James Merrick’s research focuses on the improvement of mathematical modeling methods to address a variety of energy and climate planning problems. This talk will discuss this research, with an emphasis on how to structure models to provide economic and policy insight, focusing on appropriate valuation of renewables and energy storage options.
James completed his PhD in Management Science and Engineering at Stanford University in January 2018. He previously completed a dual masters degree in Technology & Policy and Electrical Engineering & Computer Science at MIT, and a Bachelor of Engineering degree at University College Dublin. Since completing his PhD, James applies his research to, and builds optimization models for, EPRI, a stealth robotics startup in San Francisco, and a major electricity generator in Ireland. In addition, James is undertaking a number of research projects with colleagues at NASA, EPRI, and Stanford and when possible, likes to help develop his family’s farm in Ireland.
Two-Stage Monte Carlo Simulation to Forecast Levelized Cost of Electricity for Wave Energy
Rachael Green is currently an undergraduate senior at the University of California, Berkeley. She is majoring in Environmental Economics and Policy in the College of Natural Resources with a minor in History from the College of Letters and Science. She has worked as an undergraduate researcher in the collaborative effort between the Renewable and Appropriate Energy Laboratory and CalWave Power Technologies, Inc. Despite wave energy’s vast global potential, there has been relatively little commercial deployment to date. This has been partially attributed to the large uncertainty in both the current estimated and future expected electricity generation costs associated with wave technologies. Her presentation quantifies the uncertainty of the forecasted levelized cost of electricity (LCOE) for wave energy as it relates to United States and European Union energy targets. Next month she will present this work at the International Conference on Renewable Energy Research and Applications. After graduating, Rachael hopes to continue working in the renewable energy field.
Rong HAN (Ph.D Candidate in Beijing Institute of Technology, Visiting Scholar in Berkeley Energy and Climate Institute).Research progress of IAMs Downscaling model, Evaluation model and Land use model
Rong HAN is currently a third year PhD Candidate in Center for Energy & Environmental Policy Research, Beijing Institute of Technology. She came to Berkeley's Energy and Climate Institute as visiting scholar for one year. During the process of PhD student, her research mainly focus on assessment of global climate policy, China’s carbon emission trading market and carbon finance. These researches have published on Journal of Cleaner Production, Natural Hazards, and Energy Policy.
Climate change is a complex and comprehensive process, which can only be understood on the basis of the combined insights from various scientific disciplines. In recent years the need for integration of information among ‘earth system’ (ES), ‘vulnerability, impact, and adaptation assessment’ (VIA), and ‘integrated assessment’ (IA) communities has become stronger. The IAM (integrated assessment models) model is designed to couple of ES and IA models to account of the possible feedbacks between human systems and the earth system on the global scale. Her presentation will be focus on the recent research progress of IMA downscaling model, evaluation model and land use model.
Click here for a direct link to the paper, published in Environmental Science & Technology (ES&T).
Fast growing and emerging economies face the dual challenge of sustainably expanding and improving their energy supply and reliability while at the same time reducing poverty. Critical to such transformation is to provide affordable and sustainable access to electricity. We use the capacity expansion model SWITCH to explore low carbon development pathways for the Kenyan power sector under a set of plausible scenarios for fast growing economies that include uncertainty in load projections, capital costs, operational performance, and technology and environmental policies. In addition to an aggressive and needed expansion of overall supply, the Kenyan power system presents a unique transition from one basal renewable resource− hydropower− to another based on geothermal and wind power for ∼ 90% of total capacity. We find geothermal resource adoption is more sensitive to operational degradation than high capital costs, which suggests an emphasis on ongoing maintenance subsidies rather than upfront capital cost subsidies. We also find that a cost-effective and viable suite of solutions includes availability of storage, diesel engines, and transmission expansion to provide flexibility to enable up to 50% of wind power penetration. In an already low-carbon system, typical externality pricing for CO2 has little to no effect on technology choice. Consequently, a “ zero carbon emissions” by 2030 scenario is possible with only moderate levelized cost increases of between $3 and $7/MWh with a number of social and reliability benefits. Our results suggest that fast growing and emerging economies could benefit by incentivizing anticipated strategic transmission expansion. Existing and new diesel and natural gas capacity can play an important role to provide flexibility and meet peak demand in specific hours without a significant increase in carbon emissions, although more research is required for other pollutant’ s impacts.
Josiah Johnston will be presenting a review of approaches for dealing with uncertainty in the context of Switch, an investment planning tool for low-emission electric power grids. The discussion will also include an introduction to stochastic programming and decomposition tools available for use with the new version of Switch from the PySP python libraries.
This lab meeting will roughly be divided into equal time for presentation and discussion. It will be of most interest to people interested in working with uncertainty in Switch, or general interest in computational tools for optimizing under uncertainty.
Join in for a fun meeting discussing the progress of a variety of SWITCH projects and potential research ideas. Dan Kammen will also provide food to boost brain power and stimulate a lively discussion!
September 29, 20115
The very first customers who bought Tesla's new brand new SUV, will get to drive them away Tuesday night.
The Tesla Model X is pricey, but right now, gas is not. Gas prices could be putting the future of electric cars in danger.
Tesla's ModelX will be the technology motor company's luxury SUV model. With a price tag of more than $80,000 it's not the best option for saving a few dollars by avoiding gas pumps, especially since the price of gas has plummeted over the last year.
"It's not only that Saudi Arabia and the traditional oil countries are flooding the market, we're seeing much more oil and gas being pumped in U.S. states in Canada. There is a glut of oil on the market because of new exploration technologies for fossil fuels," said University of California Berkeley professor Daniel Kammen.
Those falling gas prices might be having an effect on electric car sales. This year, more than 72,000 plug-in vehicles, or EVs were sold, which is lagging behind last year's sales by about 7,000 units.
But Kammen at UC Berkeley's Goldman School of Public Policy says electric cars will likely continue to grow for a few reasons.
"The price to go a mile in an electric vehicle is about a third what it is to go, even with today's gas prices, than to drive a combustion vehicle," Kammen said.
He says California is under a mandate to have a million EV's on the roads by 2020. And there are lots of incentives for car companies and potential owners, including HOV stickers and rebates.
Chevrolet is re-launching the Volt with a sticker price that's significantly less than a Tesla.
"The 2015 Volt starts at $33,995 and that's before a Federal Tax Credit of $7,500 and in California you can also apply for a $1,500 clean vehicle rebate," said General Motors product specialists Darin Jesse.
It's not clear how much longer gas prices will continue to drop, but in the meantime car companies are hoping buyers will pay attention to these EV options.
SWITCH (Solar and wind energy integrated with transmission and conventional sources) is a linear programming modeling platform used to examine least cost energy systems designed to meet specific reliability, performance and environmental quality standards.
SWITCH is a capacity expansion model that invests in new generation and transmission assets as well as in end-use and demand-side management options (including electrified vehicles and storage) with a high-resolution assessment and planning package to explore the system performance resting from different scenarios.
SWITCH was initially developed for California, but has been expanded and refined to explore energy choices across the US West (the WECC, Chile, Nicaragua, China), with future plans to cover the East African Power Pool (EAPP) and India.
A wide range of SWITCH publications are in print and in use at various energy, climate, and development agencies.