Future Bridge is excited to welcome you to the Power Price Forecasting Summit 2023 on the 5-6th of June in Milan, Italy

With the increase in energy supply volatility there emerges a greater need for better power price forecasting analysis.

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About Conference

We aim to provide powerful content for our attendees

Encouraged by the successful events series on Power Price Forecasting Future Bridge is excited to welcome
you to the 3rd edition in June 2023.

The 3rd Power Price Forecasting Summit is a hybrid event that will be physically held in Milan, Italy. The Conference
aims to bring together the senior decision-makers from the analytic departments of power generation and
energy trading companies, energy utilities, and electricity TSO/DSO for a 2-day business networking event. During
the event, attendees will be able to participate in a program that presents case studies and panel discussions on
topics related to the electricity industry, including day-ahead and intraday forecasting, price modeling, and
long-term price analysis. These discussions will provide an opportunity for attendees to engage in meaningful
exchanges and delve into the challenges faced by the industry.

Forecasting power prices is a highly complex process influenced by numerous external factors such as weather
forecasts, transmission conditions, government regulations, and market conditions. Over the past two years,
energy markets have witnessed unprecedented volatility due to the economic turmoil caused by COVID-19,
geopolitical tensions, and changes in demand caused by the shift to carbon-free energy. This volatility has led to
fluctuations and record prices in energy markets. The Clean Energy package 2030 will accelerate the shutdown of
thermal and nuclear baseload generation, further reducing supply.

As the energy supply becomes more volatile, there is a growing need for an improved ability to forecast changes
in supply and demand. In the Summer Edition of the Power Price Forecasting summit, we will cover various topics

such as the penetration of renewables, the role of gas in the current market, regulatory changes, technology-driv-
en modeling, sector coupling analysis, the effect of raw material shortages, pricing for environmental and RES

trading, and more.

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Who Should Attend?
VPs, Directors, Heads, Managers, Analysts of the following divisions:

Program Highlights

Power Market Outlook

The outlook for price modeling in the coming year and the scope of work needed to improve the forecasting accuracy
Penetration of renewables
Future prognosis for conventional energy sources
The role of gas on the current market: regulatory changes and dealing with a possible shortage
Sector coupling: outlook, analysis and perspectives (Power, Gas, Heat, Hydrogen, etc.)
Methods for addressing regulatory changes
Plan towards energy efficiency for cutting back on gas use
Implications of the trend toward post-subsidy world for predicting power prices
Smart meters and their effect on price forecasting

Long Term

Data-driven modeling for long-term electricity price forecasting
Long-term forecasting and the impact of the deterministic approach and price sensitivity
Incorporating statistical analysis into fundamental models for long-term forecasts
Long-term electricity forecasting using smart meter data
Incorporating jumps and cojumps into long-term forecasts
Embedding calendar information into a neural network in long-term modelling
Econometric modelling for long-term power price forecasting

Short Term

Advanced techniques for day-ahead forecasting
Forecasting daily electricity prices with monthly macroeconomic variables
Day-ahead power volatility forecasting and modellingStatistical techniques for short-term forecasts
Stochastic models for short-term derivative price forecasting
The applications of AMI (Advanced Metering Infrastructure) data for short-term models
Identifying the factors and techniques involved in intraday price forecasting
Short-term electricity forecasting using smart meter data
Enhancing balancing market and intraday forecasts with sub-zonal modelling
Predicting imbalance prices and probabilistic forecasting

Strategies For Forecasting

Technology-driven modelling
Digitalisation as a means to improve data reliability
Selecting the most efficient models utilising Machine Learning
Bidding Zone Review
Evaluating shared market models vs standalone market models
The impact of market coupling and market splitting on price forecasting
AI models in price forecasting
Improving forecast accuracy by combining univariate and multivariate frameworks
Microprediction in power price forecasting
Evaluating the effectiveness of hybrid approaches that incorporate artificial intelligence
Environmental and RES trading pricing
Climate scenario strategies and integrated assessment models
Role of simulating scenarios in power price forecasting