A5074891694- Electric Power System Optimization
- Energy Load and Power Forecasting
- Smart Grid Energy Management
- Water resources management and optimization
- Electric Vehicles and Infrastructure
- Advanced Battery Technologies Research
- Integrated Energy Systems Optimization
- Energy, Environment, and Transportation Policies
- Energy Efficiency and Management
- Wind Energy Research and Development
- Capital Investment and Risk Analysis
- Risk and Portfolio Optimization
- Quality and Safety in Healthcare
- Market Dynamics and Volatility
- Optimal Power Flow Distribution
- Advanced Data Processing Techniques
- Electric and Hybrid Vehicle Technologies
- Hybrid Renewable Energy Systems
- Auction Theory and Applications
RISE Research Institutes of Sweden
2025
Technical University of Denmark
2019-2021
KTH Royal Institute of Technology
2011-2017
An aggregator acts as a middleman between the small customers and system operator (SO) offering mutually beneficial agreement to trade electric power, where each market player (system operator, vehicle (EV owner) has its own economic incentives. The EV aims maximize profit while trading energy providing balancing power in wholesale markets. This paper develops stochastic dynamic mixed integer linear program (SD-MILP) for optimal coordinated bidding of an from participating competitive...
The amount of wind power is growing significantly in the world. Large scale introduction system will increase need for improved short term planning models hydro power, because additional variations are introduced system. This huge uncertainties cause changes market and there be a value advanced techniques, that allow more flexibility hydropower generation by taking into account stochastic nature spot regulating markets, water inflow, future so on. application multi-stage optimization daily...
This paper develops a two-stage stochastic and dynamically updated multi-period mixed integer linear program (SD-MILP) for optimal coordinated bidding of an electric vehicle (EV) aggregator to maximize its profit from participating in competitive day-ahead, intra-day real-time markets. The hourly conditional value at risk (T-CVaR) is applied model the trading different objective SD-MILP modeled as convex combination expected T-CVaR measure. When market prices fleet mobility are uncertain,...
Many projections of near-future electricity system foresee a constantly increasing necessity power flexibility services. In particular, thanks to the growing presence renewable generation and innovative load technologies, distribution resources are becoming attractive productsin ancillary services markets. order open market gates flexibility, constant interactions between transmission operators required European project SmartNet is investigating in detail possible coordination schemes among...
It is understood that electricity generation from the waves and tides can be temporally spatially offset other, more established variable renewables, such as wind solar. However, it less well how this offsetting impact on power system operation. A novel modelling framework has been developed to quantify potential benefit of including higher proportions ocean energy within large-scale systems. Economic dispatch utilised model hourly supply–demand matching for a range sensitivity runs,...
The ongoing growth in wind power introduce huge amount of uncertainties to the market. stochastic nature these sources increases need for reserve real-time Having a flexible source, hydropower producer can provide and increase its profit. Therefore, build planning model, which will allocate available capacity different market places is an essential task price-taker producer. This paper uses optimal bidding model day-ahead considering balancing under prices. Specifically, built using linear...
The main purpose of this paper is to summarize the findings from simulating two stochastic short-term planning models for a price-taker hydropower producer. first model two-stage linear programming problem. Profound sensitivity analysis provided in terms volatility spot market prices and water inflow level. results show that problems effect considering price uncertainty higher compared level uncertainty. second generates optimal bids real-time uncertainties. While simultaneously bidding both...
This paper proposes a quadratic programming (QP) model for optimal coordinated production of risk-averse hydropower producer. The day-ahead, intra-day and real-time markets are considered. A rolling planning approach is used to take advantage sequential clearing mentioned markets. multi-period risk trading in different modelled as terms the objective function. To cope with uncertain prices, three price forecasting techniques used. best technique selected based on designed Markov switch....
Huge amount of uncertainties are being introduced to the power market because ongoing growth in renewable energy sources like wind and solar power. The intermittent nature these increases volatility day-ahead prices. Therefore, improving planning tools constructing an optimal bidding strategy is essential task for price-taker hydropower producer. This paper applies model under prices water inflow level. Specifically, built using a two-stage stochastic mixed integer linear programming...
Gradually replacing fossil-fueled vehicles in the transport sector with Electric Vehicles (EVs) may help ensure a sustainable future. With regard to charging electric load of EVs, optimal scheduling EV batteries, controlled by an aggregating agent, provide flexibility and increase system efficiency. This work proposes stochastic bilevel optimization problem based on Stackelberg game create price incentives that generate trading plans for aggregator day-ahead, intra-day real-time markets. The...
This paper develops a price-driven optimal bidding strategy to day-ahead and real-time markets for profit maximizer hydro power producer. The electricity prices in different market places are unknown when the takes place. problem is modeled as multi-stage stochastic program considering continuously clearing nature. Specifically that purpose rolling planning applied, which allow re-forecasting re-dispatching according arrival of new information. results have shown that, there value hydropower...
The accurate price forecasting of electricity market is crucial for profit maximizing producers and consumers in liberalized power markets. In all places (day-ahead, intra-day real-time) prediction needed to generate optimal bids maximize the profit. This paper first presents three methods day-ahead prices, namely Generalized Autoregressive Conditional Heterosedastic (GARCH), Holt-Winter (HW) Mean Reversion Jump Diffusion (MRJD). These are based on broad methodologies time series analysis,...
An aggregator is a business entity enabling smooth cooperation between System Operator (SO) and small customers to trade electric power. In this each market actor (aggregator, customer, system operator) looks for its own economic incentives. paper, we consider an aggregator, who manages portfolio of domestic heat pumps (HPs). The aims at maximizing profit while trading energy providing balancing power in wholesale markets. paper develops Mixed Integer Linear Program (MILP) optimal...
The EU is committed to reducing greenhouse gas emissions 80-95% below 1990 levels by 2050. To accomplish this goal the share of renewable energy sources have increase significantly. Challenges related keeping a high security supply raised while intermittent electricity generation increasing. increasing level RES production leads higher volatility in market prices. main challenges lay within modeling and simulation random variables. Therefore, assessment operation entire micro-grid should be...