Book contents
- Frontmatter
- Contents
- List of Contributors
- Preface
- Part I Statistical Learning
- Part II Data-Driven Anomaly Detection
- Part III Data Quality, Integrity, and Privacy
- Part IV Signal Processing
- Part V Large-Scale Optimization
- Part VI Game Theory
- 19 Distributed Power Consumption Scheduling
- 20 Electric Vehicles and Mean-Field
- 21 Prosumer Behavior: Decision Making with Bounded Horizon
- 22 Storage Allocation for Price Volatility Management in Electricity Markets
- Index
21 - Prosumer Behavior: Decision Making with Bounded Horizon
from Part VI - Game Theory
Published online by Cambridge University Press: 22 March 2021
- Frontmatter
- Contents
- List of Contributors
- Preface
- Part I Statistical Learning
- Part II Data-Driven Anomaly Detection
- Part III Data Quality, Integrity, and Privacy
- Part IV Signal Processing
- Part V Large-Scale Optimization
- Part VI Game Theory
- 19 Distributed Power Consumption Scheduling
- 20 Electric Vehicles and Mean-Field
- 21 Prosumer Behavior: Decision Making with Bounded Horizon
- 22 Storage Allocation for Price Volatility Management in Electricity Markets
- Index
Summary
Studies of prosumer decision making in the smart grid have focused on a single decision within the framework of expected utility theory (EUT) and behavioral theories such as Prospect Theory. This chapter studies prosumer decision making in a more natural market situation in which a prosumer has to decide whether to make a sale of solar energy units generated at her home every day or hold (store) the energy units in anticipation of a future sale at a better price. Specifically, it proposes a new behavioral model that extends EUT to take into account bounded horizons (in terms of the number of days) that prosumers implicitly impose on their decision making in arriving at “hold” or “sell” decisions of energy units. The new behavioral model assumes that humans make decisions that will affect their lives within a bounded horizon regardless of how far into the future their units may be sold. Modeling the utility of the prosumer using parameters such as the offered price on a day, the available energy units on a day, and the probabilities of the forecast prices, both traditional EUT and the proposed behavioral model with bounded horizons are fit to prosumer data.
- Type
- Chapter
- Information
- Advanced Data Analytics for Power Systems , pp. 524 - 544Publisher: Cambridge University PressPrint publication year: 2021
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