According to the fundamental theorems of welfare economics, any competitive equilibrium is Pareto efficient. Unfortunately, competitive equilibrium prices only exist under strong assumptions such as perfectly divisible goods and convex preferences. In many real-world markets, participants have non-convex preferences and the allocation problem needs to consider complex constraints. Electricity markets are a prime example, but similar problems appear in many real-world markets, which has led to a growing literature in market design. Power markets use heuristic pricing rules based on the dual of a relaxed allocation problem today. With increasing levels of renewables, these rules have come under scrutiny as they lead to high out-of-market side-payments to some participants and to inadequate congestion signals. We show that existing pricing heuristics optimize specific design goals that can be conflicting. The trade-offs can be substantial, and we establish that the design of pricing rules is fundamentally a multi-objective optimization problem addressing different incentives. In addition to traditional multi-objective optimization techniques using weighing of individual objectives, we introduce a novel parameter-free pricing rule that minimizes incentives for market participants to deviate locally. Our theoretical and experimental findings show how the new pricing rule capitalizes on the upsides of existing pricing rules under scrutiny today. It leads to prices that incur low make-whole payments while providing adequate congestion signals and low lost opportunity costs. Our suggested pricing rule does not require weighing of objectives, it is computationally scalable, and balances trade-offs in a principled manner, addressing an important policy issue in electricity markets.

翻译：根据福利经济学基本定理，任何竞争性均衡都是帕累托最优的。然而，竞争性均衡价格仅在完全可分商品和凸偏好等严格假设下存在。在许多现实市场中，参与者具有非凸偏好，且分配问题需要考虑复杂约束。电力市场是典型例证，但类似问题广泛存在于实际市场中，催生了日益增长的市场设计文献。当前电力市场采用基于松弛分配问题对偶的启发式定价规则。随着可再生能源渗透率提升，这些规则因导致部分参与者获得高额场外补贴及不充分的阻塞信号而备受质疑。我们证明现有定价启发式方法优化了可能相互冲突的特定设计目标，其权衡代价可能相当显著，并确立定价规则设计本质上是一个处理不同激励的多目标优化问题。除使用目标加权求解的传统多目标优化技术外，我们提出了一种无参数的新型定价规则，该规则能最小化参与者局部偏离的激励。理论与实验结果表明，新定价规则充分吸收了当前备受争议的现有定价规则的优势，其产生的价格既能提供适当的阻塞信号并降低机会成本损失，又能产生较低的整体补偿费用。建议定价规则无需目标加权，具有计算可扩展性，能以系统化方式平衡权衡取舍，解决了电力市场的重要政策问题。