Collaborative Research: Smarter Markets for a Smarter Grid: Pricing Randomness, Flexibility and Risk

电力基础设施正在加速演变。可再生能源的普及率正在增加，预计到2020年加州将达到33%。可再生能源发电的不确定性正在引发新的挑战，以前所未有的规模管理不确定性。现有的通过充足的周转储备来管理不确定性的方法，在如此大的规模下是不经济的。需求响应计划将提供一些缓解，但将是不够的。为管理这种不确定性而部署的任何其他解决方案都不太可能被采用，除非它符合正在发挥作用的经济规律。必须研究新的市场设计和定价机制，以(I)促进智能电网中的可再生能源整合和需求侧管理，以及(Ii)确保足够的电网稳定裕度。为此，随机商品市场理论将在该项目中发展和研究，其中风险管理政策、灵活性激励结构和市场设计将同时进行研究。拟议的研究工作是发展智能电网经济性的重要组成部分，也是迈向可再生能源整合的一步。该项目培养下一代工程师和科学家，以克服智能电网运营商在可再生能源发电方面将遇到的巨大不确定性的挑战。可再生能源发电的不确定性激励发电机和负荷服务实体战略性地扭曲价格，使其有利于自己。因此，有必要引入市场机制，以限制市场参与者扭曲价格的能力。设计随机商品市场的关键工具是博弈论和机制设计，再加上概率论和优化/数据科学的进步。将通过三管齐下的办法制定新的机制：(1)引入一种新的视角，将可再生能源视为随机商品，即只以一定概率产生和交付的商品。介绍和研究聚集器市场的目的是：(1)设计市场机制，购买聚集器可以在批发市场出售的随机商品；(2)设计销售可再生能源发电商可以使用的随机商品的市场机制；(3)设计可再生能源交易的市场交易所。(2)设计适当的格式，以表达需求和生产的灵活性。这需要(I)设计适当的定价机制，以诱导消费者表现出最大的灵活性(这将通过公用事业公司计划在未来几年到位的智能电表基础设施来执行和管理)；以及(Ii)设计经济调度机制，其中灵活的发电者因其灵活性而获得奖励报酬。(3)发展了经济调度中的风险缓解和风险意识理论。这需要(I)调查虚拟竞价在多阶段市场中风险缓解中的作用；以及(Ii)通过正式确定具有风险意识的经济调度框架，从头开始重新思考电力市场的具有风险意识的设计。上述研究议程需要新的经济、优化和控制框架的基础性发展，这些框架包括随机性、灵活性和风险。

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.