Closed-loop simulation testing of a probabilistic DR framework for Day Ahead Market participation applied to Battery Energy Storage Systems

In this manuscript, we test the operational performance decrease of a probabilistic framework for Demand Response (DR). We use Day Ahead Market (DAM) price scenarios generated by a Combined Quantile Regression Deep Neural Network (CQR-DNN) and a Non-parametric Bayesian Network (NPBN) to maximise profit of a Battery Energy Storage System (BESS)...

Learning from Demonstrations of Critical Driving Behaviours Using Driver’s Risk Field

In recent years, imitation learning (IL) has been widely used in industry as the core of autonomous vehicle (AV) planning modules. However, previous work on IL planners shows sample inefficiency and low generalisation in safety-critical scenarios, on which they are rarely tested. As a result, IL planners can reach a performance plateau where...

Day Ahead Market price scenario generation using a Combined Quantile Regression Deep Neural Network and a Non-parametric Bayesian Network: A framework for risk-based Demand Response

In this manuscript we propose a methodology to generate electricity price scenarios from probabilistic forecasts. Using a Combined Quantile Regression Deep Neural Network, we forecast hourly marginal price distribution quantiles for the DAM on which we fit parametric distributions. A Non-parametric Bayesian Network (BN) is applied to sample from...

Strategic Airline Crew Sizing: A Two-Stage Stochastic Optimisation Approach

This paper introduces a new two-stage stochastic optimisation approach for the strategic airline crew planning problem with uncertain demand. The developed model provides the airline with a cockpit crew composition plan per crew position before the flight schedule and crew demand are known. This is done by estimating future crew demand and by...

A probabilistic building characterization method for district energy simulations

To assess the impact of implementing energy efficiency and renewable energy measures, urban building energy models are emerging. In these models, due to the lack of data, the natural variability of the existing building stock is often highly underestimated and uncertainty on the simulated energy use arises. Therefore, this work proposes a...

Comparing electric vehicle charging strategies in stochastic microgrid optimization

Renewable energy sources, e.g. solar energy and wind energy, have gained popularity as an alternative means of energy production as they do not reinforce global warming. In addition, more and more electrical appliances (e.g. electric vehicles, induction cookers, and heat pumps) are used as a substitute for appliances that need non-renewable...