SmartGrid

By 2050, the costs of an average PV and wind plant are expected to fall by 71% and 58%, respectively. Meanwhile, batteries will further depress market prices, which in turn enable the deeper penetration of renewable energies like PV, wind, and electric vehicles (EVs). However, the transition on primary energy resources can be a double-edged sword. Problems such as protective relay is landing and fault detection, protective relay coordination under environmental uncertainty, topology recovery of secondary distribution networks, and EV charging station planning are critical to the security and resilience of the electric systems. This presentation describes several timely solutions to enable more secure and efficient grid operations by analyzing voluminous power system operation data. The aforementioned solutions include the multifunction intelligent relays, an environment-driven adaptive protection scheme, a transformer connectivity inferencing tool, and an EV charging station planning method. Several types of machine learning algorithms are developed in power systems to support renewable energy integration for sustainability.

Project poster session spanning a very broad range of topics from battery technology and modeling to applications to transportation and the grid.

You are welcome to come and meet our students and learn about their amazing work.

List of EE/CEE 292X projects:
1. Voltage sensing separator for battery fast charging
2. Equivalent circuit models for lithium ion batteries under EV drive cycles
3. Machine learning based models for lithium ion batteries
4. Characterizing error in linear battery dynamics model
5. Homogenized thermal runaway model in Li-ion cells
6. Battery pack design for thermal runaway prevention
7. Smart lithium ion battery pack for small-scale UAV applications
8. Battery-aware intelligence for autonomous robot navigation
9. Battery modeling to optimize range and cycle life for electric aircraft
10. Mileage prediction based on driving profiles
11. Data-driven system modeling of Stanford EV buses
12. Empirical trends in energy consumption of electric buses
13. Quantifying load impact from autonomous electric TNC fleets
14. Data-driven placement of charging station locations
15. Charging station locations via agent based simulation
16. Battery design for resilient decentralized wastewater treatment
17. Low cost, temperature robust batteries for farm applications
18. Battery charge controller for small scale off-grid wind
19. Techno-economic feasibility of a hybrid storage system for a university campus
20. Distributed vs grid scale storage systems for future EV charging stations
21. Ancillary services with vehicle to grid charging
22. Quantifying 2nd life EV battery value for grid applications

The emergence of ergodic behavior in quantum systems is an old puzzle. Quantum mechanical time-evolution is local and unitary, but many quantum systems are successfully described by irreversible hydrodynamics. I will present a hypothesis for how operators grow in strongly-interacting many-body systems and thence give rise to hydrodynamics. The hypothesis states that the Lanczos coefficients in the continued fraction expansion of the Green's function growth linearly with a "universal growth rate" $\alpha$ in chaotic quantum systems.

I will describe the extensive analytical and numerical evidence for this hypothesis, as well as three of its consequences. (1) Operator growth can diagnose free, integrable, and chaotic dynamics. (2) The growth rate --- an experimental observable --- gives rise to a quantity called the "K-complexity". The K-complexity quantifies the "amount of chaos" in any quantum system, and reduces to the Lyapunov exponent in semiclassical limits. (3) Assuming the hypothesis, one can accurately compute diffusion coefficients and other hydrodynamical data with minimal computational effort.

This talk is based on arXiv: 1812.08657.

In developing the 20th century grid, George Westinghouse and Nikola Tesla did not design an architecture for distributed or renewable resources. To decarbonize the grid--and to electrify transportation and heating--requires exactly that: a remaking of the grid to accommodate these resources. While doing so will require some new technology solutions, this seminar will explore how existing policy has inhibited innovation in the regulated power sector, and more important, will give an update on New York State's Reforming the Energy Vision (REV) policy, a market-based approach to build the smart grid.

What is driving our electric power industry to improve performance? How do we, as an industry, make sure we are performing to our customers' expectations? In today's power systems, every technology employed, trend established, and policy or standard implemented, should be done so with the best interests of the customer in mind. The utility sector is economically immense and vast in geographic scope, and it combines ownership, management, and regulation in complex ways to achieve reliable energy service. This lecture provides a broad view on energy market regulation in the US, including a rulemaking process and landmark orders. It addition, it explores how improving bulk power system performance through technology, data, and policies will benefit the customers of electric power.

We invite you to join us in this quarter's Stanford Smart Grid Seminar. The theme of the seminar series is on smart grids and energy systems, scheduled for Thursdays, and with speakers from academic institutions and industry. The seminar room is Room 111 in Y2E2 Building.

The speakers are renowned scholars or industry experts in power and energy systems. We believe they will bring novel insights and fruitful discussions to Stanford. This seminar is offered as a 1 unit seminar course, CEE 272T/EE292T. Interested students can take this seminar course for credit by completing a project based on the topics presented in this course. Please discuss with the faculty in charge before signing up for credit.

Smart Grid Seminar Organization Team:

• Ram Rajagopal, Associate Professor, Civil & Environmental Engineering, and Electrical Engineering
• Liang Min, Managing Director, Bits and Watts Initiative
• Chin-Woo Tan, Director, Stanford Smart Grid Lab
• Mohammad Rasouli, Postdoctoral Scholar, Civil and Environmental Engineering

Vehicle Grid Integration (VGI) is the umbrella-concept that encompasses managed charging of electric vehicles (V1G) as well as vehicle-to-grid (V2G) solutions. As more electric vehicles hit the road inCalifornia, PG&E has been leading industry efforts to better clarify and articulate the scope, need, and value of VGI. This talk provides an overview of PG&E's activities in the VGI space, focusing on a recently developed market framework that identifies hundreds of potential VGI use-cases and help quantify their value. Dr. Farhat will also share findings from two of PG&E's VGI pilots: the ChargeForward pilot in collaboration with BMW North America, and the School Bus Renewable Integration pilot with PittsburghUnified School District.

We invite you to join us in this quarter's Stanford Smart Grid Seminar. The theme of the seminar series is on smart grids and energy systems, scheduled for Thursdays, and with speakers from academic institutions and industry. The seminar room is Room 111 in Y2E2 Building.

The speakers are renowned scholars or industry experts in power and energy systems. We believe they will bring novel insights and fruitful discussions to Stanford. This seminar is offered as a 1 unit seminar course, CEE 272T/EE292T. Interested students can take this seminar course for credit by completing a project based on the topics presented in this course. Please discuss with the faculty in charge before signing up for credit.

Smart Grid Seminar Organization Team:

• Ram Rajagopal, Associate Professor, Civil & Environmental Engineering, and Electrical Engineering
• Liang Min, Managing Director, Bits and Watts Initiative
• Chin-Woo Tan, Director, Stanford Smart Grid Lab
• Mohammad Rasouli, Postdoctoral Scholar, Civil and Environmental Engineering

In the first part of the talk, we study the problem of designing optimal control actions (e.g., real-time prices) for demand management in power distribution systems given unknown customer response functions. Without exact response information or a market mechanism that extracts this information from customers, the design of demand management initiatives can present economic uncertainty and grid reliability concerns for the aggregator. This highlights the need for safety-constrained learning heuristics that can be applied in power and more broadly safety-critical systems. We showcase "safety-aware" bandit heuristics for designing control actions that constrain the probability of violation of power grid constraints during the learning process. We then highlight the effect of such safety constraints on the growth of regret for special classes of stochastic bandit optimization problems.

In the second part of the talk, we consider the problem of joint routing, battery charging, and pricing problem faced by a profit-maximizing transportation service provider that operates a fleet of autonomous electric vehicles. To accommodate for the time-varying nature of trip demands, renewable energy availability, and electricity prices, a dynamic pricing and control policy is required. We highlight several such policies, including one trained through deep reinforcement learning to develop a near-optimal policy. We also determine the optimal static policy to serve as a baseline for comparison with our dynamic policy and for determining the capacity region of the system. While the static policy provides important insights on optimal pricing and fleet management, we showcase how in a real dynamic setting, it is inefficient to utilize a static policy.

We invite you to join us in this quarter's Stanford Smart Grid Seminar. The theme of the seminar series is on smart grids and energy systems, scheduled for Thursdays, and with speakers from academic institutions and industry. The seminar room is Room 111 in Y2E2 Building.

The speakers are renowned scholars or industry experts in power and energy systems. We believe they will bring novel insights and fruitful discussions to Stanford. This seminar is offered as a 1 unit seminar course, CEE 272T/EE292T. Interested students can take this seminar course for credit by completing a project based on the topics presented in this course. Please discuss with the faculty in charge before signing up for credit.

Smart Grid Seminar Organization Team:

• Ram Rajagopal, Associate Professor, Civil & Environmental Engineering, and Electrical Engineering
• Liang Min, Managing Director, Bits and Watts Initiative
• Chin-Woo Tan, Director, Stanford Smart Grid Lab
• Mohammad Rasouli, Postdoctoral Scholar, Civil and Environmental Engineering

Artificial intelligence (AI) may be the key to unlocking humanity's problem-solving capabilities but engaging with AI is not necessarily intuitive. Industrial enterprises find it difficult to understand how specific AI advances can be applied to their organizations and how to begin integrating AI technology at scale. Starting to work with AI is no different than with any other technology: Understand the problem you are trying to solve, understand the capabilities of the technology, and reconcile the two. We distilled the steps from our application of AI across a variety of real-world projects. To make the steps tangible, we will deepdive into one: Google data center energy efficiency. Google wanted to reduce the energy consumed by its data centers while maintaining a temperature that was safe for operations. The team started this project with one of Google's newest, most optimized data centers. This provided a data-rich environment with the most up-to-date sensors and equipment, which helped baseline performance (and later measure impact). The result was an AI system that achieved 30% reduction in energy consumption while continuing to operate the data center in a safe, effective manner. The benefit was clear: Google reduced its data center energy consumption, environmental impact, and bottomline cost while improving the efficiency of the system. Google is now looking to expand the scale and application of this technology.

We invite you to join us in this quarter's Stanford Smart Grid Seminar. The theme of the seminar series is on smart grids and energy systems, scheduled for Thursdays, and with speakers from academic institutions and industry. The seminar room is Room 111 in Y2E2 Building.

The speakers are renowned scholars or industry experts in power and energy systems. We believe they will bring novel insights and fruitful discussions to Stanford. This seminar is offered as a 1 unit seminar course, CEE 272T/EE292T. Interested students can take this seminar course for credit by completing a project based on the topics presented in this course. Please discuss with the faculty in charge before signing up for credit.

Smart Grid Seminar Organization Team:

• Ram Rajagopal, Associate Professor, Civil & Environmental Engineering, and Electrical Engineering
• Liang Min, Managing Director, Bits and Watts Initiative
• Chin-Woo Tan, Director, Stanford Smart Grid Lab
• Mohammad Rasouli, Postdoctoral Scholar, Civil and Environmental Engineering

We invite you to join us in this quarter's Stanford Smart Grid Seminar. The theme of the seminar series is on smart grids and energy systems, scheduled for Thursdays, and with speakers from academic institutions and industry. The seminar room is Room 111 in Y2E2 Building.

The speakers are renowned scholars or industry experts in power and energy systems. We believe they will bring novel insights and fruitful discussions to Stanford. This seminar is offered as a 1 unit seminar course, CEE 272T/EE292T. Interested students can take this seminar course for credit by completing a project based on the topics presented in this course. Please discuss with the faculty in charge before signing up for credit.

Smart Grid Seminar Organization Team:

• Ram Rajagopal, Associate Professor, Civil & Environmental Engineering, and Electrical Engineering
• Liang Min, Managing Director, Bits and Watts Initiative
• Chin-Woo Tan, Director, Stanford Smart Grid Lab
• Mohammad Rasouli, Postdoctoral Scholar, Civil and Environmental Engineering