scholarly journals Understanding Power Market Dynamics by Reflecting Market Interrelations and Flexibility-Oriented Bidding Strategies

Energies ◽  
2022 ◽  
Vol 15 (2) ◽  
pp. 494
Author(s):  
Ramiz Qussous ◽  
Nick Harder ◽  
Anke Weidlich

Power markets are becoming increasingly complex as they move towards (i) integrating higher amounts of variable renewable energy, (ii) shorter trading intervals and lead times, (iii) stronger interdependencies between related markets, and (iv) increasing energy system integration. For designing them appropriately, an enhanced understanding of the dynamics in interrelated short-term physical power and energy markets is required, which can be supported by market simulations. In this paper, we present an agent-based power market simulation model with rule-based bidding strategies that addresses the above-mentioned challenges, and represents market participants individually with a high level of technical detail. By allowing agents to participate in several interrelated markets, such as the energy-only market, a procurement platform for control reserve and a local heat market representing district heating systems, cross-market opportunity costs are well reflected. With this approach, we were able to reproduce EPEX SPOT market outcomes for the German bidding zone with a high level of accuracy (mean absolute percentage error of 8 €/MWh for the years 2016–2019). We were also able to model negative market prices at the energy-only market realistically, and observed that the occurrence of negative prices differs among data inputs used. The simulation model provides a useful tool for investigating different short-term physical power/energy market structures and designs in the future. The modular structure also enables extension to further related markets, such as fuel, CO2, or derivative markets.

Energy ◽  
2020 ◽  
Vol 198 ◽  
pp. 117311 ◽  
Author(s):  
Pernille Seljom ◽  
Eva Rosenberg ◽  
Linn Emelie Schäffer ◽  
Marte Fodstad

2021 ◽  
Vol 9 ◽  
Author(s):  
Danhong Wang ◽  
Xiang Li ◽  
Julien Marquant ◽  
Jan Carmeliet ◽  
Kristina Orehounig

This paper investigates modeling methods with thermal network representation under the scope of the optimal design and operation of Distributed Multi-Energy System (D-MES). Two modeling approaches are compared: A Mixed‐Integer Linear Programming (MILP) optimization model and a district heating network (DHN) simulation model. The MILP model was developed for the simultaneous design of the network layout, the sizing, and locations of energy generation and storage technologies to minimize both costs and carbon emissions. The thermal network is represented with a simplified linear approximation. The DHN simulation model is a thermal-hydraulic model to address the non-linear operational performance regarding hourly heat losses, pumping energy, and temperature distribution along with the network. The discrepancies in the network’s costs and operational performances from the two models are identified. The MILP model is further improved by adding new constraints. Results from both MILP models are compared and demonstrated with a case study. It reveals that the state-of-art MILP-model with simplified network representation suffices for optimal selection and sizing for most of the technologies. Although more computationally intensive, the refined model can address the operational issues with distributed design solutions.


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