Generating Electricity Price Forecasting Scenarios to Analyze Whether Price Uncertainty Impacts Tariff Performance

A higher share of renewables and electric vehicles increase the risk of congestion in electricity distribution systems. New distribution tariff designs have been proposed to prevent congestion. However, most modeling of tariff performance assumes deterministic price information. This paper proposes a method to assess the impact of price...

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...

Low-complexity control algorithm for decentralised demand response using thermostatic loads

Thermostatically controlled loads such as refrigerators are exceptionally suitable as a flexible demand resource. This paper derives a decentralised load control algorithm for refrigerators. It is adapted from an existing continuous time control approach, with the aim to achieve low computational complexity and an ability to handle discrete time...

Demand Response With Micro-CHP Systems

With the increasing application of distributed energy resources and novel information technologies in the electricity infrastructure, innovative possibilities to incorporate the demand side more actively in power system operation are enabled. A promising, controllable, residential distributed generation technology is a microcombined heat and...

Model predictive control of fuel cell micro cogeneration systems

With the increasing application of distributed energy resources and information technologies in the electricity infrastructure, innovative possibilities for incorporating the demand side more actively in power system operation are enabled. At the residential level energy costs could be reduced with intelligent price-based control concepts ...