In centralized wholesale electricity markets worldwide, market operators use mixed-integer linear programming to solve the allocation problem. Prices are typically determined based on the duals of relaxed versions of this optimization problem. The resulting outcomes are efficient, but market operators must pay out-of-market uplifts to some market participants and incur a considerable budget deficit that was criticized by regulators. As the share of renewables increases, the number of market participants will grow, leading to larger optimization problems and runtime issues. At the same time, non-convexities will continue to matter, e.g., due to ramping constraints of the generators required to address the variability of renewables or non-convex curtailment costs. We draw on recent theoretical advances in the approximation of competitive equilibrium to compute allocations and prices in electricity markets using convex optimization. The proposed mechanism promises approximate efficiency, no budget deficit, and computational tractability. We present experimental results for this new mechanism in the context of electricity markets, and compare the runtimes, the average efficiency loss of the method, and the uplifts paid with standard pricing rules. We find that the computations with the new algorithm are considerably faster for relevant problem sizes. In general, the computational advantages come at the cost of efficiency losses and a price markup for the demand side. Interestingly, both are small with realistic problem instances. Importantly, the market operator does not incur a budget deficit and the uplifts paid to market participants are significantly lower compared to standard pricing rules.

中文翻译：

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多项式时间内解决大规模电力市场定价问题


在全球集中批发电力市场中，市场运营商使用混合整数线性规划来解决分配问题。价格通常是根据该优化问题的松弛版本的对偶来确定的。由此产生的结果是有效的，但市场运营商必须向一些市场参与者支付市场外的费用，并产生相当大的预算赤字，这受到了监管机构的批评。随着可再生能源份额的增加，市场参与者的数量将会增加，从而导致更大的优化问题和运行时间问题。与此同时，非凸性将继续发挥重要作用，例如，由于解决可再生能源的可变性或非凸限电成本所需的发电机组的斜坡限制。我们利用竞争均衡近似方面的最新理论进展，使用凸优化来计算电力市场的分配和价格。所提出的机制保证了近似的效率、无预算赤字和计算的易处理性。我们在电力市场的背景下展示了这种新机制的实验结果，并比较了该方法的运行时间、平均效率损失以及采用标准定价规则所支付的费用。我们发现，对于相关问题规模，使用新算法的计算速度要快得多。一般来说，计算优势是以效率损失和需求方价格上涨为代价的。有趣的是，两者都很小，都有现实的问题实例。重要的是，市场运营商不会产生预算赤字，而且与标准定价规则相比，向市场参与者支付的费用要低得多。