the summer of 2015, President Obama and the Environmental Protection Agency finalized the Clean Power Plan,” explains Dr. Monty. “It called for a 30% reduction in power plant carbon emissions by the year 2030. The CPP gives states a lot of flexibility in how to go about achieving the reduction, which is why we started thinking about modeling different scenarios to help North Carolina achieve an optimum result.”
The state’s power data is publicly-available information, and by using actual energy generation and emissions data from the Energy Information Administration, the N.C. A&T researchers can look at every possible scenario. By inputting data for all plants in North Carolina (nuclear, coal, natural gas, hydro, solar, and wind) into their modeling resources, the team hopes to identify trends which will help power companies reduce costs, raise plant efficiencies and lower carbon emissions. The model will incorporate fluctuations in the prices of oil, natural gas, and other resources, and recommend the best mix of power generation under a variety of scenarios.
“No matter what the present administration’s opinion of climate change might be, or the immediate fate of the Clean Power Plan, it is just a matter of time before our state faces pressure to examine its practices or a different approach becomes economically more attractive”, says Dr. Marwan Bikdash. “In a way, this is the perfect time to address this! Without a high pressure mandate, North Carolina can carefully examine all the information, formulate a game plan and get a head start on creating cheaper, lower-polluting energy for the state.”
Data is being loaded into Matlab, a technical computing environment used by engineers and scientists. Gurobi Optimizer software is used to model the emissions. Monte Carlo simulations (computerized mathematical techniques that allow the researchers to account for risk in quantitative analysis and decision making) are used to generate thousands of power generation scenarios that can meet North Carolina’s energy demands. Finally, big data analytics are used to understand those promising scenarios that (1) meet the energy demand in the state, (2) would produce 30% reductions in carbon emissions by 2030, (3) while keeping the price of electricity low or very close to the 2017 cost of electricity in North Carolina.
“If we can provide modeling data that allows North Carolina to reduce its carbon emissions while still providing the energy needs of the state, at less cost, that would be a big win for all,” says Monty.
The university will complete its power generation modeling research this spring, with final results expected in June 2017. The researchers will make their findings available to the public, the North Carolina Utilities Commission, the state legislature and every North Carolina power company interested in lowering costs and reducing carbon emissions for the Tarheel state. The intent is to help leaders craft policy and practice that puts North Carolina in an energy leadership position in the nation.”