NSF SaTC: Towards Securing Coupled Financial and Power Systems in the Next Generation Smart Grid

G. Kesidis (PSU PI), D.J. Miller (PSU co-PI), in collaboration with K. Levitt, J. Rowe, D. Raphson & J. Bushnell (U.C. Davis), A. Scaglione (ASU)

2012-2017

           

           

We studied different models of the electricity economy, including situations where some of the participants attempt to manipulate the market. In addition, we considered coincident-peak based pricing over a billing interval for the case of a datacenter (cloud) managing its electricity costs. Also, we considered the problem of managing electricity consumption of flexible appliances, including automated scheduling of overnight charging of electric vehicles (EVs).  In on-going work, we are considering security and fairness issues of electricity pricing in important existing (cloud) and future (EV) sectors.

           

 

         Papers and personnel participating in work supported in whole or part by this grant:

 

·Y. Shan, C. Lo Prete, G. Kesidis and D.J. Miller. Modeling and detecting bidding anomalies in day-ahead electricity markets. Proc. ACM NetEcon, Antibes, June 2016 (extended abstract); Proc. American Control Conference (ACC), Seattle, May 2017.

 

·N. Nasiriani, G. Kesidis, D. Wang.  Optimal Peak Shaving Using Batteries at Datacenters: Characterizing the Risks and Benefits. In Proc. IEEE MASCOTS, Banff, Sept. 20-22, 2017.

 

·G. Kesidis, U.V. Shanbhag, N. Nasiriani, B. Urgaonkar. Competition and Peak-Demand Pricing in Clouds Under Tenants’ Demand Response. In Proc. IEEE MASCOTS, Banff, Sept. 20-22, 2017.

·    N. Nasiriani, C. Wang, G. Kesidis, B. Urgaonkar. On fair attribution of costs to cloud tenants under peak- based pricing. In Proc. IEEE MASCOTS, Atlanta, Oct. 2015 (conference version); ACM TOMPECS Nov. 2016 (journal version).

·Y. Shan and G. Kesidis. Optimal power flow with random wind resources. Proc. IEEE HICSS, Power Systems Track, Kauai, Hawaii, Jan. 2016.

·    Y. Shan, J. Raghuram, G. Kesidis, C. Grin, K. Levitt, D.J. Miller, J. Rowe, A. Scaglione. Generation bidding game with potentially false attestation of flexible demand. EURASIP Journal on Advances in Signal Processing - Special issue on advanced signal processing techniques and telecommunications network infrastructures for Smart Grid analysis, monitoring and management, Issue 1, March 2015.

·    M. Alizadeh, A. Scaglione, A. Applebaum, G. Kesidis, and K. Levitt. Reduced-Order Load Models for Large Populations of Flexible Appliances. IEEE Transaction on Power Systems (TPWRS), Sept. 2014.

·    C. Wang, N. Nasiriani, G. Kesidis, B. Urgaonkar, Q. Wang, L.Y. Chen, A. Gupta, R. Birke. Recouping Energy Costs from Cloud Tenants: Tenant Demand Response Aware Pricing Design. Proc. ACM eEnergy, Bangalore, June 2015.

·    M. Alizadeh, A. Scaglione, A. Goldsmith and G. Kesidis. Capturing Aggregate Flexibility in Demand Response. In Proc. IEEE CDC, Dec. 2014.

·    C. Wang, B. Urgaonkar, G. Kesidis, and Q. Wang. A Hierarchical Demand Response Framework for Data Center Power Cost Optimization Under Real-World Electricity Pricing. In Proc. IEEE MASCOTS, Paris, Sept. 2014.

·    J. Raghuram, G. Kesidis, C. Grin, K. Levitt, D.J. Miller, J. Rowe, A. Scaglione. Generation bidding game with flexible demand. Proc. USENIX Workshop on Feedback Computing, Philadelphia, June 17, 2014.

·    C. Wang, B. Urgaonkar, G. Kesidis, U.V. Shanbhag, Q. Wang. A Case for Virtualizing the Electric Utility in Cloud Data Centers. In Proc. USENIX HotCloud, Philadelphia, June 2014.

·    C. Wang, B. Urgaonkar, Q. Wang, G. Kesidis and A. Sivasubramaniam. Data Center Cost Optimization Via Workload Modulation Under Real-World Electricity Pricing. In Proc. ACM/IEEE Int’l Conf. on Utility and Cloud Computing (UCC), Desden, Germany, Dec. 2013.

·    M. Alizadeh, G. Kesidis, and A. Scaglione. Clustering consumption in queues: A Scalable Model for Electric Vehicle Scheduling. In Proc. IEEE Asilomar Conference, invited session on Signal Processing for the Smart Grid, Nov. 2013.

·    H. Lu, G. Pang and G. Kesidis. Automated scheduling of deferrable PEV/PHEV load by power-profile un- evenness. In Proc. IEEE SmartGridComm, Vancouver, Oct. 2013.

·    M. Alizadeh, A. Scaglione, and G. Kesidis. Scalable Model Predictive Control of Demand For Ancillary Services. In Proc. IEEE SmartGridComm, Vancouver, Oct. 2013.

 

Some earlier papers on related work:

 

·    G. Pang, G. Kesidis and T. Konstantopoulos. Avoiding Overages by Deferred Aggregate Demand for PEV Charging on the Smart Grid. In Proc. IEEE ICC, Ottawa, June 2012. Extended version is CSE Dept Technical Report CSE-13-002, available at http://www.cse.psu.edu/research/publications/tech-reports/2012/CSE-12-004.pdf

·    S. Caron and G. Kesidis. Incentive-based energy consumption scheduling algorithms for the Smart Grid. In Proc. IEEE SmartGridComm, Gaithersburg, MD, Oct. 4-6, 2010. Extended version available at http://www.cse.psu.edu/~gik2/papers/smartgridcomm10-extended.pdf