Chiara Lo Prete

Chiara Lo Prete

Phone: 
814-865-0982
Office Address: 
213 Hosler Building
Title(s): 
Assistant Professor of Energy Economics
Unit: 
John and Willie Leone Family Department of Energy and Mineral Engineering
PDF icon Curriculum Vitae (113.58 KB)
Expertise: 
  • Electricity market design
  • Energy economics
  • Mathematical programming models of energy markets
  • Applied econometrics
Education: 
  • 2012: Ph.D., Geography and Environmental Engineering, The Johns Hopkins University
  • 2009: M.S., Geography and Environmental Engineering, The Johns Hopkins University
  • 2004: M.A., Energy Economics, Scuola Enrico Mattei
  • 2003: B.A., Economics (summa cum laude), LUISS University
Courses Taught: 
  • EBF 483 (Introduction to electricity markets, undergraduate)
  • EBF 200 (Introduction to energy and environmental economics, undergraduate)
  • EBF 401 (Corporate finance, undergraduate)
  • AEREC 511 (Econometrics II, graduate)

About:

Chiara Lo Prete is Assistant Professor of Energy Economics in the John and Willie Leone Family Department of Energy and Mineral Engineering. Dr. Lo Prete’s research centers on the design and operations of electricity markets, and employs quantitative methods at the intersection of economics, operations research and statistics. Before joining Penn State in July 2014, Dr. Lo Prete was a Ziff Environmental Fellow at Harvard University from 2012 to 2014. She earned a B.A. in Economics (summa cum laude) from LUISS University (Italy), a M.A. in Energy Economics from the Scuola Mattei (Italy), and a M.S. and Ph.D. in Geography and Environmental Engineering from The Johns Hopkins University.

Research Projects: 

Cross-Product Manipulation in Electricity Markets

The use of uneconomic virtual transactions in day-ahead electricity markets with the intent to benefit related financial positions constitutes cross-product manipulation, and has emerged as a policy concern in recent years. Cross-product manipulation has been extensively studied in securities and commodities markets, but its theoretical foundations and empirical implications in electricity markets are not well understood. Price manipulation may increase the total cost of serving electricity demand, lead to market outcomes that do not reflect underlying fundamentals, and affect the distribution of profits among market participants. Dr. Lo Prete and collaborators have developed equilibrium models that examine economic conditions allowing cross-product manipulation to persist over time, rather than as an isolated surprise. Ongoing work focuses on the application of machine learning algorithms for price manipulation detection.

State Policy Interactions with Electricity Markets

Since the adoption of restructured wholesale electricity markets, states have implemented policies that affect market outcomes, potentially leading to unintended consequences and reducing market efficiency. For example, carbon policies set by individual states (or groups of states) often create concerns of leakage, defined as the shift in production and associated emissions from the region where climate regulations apply to surrounding unregulated jurisdictions. Leakage may result in overall emission increases, if power generation in the unregulated regions is more emission intensive than in the regulated region. Dr. Lo Prete and collaborators have employed statistical analysis of historical data to examine how state-level carbon policies affect power plant operations in regional electricity markets.

Electricity Market Structure for Wind Energy Integration

Wholesale electricity markets are confronting new challenges and must evolve to meet system conditions. Increasing penetration of renewable generation induces a decrease in energy prices and capacity factors for other generator types, eroding revenue streams from the energy market and shifting a greater proportion of returns for units’ recovery of their investment costs to capacity markets, if they exist. Further, increasing shares of intermittent renewables, like wind, into the energy mix pose a challenge to the existing two-settlement market structure because the real-time availability of renewable energy sources cannot be accurately predicted day ahead. The later the grid operators become aware of the need to modify day-ahead market schedules, the higher the costs associated with large forecast errors will be, due to greater inflexibility in power system operations close to real time. Dr. Lo Prete and collaborators will integrate techniques from stochastic optimization, experimental economics and statistics to examine alternate market designs for managing the uncertainty and variability associated with wind generation.

Economics of Widespread, Long Duration Power Interruptions

A key policy issue for electric utilities and regulators is how to prioritize investments designed to address low probability, high impact events resulting in widespread, long duration outages. Investing in a more resilient system has the classic characteristics of a public good – localized and concentrated costs with diffused and difficult to measure benefits. Electric utilities often face difficulties in justifying investments that may not yield benefits for years to the regulator, and take a reactive approach by spending heavily to fix problems in the aftermath of a disaster. Dr. Lo Prete and collaborators will develop models to represent parties that are involved in making resilience-enhancing investments in practice, and examine incentive structures for encouraging adoption of resilience. Estimating the value to customers of assuring the continuation of electric service during widespread, long duration power interruptions is another area of interest.

Publications: 

Journal articles

  • C.  Lo  Prete,  N.  Guo,  and  U.V.  Shanbhag (2019).  “Virtual  Bidding  and Financial Transmission Rights: An Equilibrium Model for Cross-Product Manipulation  in  Electricity  Markets”. IEEE  Transactions  on  Power Systems 34(2), pp. 953–967.
  • A. Kleit, C. Lo Prete, S. Blumsack and N. Guo. (2018). “Weather or not? Welfare impacts of natural gas pipeline expansion in the Northeastern U.S.” Energy Systems. Advance online publication, https://doi.org/10.1007/s12667-018-0292-x.
  • C. Lo Prete and B.F. Hobbs (2016). “A cooperative game theoretic analysis of incentives for microgrids in regulated electricity markets”. Applied Energy 169, pp. 524-541.
  • C. Lo Prete and B.F. Hobbs (2015). “Market power in power markets: an analysis of residual demand curves in California’s day-ahead energy market in 1998-2000”. The Energy Journal 36(2), pp. 191-218.
  • S. Cano-Andrade, M.R. von Spakovsky, A. Fuentes, C. Lo Prete and L. Mili (2015). “Upper level of a sustainability assessment framework for power system planning”. Journal of Energy Resources Technology 137(4), pp. 1-11.
  • C. Lo Prete and C.S. Norman (2013). “Rockets and feathers in CO2-power markets? New evidence from the second phase of the EU ETS”. Energy Economics 36, pp. 312-321.
  • C. Lo Prete, B.F. Hobbs, C.S. Norman, S. Cano-Andrade, A. Fuentes, M.R. von Spakovsky and L. Mili (2012). “Sustainability and reliability assessment of microgrids in a regional electricity market”. Energy 41, pp. 192-202.

Refereed conference papers

  • Y. Shan, C. Lo Prete, G. Kesidis and D.J. Miller (2017). “A simulation framework for uneconomic virtual bidding in day-ahead electricity markets”. Proceedings of the 2017 American Control Conference (ACC), Seattle, WA, May-24-26.
  • C. Lo Prete and B.F. Hobbs (2013). “Modeling the interaction between microgrids and electric utilities: a regulator’s perspective”. Proceedings of the Fourth IEEE International Conference on Smart Grid Communications, Vancouver, October 21-24.
  • S. Cano-Andrade, M.R. von Spakovsky, A. Fuentes, C. Lo Prete, B.F. Hobbs and L. Mili (2012). “Multi-objective optimization for the sustainable-resilient synthesis/design/operation of a power network coupled to distributed power producers via microgrids”. Proceedings of ASME International Mechanical Engineering Congress and Exposition, vol. 6, Energy: Sustainable Technologies, Houston, TX, November 9-15.