Electricity infrastructure is under-going an accelerated evolution. The penetration of renewable energy is increasing and expected to reach 33% by 2020 in California. Uncertain nature of renewable energy generation is throwing up new challenges to manage uncertainty on a scale never seen before. Existing methods of managing uncertainty via adequate spinning reserves are uneconomical at such a large scale. Demand response programs will provide some mitigation, but will be inadequate. Any other solution deployed to manage this uncertainty is unlikely to be adopted, unless it is consistent with the economic laws at play. New market designs and pricing mechanisms have to be investigated that (i) facilitate renewable energy integration and demand side management in the smart grid and (ii) ensure sufficient grid stability margins. Towards this end, the theory of market for random goods will be developed and studied in the project where risk management policies, incentive structures for flexibility, and market design is studied in tandem. The proposed research effort is an essential part of developing the economics of the smart grid and a step towards renewable energy integration. The project trains the next generation of engineers and scientists to overcome challenges that the smart grid operators will encounter with large uncertainty in renewable generation.
Uncertainty in renewable generation provides incentives for generators and load serving entities to strategically distort prices in their favor. Thus, there is a need to introduce market mechanisms to restrict the ability of market players to distort prices. The key tools to designing a market for random goods are game theory and mechanism design, coupled with advances in probability theory and optimization/data science. New mechanisms will be developed by a three-pronged approach: (1) Introduce a new perspective of viewing renewable energy as a random good, i.e., a good that is only generated and delivered with some probability. The market for aggregators is introduced and studied for (i) designing market mechanisms for buying random goods that aggregators could sell in wholesale markets; (ii) designing market mechanisms for selling random goods that renewable generators could use; and (iii) designing market exchanges, where renewable energy could be traded. (2) Devise appropriate formats for expressing flexibility in demand and generation. This entails (i) designing appropriate pricing mechanisms to induce consumers to express maximum flexibility (this will be enforced and managed via the smart-meter infrastructure that utilities plan to put in place in the next few years); and (ii) designing mechanisms for economic dispatch wherein flexible generator receive incentive payments for their flexibility. (3) Develop a theory for risk mitigation and risk-awareness in economic dispatch. This entails (i) investigating the role of virtual bidding in risk mitigation in multi-stage markets; and (ii) rethinking risk-aware design for electricity markets from the ground-up by formalizing a risk-aware economic dispatch framework. The above research agenda requires foundational developments of new economic, optimization, and control frameworks that incorporate randomness, flexibility, and risk.