Reducing CO2 Emissions on the Electric Grid through a Carbon Disincentive Policy

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. Continue reading

Smart Grid Policy Support will Reduce European Carbon Emissions

by Stephanie Oehler

Carbon emissions are greenhouse gases and are often targeted for reductions in order to slow the progression of climate change. The energy sector, in particular, is seen as an area with significant potential for minimizing emissions since it is responsible for such a high percentage of society’s atmospheric carbon contribution. In Europe, a plethora of smart grid technologies has been installed and more are being designed in order to increase efficiency of electricity production and transmission. Darby et al. (2013) examined six national energy markets in the European Union (EU) in order to determine how carbon emission reductions occurred with the implementation of technologies and policies, market characteristics that were conducive to reductions, the areas with the greatest potential of achieving emission reductions, and the areas in which the new systems would be most effective. They collected a variety of quantitative and qualitative data from the German, Austrian, French, Spanish, Portuguese, and British markets in order to predict the emission reductions produced under three conditions: no smart grid implementation, smart grid technology implemented without legal or economic support for users, and smart grid technologies installed and supportive legislation and market conditions adopted. Continue reading

Maximizing Flexible Electricity Use by Load Balancing of Smart Grids

by Stephanie Oehler

The electricity supply has traditionally been dictated by consumers. Consumers demand varying amounts of energy depending on their instantaneous needs and suppliers are left to use whatever resources are necessary to meet their demands. As populations grow and electricity demands per capita increase, the discrepancy between demand and sustainable supply levels continues to widen. The smart grid may have the potential to mediate the conflicting objectives of consumers, who prefer supply levels that correspond with high levels of convenience for them according to their preferences, and suppliers, who would benefit from producing at a more constant rate. Hassan et al. (2013) explore the plausibility of load balancing, which has been enabled by smart grid technologies, as a method of balancing demand to more closely align with reasonable supply levels. Continue reading

Do Smart Energy Monitors Decrease Usage?

by Stephanie Oehler

As energy demand continues to increase, more utilities are turning to smart grids to manage larger systems and the increasingly diverse array of energy sources. The first technology implemented in a system is typically the smart meter because it allows for greater communication between utilities and consumers. Giving consumers access to usage information allows them to play a role in demand-side energy management. Smart meters have been installed in many systems around the world with the intention of increasing awareness amongst consumers regarding energy use patterns, and empowering them to change their behavior in order to lower their electricity costs, and subsequently reduce greenhouse gas emissions. Studies have revealed that smart meters Continue reading

“Smart” Smart Grids Improve Energy Efficiency

by Stephanie Oehler

As climate change progresses, concerned parties have turned to the electricity grid as a critical target for making large improvements in efficiency and reductions in greenhouse gas emissions. Engineers are scrambling to construct a more efficient electricity production and distribution system as the global population continues to increase and society becomes increasingly reliant on energy to fulfill its needs; this new system is referred to as the smart grid. As a hybrid between smart grid and demand-side management program efficiency strategies, information systems provide a link between the demand and supply sides of the grid and are being implemented with varying degrees of success throughout the United States. While a variety of smart grid technologies exist, Corbett (2013) evaluated the efficiency improvement abilities of three specific types of information systems; AMR (automatic meter readers) that provide the utility companies with usage information from customers, smart metering that allows for the transmission of information back and forth between the utility company and the consumers, and net metering which involves two-way communication and allows the consumer to sell power back to the grid.

Corbett, J., 2013. Using information systems to improve energy efficiency: Do smart meters make a difference? Information Systems Frontiers 15, 747-760.  http://goo.gl/FiktO3

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Maximizing the Storage Potential of Electric Vehicles in Smart Grids

Large scale renewable energy projects, as well as small installments on houses and businesses, have the ability to transform the composition of energy sources that fuel society. While such sources are beneficial in reducing greenhouse gas emissions that result from power production, they provide new obstacles for the use and storage of energy. As renewable energy sources continue to produce larger quantities of energy, the electricity grid will have to adapt to this decentralized and unpredictable production. Ridder et al. (2013) examined the feasibility of charging electric vehicles (EVs) in a smart grid scenario and their ability to compensate for shortages and surpluses that occur in the energy market due to unpredictable energy supply. Utilizing behavioral information about the EV users, EV capacity, and the capacities of charging stations, the authors created a model to simulate EV potential in Flanders, Belgium. The coordination algorithm that was determined to fit the population resulted in the proper distribution of EVs amongst available charging stations so that capacity was maximized. In the second scenario, the authors demonstrated the ability of EV users to take advantage of varying prices of energy by strategically charging when excess day-ahead energy was available and selling energy back to the grid when demand exhausted supply and only day-of, or imbalance market energy was available. Ultimately, the study demonstrated that as imbalance market prices increased compared to day-ahead prices, flexible chargers were able to save money and charger/dischargers were able to make money by discharging energy at high market prices.—Stephanie Oehler
 
Ridder, F., D’Hulst, R., Knapen, L., Janssens, D., 2013. Applying an activity based model to explore the potential of electrical vehicles in the smart grid. Procedia Computer Science,847—853

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Implementation Status of Electric Distribution Systems in U.S. Smart Grid Projects Funded Under the 2009 American Recovery and Reinvestment Act

As climate change continues to have a greater impact on individuals and habitats around the world, many nations are taking actions to reduce their impacts by minimizing greenhouse gas emissions. Modernization of electrical grids in order to increase efficiency, accommodate new sources of energy and technology, minimize losses, and ultimately reduce harmful emissions from high-polluting forms of energy production has become a priority for many countries. For example, the American and Chinese governments each contributed over seven billion U.S. dollars to national Smart Grid deployment in 2010, with numerous other developed countries investing similarly large amounts in their own electricity infrastructures. Ghosh et al. (2013) explored the current status of projects partially funded through the Smart Grid Investment Grant (SGIG)  and the Smart Grid Demonstration (SGDP) programs created under the American Recovery and Reinvestment Act (ARRA) of 2009. Through a quantitative analysis of customer profile and distribution circuit data collected by the Department of Energy (DOE) specific to the progress of implementation of federally funded Smart Grid projects, the authors were able to observe trends in the impacts of utility size and type of technology on status of completion of Electric Distribution Systems (EDS) modernization specifically. Using these data, the authors concluded that SCADA technology tended to be implemented more quickly than DA devices, regardless of utility size. In the future, this may have an impact on which technologies developers decide to use in upgrading electricity grids. —Stephanie Oehler
 
Ghosh, S., Pipattanasomporn, M., Rahman, S., 2013. Technology deployment status of U.S. Smart grid projects — electric distribution systems. IEEE Innovative Smart Grid Technologies, 1—8.

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Noncooperative and Cooperative Demand—Side Smart Grid Day—Ahead Optimization Practices Result in Reduced Reliance on Peaking Power Plants

Electricity production and usage are closely related with the impacts of climate change because many forms of energy come from the combustion of fossil fuels and emit high amounts of carbon dioxide into the atmosphere. Smart grids, electricity networks that incorporate communication devices and allow energy to flow both to and from consumers and producers in order to increase efficient energy usage, offer a promising solution to many problems that are associated with traditional energy grids. By accommodating individual energy producers and storers, in addition to traditional production methods, smart grids provide a necessary modernization of energy management systems. Atzeni et al. (2013) studied several optimization methods that cater to different types of users on the demand side of smart grids. Through day-ahead demand-side management, the authors monitored the behavior of noncooperative and cooperative energy users in order to determine which was more beneficial in reducing costs among consumers. Both simulations demonstrated that active electricity users had the potential to reduce costs by distributing generation and storage according to time-slot dependent rates, regardless of whether they were strategizing individually or within a group, thereby stabilizing the load throughout the day and improving predictability of aggregate demand.—Stephanie Oehler

Atzeni, I., Ordonez L., Scutari, G., Palomar, D., Fonollosa J., 2013. Noncooperative and cooperative optimization of distributed energy generation and storage in the demand-side of the smart grid.               IEEE Transactions on Signal Processing 61, 2454—2472.

                  Recent developments in smart grid technology and management have focused on the demand side of energy and consumer behavior. Energy supply is reactive to consumer demand, so changes to the system have involved educating users and providing incentives to use less energy in a smarter way. Italo Atzeni and his fellow authors approach this topic from the demand-side as well by applying game theory to cooperative and noncooperative day-ahead energy consumption scheduling. They gathered hour-by-hour energy consumption data for a 24 hour period from a variety of consumers and used the information to produce algorithms to represent usage. Both passive and active users were accounted for in the algorithms; passive users being those that simply accept electricity from the grid and active users being those who possess energy storage or production capacity. Active users maintain the ability to function independently from the grid at times of peak usage by tapping into their own stored or personally produced sources and can take advantage of non-peak energy prices by storing energy to use in the future. The authors constructed two different models in which active users could determine their electricity usage for the following day with the intention of reducing personal energy costs by consulting a pricing model. The first model incorporated noncooperative users in which users considered only their own needs. The second model was cooperative and allowed groups of users to collaborate in deciding how much energy they would use and during what time slots. Factors accounted for in the models included the type of users, nondispatchable and distributed generation power, the storage capacities and characteristics of energy storage devices, and the varying cost per unit of energy.
                  Each model resulted in similar load shifts from peak hours to non-peak hours, thus evening out the aggregate electricity demand curve. Consequently, both active and passive users observed a decrease in their electricity costs. While each method produced the same result, the authors concluded that the cooperative optimization practices are probably superior to the noncooperative ones because they offer optimization on a larger scale which contributes to greater predictability and stability within the system. The authors also concluded that users who implemented their own energy production and/or storage technologies experienced the highest energy savings. Ultimately, the findings from these models demonstrated the ability that consumers have when using smart grids to stabilize electricity usage such that high-emission power plants that are only used in times of peak power are no longer required to meet society’s electricity demand.

                  As the global population continues to grow and individual electricity usage increases, reforming the energy grid has become a regulatory priority in an effort to confront climate change. Addressing energy consumption from the demand-side requires educating consumers and increasing communication regarding rates and usage trends, but it does not necessarily require extensive new infrastructure like supply-side advancements demand. As the authors demonstrated, there is much that can be done by consumers to improve energy efficiency and reduce carbon emissions. The continued expansion of renewable energy sources and increasing prevalence of energy storage vehicles and devices that are present on the electricity grid will allow smart users to rely on clean energy and to store excess when it is available in order to reduce their reliance on fossil fuels.