Prediction Markets for Probabilistic Forecasting of Renewable Energy Sources

Shamsi, Mahdieh; Cuffe, Paul

doi:10.1109/tste.2021.3112916

Cited by 10 publications

(4 citation statements)

References 42 publications

(57 reference statements)

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“…Prediction markets are a systematic approach for implementing the wisdom of the crowd principle where the participants have monetary incentives to reveal truthful information. A classic application of these markets is forecasting uncertain outcomes of events and has been proposed for renewable forecasting in [10]. In such a forecasting application, the prediction market asks, for instance, will there be less than 10 mwh wind energy production tomorrow?, the participants then freely bet on the outcome (Yes or No possible answers to that question) and the instantaneous price of shares represents the participants' aggregate forecast of the outcome with high accuracy [11].…”

Section: B Relevant Literaturementioning

confidence: 99%

Towards Conditional Prediction Markets as Policy-Making Instruments for the Promotion of Renewable Energy

Shamsi

Cuffe

2022

2022 International Conference on Smart Energy Systems and Technologies (SEST)

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In prediction markets participants bet on the outcome of uncertain future events and the instantaneous price of such shares then represents an accurate forecasting signal. This paper demonstrates how conditional prediction markets can be employed as decision support tools to identify effective policies for the promotion of renewable energy. In this model, the policy maker's objective (e.g. achievement of renewable generation targets, social welfare, carbon emission level, etc.) is defined as the settlement metric of the prediction market; participants speculate on whether this metric will be achieved, conditional on each of available policy alternatives being implemented. For instance, one prediction market could ask will the installed capacity of renewable generation in a specific region exceed 6 gw by the end of the year 2023, conditional on implementing a feed-in-tariff policy ?; another prediction market may ask will the installed capacity of renewable generation in a specific region exceed 6 gw until the end of the year 2023 conditional on implementing renewable portfolio standards policy? The policy with the highest market price can be interpreted as the option believed by the market participants as having the best prospects for acheiving the installed capacity target of 6 gw. We have simulated the evolution of prices within such a prediction market, where an automated market maker aggregates the trades and settles the market. By using the proposed approach, a case study evaluating two renewable support schemes (comparing feed-in-tariff and renewable portfolio standards) in achieving the renewable generation target is analysed.

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Section: B Relevant Literaturementioning

confidence: 99%

Towards Conditional Prediction Markets as Policy-Making Instruments for the Promotion of Renewable Energy

Shamsi

Cuffe

2022

2022 International Conference on Smart Energy Systems and Technologies (SEST)

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“…First, let us introduce the forecasting markets that are designed to predict an event e.g. renewable energy generation [24]. Generally, in such markets, the market participants (forecasters) sell predictions in the form of a probability distribution; then the true outcome of the event is observed and the market pays each expert based on the quality of their predictions.…”

Section: Introductionmentioning

confidence: 99%

Online coalitional games for real-time payoff distribution with applications to energy markets

Raja¹,

Grammatico²

2023

Preprint

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Motivated by the markets operating on fast time scales, we present a framework for online coalitional games with time-varying coalitional values and propose real-time payoff distribution mechanisms. Specifically, we design two online distributed algorithms to track the Shapley value and the core, the two most widely studied payoff distribution criteria in coalitional game theory. We show that the payoff distribution trajectory resulting from our proposed algorithms converges to a neighborhood of the time-varying solutions. We adopt an operatortheoretic perspective to show the convergence of our algorithms. Numerical simulations of a real-time local electricity market and cooperative energy forecasting market illustrate the performance of our algorithms: the difference between online payoffs and static payoffs (Shapley and the core) to the participants is little; online algorithms considerably improve the scalability of the mechanism with respect to the number of market participants.

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“…Consequently, the share price indicates the aggregate opinion on the probability of a candidate's win. Although prediction markets can elicit forecasts of discrete events in diverse areas of applications (Shamsi & Cuffe, 2022), here we are interested in a general market framework where the forecasters can report a forecast even in terms of a continuous probability distribution function. Prediction markets have been empirically shown to work well in several use cases, e.g., at Iowa Electronic Markets (Iowa, 2022).…”

Section: Introductionmentioning

confidence: 99%

A Market for Trading Forecasts: A Wagering Mechanism

Raja¹,

Kazempour²,

Grammatico³

2022

Preprint

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The ever-increasing interest in the collection of data by advancing technical and social sectors makes it distributed in terms of ownership. Also, the diverse expertise of these owners results in the extraction of varying quality of predictive information. Thus, the platforms for pooling forecasts based on distributed data and heterogeneous predictive skills allow gaining a collective value for a prediction task. For this purpose, we design a wagering-based forecast elicitation market platform, where a buyer intending to improve their forecasts posts a prediction task, and sellers respond to it with their forecast reports and wagers. This market delivers an aggregated forecast to the buyer (pre-event) and allocates a payoff to the sellers (post-event) for their contribution. We propose a payoff mechanism and prove that it satisfies several desirable economic properties, including those specific to electronic platforms. Furthermore, we discuss the properties of the scoring rules that allow us to provide ex-ante theoretical support for showing that the quantile averaging produces higher-quality aggregate forecasts in terms of scores, compared to the widely used linear pooling methods. Finally, we provide numerical examples to illustrate the structure and properties of the proposed market platform.

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Prediction Markets for Probabilistic Forecasting of Renewable Energy Sources

Cited by 10 publications

References 42 publications

Towards Conditional Prediction Markets as Policy-Making Instruments for the Promotion of Renewable Energy

Towards Conditional Prediction Markets as Policy-Making Instruments for the Promotion of Renewable Energy

Online coalitional games for real-time payoff distribution with applications to energy markets

A Market for Trading Forecasts: A Wagering Mechanism

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