Value-oriented forecast reconciliation for renewables in electricity markets

• URL: http://arxiv.org/abs/2501.16086v1
• Date: Mon, 27 Jan 2025 14:35:39 GMT
• Title: Value-oriented forecast reconciliation for renewables in electricity markets
• Authors: Honglin Wen, Pierre Pinson,
• Abstract summary: We propose a value-oriented forecast reconciliation approach that focuses on the forecast value for individual agents. Specifically, we model this problem as a cooperative bargaining game, where each agent aims to optimize their own gain. From an application perspective, we consider an aggregated wind energy trading problem, where profits are distributed using a weighted allocation rule.
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• Abstract: Forecast reconciliation is considered an effective method for achieving coherence and improving forecast accuracy. However, the value of reconciled forecasts in downstream decision-making tasks has been mostly overlooked. In a multi-agent setup with heterogeneous loss functions, this oversight may lead to unfair outcomes, hence resulting in conflicts during the reconciliation process. To address this, we propose a value-oriented forecast reconciliation approach that focuses on the forecast value for individual agents. Fairness is ensured through the use of a Nash bargaining framework. Specifically, we model this problem as a cooperative bargaining game, where each agent aims to optimize their own gain while contributing to the overall reconciliation process. We then present a primal-dual algorithm for parameter estimation based on empirical risk minimization. From an application perspective, we consider an aggregated wind energy trading problem, where profits are distributed using a weighted allocation rule. We demonstrate the effectiveness of our approach through several numerical experiments, showing that it consistently results in increased profits for all agents involved.

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