Approximating Nash Equilibrium in Day-ahead Electricity Market Bidding with Multi-agent Deep Reinforcement Learning
نویسندگان
چکیده
منابع مشابه
Agent-Based Modeling of Day-Ahead Real Time Pricing in a Pool-Based Electricity Market
In this paper, an agent-based structure of the electricity retail market is presented based on which day-ahead (DA) energy procurement for customers is modeled. Here, we focus on operation of only one Retail Energy Provider (REP) agent who purchases energy from DA pool-based wholesale market and offers DA real time tariffs to a group of its customers. As a model of customer response to the offe...
متن کاملOptimal Bidding Strategy for GENCO with Green Power in Day-ahead Electricity Market
The electricity market has evolved from a regulated monopoly to a more liberalized competitive market, which allows a generating company (GENCO) to bid to provide energy. The two-period structure of the electricity market (day-ahead and real-time market) introduces a mechanism for determining the GENCO’s optimal bidding strategy. The difference between clearing prices for each period adds uncer...
متن کاملMulti-Agent Deep Reinforcement Learning
This work introduces a novel approach for solving reinforcement learning problems in multi-agent settings. We propose a state reformulation of multi-agent problems in R that allows the system state to be represented in an image-like fashion. We then apply deep reinforcement learning techniques with a convolution neural network as the Q-value function approximator to learn distributed multi-agen...
متن کاملModeling and Detecting Bidding Anomalies in Day-ahead Electricity Markets
Virtual bids were introduced in U.S. wholesale electricity markets to exploit arbitrage opportunities arising from expected price differences between day-ahead and real-time energy markets. These financial instruments have interactions with other elements of the electricity market design. For instance, virtual bids could affect day-ahead market-clearing prices so as to enhance the value of Fina...
متن کاملOptimal Bidding Strategies for Wind Power Producers in the Day-ahead Electricity Market
Wind Power Producers (WPPs) seek to maximize profit and minimize the imbalance costs when bidding into the day-ahead market, but uncertainties in the hourly available wind and forecasting errors make the bidding risky. This paper assumes that hourly wind power output given by the forecast follows a normal distribution, and proposes three different bidding strategies, i.e., the expected profit-m...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Journal of Modern Power Systems and Clean Energy
سال: 2021
ISSN: 2196-5625
DOI: 10.35833/mpce.2020.000502