A review on the integrated optimization techniques and machine learning approaches for modeling, prediction, and decision making on integrated energy systems
The optimal co-planning of the integrated energy system (IES) and machine learning (ML)
application on the multivariable prediction of IES parameters have mostly been carried out …
application on the multivariable prediction of IES parameters have mostly been carried out …
[HTML][HTML] Transformation and linearization techniques in optimization: A state-of-the-art survey
M Asghari, AM Fathollahi-Fard… - Mathematics, 2022 - mdpi.com
To formulate a real-world optimization problem, it is sometimes necessary to adopt a set of
non-linear terms in the mathematical formulation to capture specific operational …
non-linear terms in the mathematical formulation to capture specific operational …
Smart charging of electric vehicles considering photovoltaic power production and electricity consumption: A review
R Fachrizal, M Shepero, D van der Meer… - ETransportation, 2020 - Elsevier
Photovoltaics (PV) and electric vehicles (EVs) are two emerging technologies often
considered as cornerstones in the energy and transportation systems of future sustainable …
considered as cornerstones in the energy and transportation systems of future sustainable …
Data-driven building energy modelling–An analysis of the potential for generalisation through interpretable machine learning
Data-driven building energy modelling techniques have proven to be effective in multiple
applications. However, the debate around the possibility of generalisation is open …
applications. However, the debate around the possibility of generalisation is open …
PEV fast-charging station siting and sizing on coupled transportation and power networks
Plug-in electric vehicle (PEV) charging stations couple future transportation systems and
power systems. That is, PEV driving and charging behavior will influence the two networks …
power systems. That is, PEV driving and charging behavior will influence the two networks …
Interval optimization based coordination of demand response and battery energy storage system considering SOC management in a microgrid
Microgrids can effectively integrate distributed generation (DG) to supply power to local
loads. However, uncertainties from renewable DG and loads may lead to increased …
loads. However, uncertainties from renewable DG and loads may lead to increased …
Coordinating urban power-traffic networks: A subsidy-based Nash–Stackelberg–Nash game model
The growing penetration of electric vehicles results in interdependence between power and
transportation networks, in which the coordination among drivers and network operators is …
transportation networks, in which the coordination among drivers and network operators is …
Power–transportation coordination: Toward a hybrid economic-emission dispatch model
The increasing penetration of electric vehicles (EVs) results in growing interdependency
between power and transportation networks. This paper proposes a hybrid economic …
between power and transportation networks. This paper proposes a hybrid economic …
Are complex energy system models more accurate? An intra-model comparison of power system optimization models
J Priesmann, L Nolting, A Praktiknjo - Applied Energy, 2019 - Elsevier
Today, optimization models are by far the most popular choice when analyzing energy
systems. Impressive advances in computer and data sciences have allowed for a multitude …
systems. Impressive advances in computer and data sciences have allowed for a multitude …
Synchromodal transport planning with flexible services: Mathematical model and heuristic algorithm
As a critical feature of synchromodal transport (ST), service flexibility plays an important role
in improving the utilization of resources to reduce costs, emissions, congestions, and delays …
in improving the utilization of resources to reduce costs, emissions, congestions, and delays …