# (324g) Space-Time Dynamics of Electricity Markets Incentivize Technology Decentralization

- Conference: AIChE Annual Meeting
- Year: 2019
- Proceeding: 2019 AIChE Annual Meeting
- Group: Computing and Systems Technology Division
- Session:
- Time:
Tuesday, November 12, 2019 - 2:18pm-2:36pm

In this work, we propose a computational framework for analyzing economic incentives provided by space-time dynamics of electricity prices. Our framework is based on a technology placement formulation that seeks to find optimal placement locations for generators and loads in the network that minimize profit risk. We show that an unconstrained version of this problem can be cast as an eigenvalue problem. Under this representation, optimal network allocations are eigenvectors of the space-time price covariance matrix while the eigenvalues are the associated revenue variances. Consequently, risk analysis can be performed by using principal component analysis (PCA) techniques. Analysis using CAISO market data for 2015 reveals that there exists a large number of placement strategies that completely eliminate risk. We construct a constrained placement problem that captures constraints on the types of technologies. Unfortunately, for the ISO-scale data sets of interest, this problem is a mixed-integer quadratic programming problem that is intractable with current solvers. We thus propose to use the mean absolute deviation as an alternative risk measure to obtain a more scalable (but still challenging) mixed-integer linear program. Our analysis reveals that complete mitigation of revenue risk is only possible by simultaneous investment in decentralized generation and loads (which can also be achieved by using batteries or hybrid systems such microgrids). We thus conclude that space-time market dynamics indeed provide incentives for strategic diversification and placement of technologies.

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