Deep reinforcement learning–based approach for optimizing energy conversion in integrated electrical and heating system with renewable energy
With advanced information technologies applied in integrated energy systems (IESs),
controlling the energy conversion has become an effective method for improving grid …
controlling the energy conversion has become an effective method for improving grid …
Effects of regulating the European Internal Market on the integration of variable renewable energy
The new proposal for regulating the European Internal Market for Electricity (EIME) can
motivate the harmonization of the various National markets. The process of harmonizing the …
motivate the harmonization of the various National markets. The process of harmonizing the …
Application of stochastic dual dynamic programming to the real-time dispatch of storage under renewable supply uncertainty
This paper presents a multistage stochastic programming formulation of a transmission-
constrained economic dispatch subject to multiarea renewable production uncertainty, with …
constrained economic dispatch subject to multiarea renewable production uncertainty, with …
On-line classification of coal combustion quality using nonlinear SVM for improved neural network NOx emission rate prediction
A nonlinear support vector machine (SVM) uses engineered features to classify the quality of
currently combusting coal as it is fired in an operating electric utility generator. The SVM …
currently combusting coal as it is fired in an operating electric utility generator. The SVM …
[HTML][HTML] Strategic investment decisions in an oligopoly with a competitive fringe: An equilibrium problem with equilibrium constraints approach
MT Devine, S Siddiqui - European Journal of Operational Research, 2023 - Elsevier
Modern wholesale electricity markets often have producers who exercise market power. The
standard way to model market power in an oligopoly with a competitive fringe is by using …
standard way to model market power in an oligopoly with a competitive fringe is by using …
Applications of bilevel optimization in energy and electricity markets
Ever since the beginning of the liberalization process of the energy sector and the arrival of
electricity markets, decision making has gone away from centralized planners and has …
electricity markets, decision making has gone away from centralized planners and has …
Do intermittent renewables threaten the electricity supply security?
M Liebensteiner, M Wrienz - Energy Economics, 2020 - Elsevier
Around the globe, intermittent renewable energies in the form of wind and solar power are
on the rise. Their subsidization can be seen as a market intervention, which may deter …
on the rise. Their subsidization can be seen as a market intervention, which may deter …
Optimal scheduling of a wind energy dominated distribution network via a deep reinforcement learning approach
With the development of clean energy systems, large-scale renewable energy is being
connected to the traditional distribution network, which also brings new challenges to the …
connected to the traditional distribution network, which also brings new challenges to the …
[HTML][HTML] Pricing and hedging wind power prediction risk with binary option contracts
In markets with a high proportion of wind generation, high wind outputs tend to induce low
market prices and, alternatively, high prices often occur under low wind output conditions …
market prices and, alternatively, high prices often occur under low wind output conditions …
A review of machine learning applications in electricity market studies
S Mohammadi, MR Hesamzadeh… - … on Intelligent Grid …, 2020 - ieeexplore.ieee.org
Liberalized electricity markets have been studied for the past few decades with different
mathematical techniques. Operating these markets under the growing uncertainties has …
mathematical techniques. Operating these markets under the growing uncertainties has …