A new policymaking tool to better enable the shift to renewable energy has been developed by researchers at the University of California–Berkeley, and presented at an event at the University of Copenhagen.
Policymakers and planners need to discern the most efficient and effective means within the multiple choices and routes to cutting greenhouse gases and shifting away from fossil fuels. A new tool called “SWITCH” aids them in this process. It allows for better assessing of the economic and environmental implications of different policies, and a framework for investment of different renewable energy processes. Presented at the Global Challenges: Achieving Sustainability congress hosted by the University of Copenhagen, this brilliant tool could genuinely help speed up and make more efficient the shift to clean energy.
Professor Daniel Kammen. Photo Credit: Lizette Kabré.
“SWITCH is a tool we can use to examine the different choices of technologies within the electrical power sector and their locations. It enables us to estimate the impact on regional air pollution emissions, as well as how much land area, and water consumption would be needed for each scenario. We have used this model for different future energy scenarios across western North America, and we see an enormous variation in both the magnitude and location of environmental impacts,” explains doctoral candidate Tessa Beach.
Tessa and Professor Daniel Kammen, Director of Renewable and Appropriate Energy Laboratory, both from the University of California–Berkeley, together presented the idea of the tool at the Copenhagen event.
The University of Copenhagen press release adds: “The tool demonstrates that different energy scenarios with the same decarbonization target can make a difference of 108.000 [108,000] tons in annual air pollutant emissions or 1.2 million acres of land use; an area about twice the size as the country Luxembourg.”
“With this tool we can examine not only carbon emissions, but also those of other greenhouse gases, and as a result tease apart the cost-effectiveness of the scenarios as well as identify what and where impacts are likely to occur for a range of resources,” says Daniel Kammen.
At the event, Tessa Beach introduced results of the “interconnected grid system that encompasses the western United States, Alberta, British Columbia and northwest Mexico.” But the tool has been applied much more broadly already, with versions of SWITCH created for China, Chile, and Nicaragua; and coming versions for Mexico, India, and East Africa.
Incorporating natural gas prices, hydropower availability, the cost of solar and wind power, and much more, the tool offers a diverse and holistic look at different economic and policy options.
The SWITCH model can be aimed at identifying the most cost-effective choices, the generation needed, the transmission needed, and the storage options for proposed electricity systems.
“Transmission terrain cost multiplier between pairs of load zones. The most costly routes to build are the ones with the highest value for the cost multiplier. The largest capacity substation in each load area is depicted by a black dot. The cost multipliers depicted here are not normalized by the factor of 1.50 described above.”
“SWITCH uses time-synchronized load and renewable generation data to evaluate future capacity investments while ensuring that load is met and policy goals are reached at minimum cost. The optimization is formulated as a deterministic linear program, which is solved by standard commercial software,” a UC-Berkeley website connected to the project states.
There is a persuasive argument to move beyond a singular focus on carbon reductions. It is a useful first step, but Alexis Laurent from the Technical University of Denmark has shown that carbon emission is a poor metric for overall environmental impact:
‘We know that carbon footprint, a popular indicator used in environmental policies, does not correspond well with other environmental impacts such as toxicity to ecosystems and humans, depletion of resources, and land use. In a decision-making context where you are confronted with product A and product B with the same carbon footprint score, you do not have enough information to choose the most environmentally friendly option,” says Laurent.
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