by Stephanie Oehler
While energy production is widely acknowledged as a significant contributor to climate change, there is a discrepancy in opinion about what the most effective solution is to cut back on emissions. The most commonly addressed method of bringing about a smart grid is through new technologies that have the potential to improve distribution efficiency, encourage demand side management behaviors, and reduce the emissions associated with the production process. Policy change, however, is another route that has the potential to be more efficient in reducing emissions in the short term as technological developments are in progress. Li et al. (2013) examined the potential of several types of policy initiatives to modify electricity operator behavior in order to reduce CO2 emissions while continuing to meet energy demand. Basing their assumptions on the energy profile of Michigan, the authors created three models to represent different policy approaches: the first served as a baseline and represented the present energy cost and load distribution, the second imposed demand-side financial penalties for CO2 emissions, and the third created a carbon disincentive that produced a new pricing scheme for energy sources in terms of emissions.The models revealed that the carbon disincentive approach was the most successful in changing operator behavior because it increased the production costs associated with selling dirtier energy without raising prices considerably for consumers. The roles of plug-in electric vehicles (PEVs) and renewable wind energy were also examined, separately and together, and Li and colleagues concluded that the technologies were most beneficial when implemented jointly so that the low-cost, emission-free wind energy would supply the majority of the energy demand increase brought about by the PEVs, while the PEVs would serve as storage for wind energy produced in periods of low demand. Ultimately, the authors argued that a carbon disincentive program is the preferable policy measure to address carbon emissions because it is not a tax placed directly on carbon, but rather it restructures the costs of energy sources in order to incentivize suppliers to use cleaner sources first, even if it is more costly to do so.
Without external forces, energy suppliers are motivated by the cost of energy in deciding which sources to use to comprise the load that is demanded by their customers. Currently, nuclear power is the cheapest form of energy and does not result in measurable carbon emissions. As a result, nuclear power has been chosen by operators and approved of by environmentalists as the first power source, when available, to satisfy demand. In many areas, such as Michigan, the next most prevalent energy source is coal. Coal-fired power plants are among the heaviest polluting in terms of CO2 emissions per output of energy, but because coal is cheaper than alternative sources, it is used frequently. Natural gas is another common source and while slightly more expensive than coal, it has a smaller environmental impact. Other forms of renewable energy, such as wind power, are more expensive, or are unpredictable and are thus not commonly relied upon by energy suppliers. The dichotomy between price of power and CO2 emitted poses a challenge to those who are trying to reduce the environmental impacts of the electricity grid. Li and colleagues evaluated the success of different policy measures intended to change the tradeoff between emissions and costs so operators would use lower emitting energy sources first. They began by listing the assumptions behind their models. The hypothetical grid was price-inelastic, the grid operators were assumed to utilize cheaper power sources first, costs of reserves were considered, PEV characteristics were standardized, and emission data for each type of energy production, including wind, were acquired and interpreted. The authors used this information to evaluate the costs and emissions that resulted from the baseline scenario, the carbon penalization policy, and the carbon disincentive policy.
The baseline scenario did not take carbon emissions into consideration and produced a cost-minimizing sequence of energy sources. As a result, the first 2040 megawatts (MW) of power were nuclear, the subsequent 4800 were supplied from coal, and the remaining demand was satisfied with production from natural gas. The second model enacted a demand-side penalty based on emissions. The authors experimented with different prices for each ton of CO2 emitted, ranging from $10 to $55. While the penalty cost did alter behaviors, it created significant inconveniences for PEV owners who began charging their vehicles at different times and changing the demand composition. As a result, only moderate emission reductions were observed. The final model incorporated the supply-side targeting disincentive policy, which added between $0.05 and $20 to the generation cost incurred by power plants per ton of carbon emitted. The disincentive was thus felt by the grid-operators who revised the composition of their load based on the new prices for each type of power. The costs of renewable energy and other lower emitting sources became more affordable when compared to coal, and were thus increasingly relied upon to meet demand. Meanwhile, the cost of emissions was not felt considerably by the grid operator or consumers due to its “revenue return mechanism.” When the disincentive was $0.05 per ton of CO2, emissions were 0.13 percent lower and consumer cost increased 0.04 percent. When the disincentive was increased to $20 per ton, emission reductions increased to nearly 25 percent and cost increases almost reached 20 percent. More heavily polluting power plants were negatively impacted by the disincentive and experienced lower profits, while renewable energy producers saw higher profits.
The results of the models indicated that the disincentive policy was the most influential in reducing carbon emissions. By altering the composition of the power supply that utility operators used to meet consumer demand, this policy encouraged cost-driven suppliers to consult low-emitting sources before relying on higher polluting methods, such as coal-fired power plants. This method, as compared to the current scenario and the direct penalty option, altered behavior on the supply and demand sides and was significantly more effective in reducing CO2 emissions. The models also revealed the ability of PEV and wind power implementation to reduce emissions, and the authors concluded that the technologies should be implemented together in order to improve effectiveness. While the impacts of a carbon disincentive as applied in this study would render different results depending on the composition of energy sources in a geographical area, this policy approach could have significant impacts in the transition to smarter electricity grids.
Li, C., Peng, H., Sun, J., 2013. Reducing CO2 emissions on the electric grid through a carbon disincentive policy. Energy Policy, 793–802.