SCRO / Journées de l'optimisation

HEC Montréal, 29-31 mai 2023


HEC Montréal, 29 — 31 mai 2023

Horaire Auteurs Mon horaire

MMESIII Methods and Models for the Energy Sector III

31 mai 2023 15h40 – 17h20

Salle: TAL Gestion globale d'actifs inc. (vert)

Présidée par Florian Mitjana

4 présentations

  • 15h40 - 16h05

    A Distributed Energy Management System for Multi-Microgrid Systems

    • Carlos Ceja-Espinosa, prés., University of Waterloo

    Environmental concerns have motivated a gradual transformation of power systems, focused on replacing fossil energy sources with renewable energy sources (RESs). However, due to their variability, the large-scale integration of RESs into existing power grids compromises their safe and reliable operation. Microgrids (MGs) are an appealing approach to enable high penetration of RESs and enhance the reliability of conventional power grids. More recently, the coordinated operation of multiple MGs as a single multi-microgrid (MMG) system has attracted attention due to the potential improvement in the overall system operation and the mutual benefits for all participating MGs, which originate from power exchanges among MGs and the main grid.

    In this presentation, a centralized MMG energy management system (EMS) model is discussed, formulated as a cost minimization problem that considers the operation of all MGs and their interactions among each other and the main grid. Then, a decomposition procedure based on Lagrangian relaxation is applied to obtain subproblems for each MG which are solved through a distributed optimization algorithm. A distributed MMG EMS has several advantages, such as preserving the privacy of each MG, enhancing the reliability and flexibility of the system, and reducing the computational burden for local MG controllers.

  • 16h05 - 16h30

    Economic analysis of local power storage for pumps in water distribution networks

    • Richard Perryman, prés., University of Toronto
    • Joshua A. Taylor, University of Toronto
    • Bryan Karney, University of Toronto

    Power outages cause significant damage to water distribution networks (WDNs) by creating large pressure changes when a pump suddenly stops working. We investigate the financial feasibility of installing local energy storage to power pumps in the event of an outage. This scheme benefits WDNs by reducing damage done to the network's elements, as well as potentially allowing for fewer mitigation elements, such as surge tanks, to be installed. The cost of implementing these storage units is offset by providing services to the power distribution network, including arbitrage and load shifting. The optimal sizing of the storage units is found, considering batteries, flywheels, and supercapacitors.

  • 16h30 - 16h55

    Electric system decarbonization for Northeastern North America: insights from a multistage, stochastic model

    • Florian Mitjana, prés., HEC Montréal
    • Michel Denault, HEC Montréal
    • Pierre-Olivier Pineau, HEC Montréal

    The decarbonization challenge requires deploying non-emitting generation capacities and the electrification of many sectors of the economy, leading to profound changes in the electricity sector and a growing electricity demand.

    This energy transition is a multi-scale problem that combines the expansion of generation and transmission capacity with the management of system operations. Capacity expansion must be planned for the long term to account for multi-year deployment, while system operations is about ensuring that hourly demand is met throughout the year.

    To account for these uncertainties in demand and cost evolution, we developed a multi-stage 2020-2050 stochastic investment and operation model that covers generation, transmission, and storage capacities. The model is calibrated to represent Northeastern North America (Ontario, Québec, Atlantic provinces, New York and New England).

    Our numerical results show that controlling demand growth will be essential to decarbonize the power system. Otherwise, the scale of the required electricity infrastructure could become prohibitive. We note that decisions made over the next decade, as well as whether new transmission lines are created, will have a significant impact on system costs.

  • 16h55 - 17h20

    CANCELED : A Robust Framework for Waste-to-Energy Technology Selection: A Case Study in Nova Scotia, Canada

    • Mostafa Mostafavi Sani, prés., PhD student at Dalhousie University
    • Hamid Afshari, Assistant Professor at Dalhousie University
    • Ahmed Saif, Associate Professor at Dalhousie University

    With recent advances in waste-to-energy technologies, the integration of municipal solid waste in energy recovery systems is becoming a promising alternative. However, it is still unclear how these technologies can be optimally combined, especially when the future price of energy and the quantity of waste are uncertain. Moreover, whether such uncertainties significantly influence the optimal design and cost/emissions tradeoff of energy recovery systems is an open question. This paper studies a multi-carrier energy infrastructure to generate energy from municipal solid waste, aiming to optimize the selection and size of waste-to-energy technologies. To account for uncertainty in electricity, heat, and hydrogen prices, as well as waste supply in the future, a two-stage robust optimization model is proposed to minimize the total annual cost (including an environmental penalty) of the waste-to-energy facility. On a real test case in Nova Scotia, Canada, the solution obtained from the robust model led to a 19.9% decrease in emissions compared to that of the deterministic model, albeit with an increase in cost under the current prices. Plasma arc gasification is selected as the optimal technology in the deterministic case, but pyrolysis outperforms it when the cost of hydrogen sufficiently decreases. Furthermore, hydrogen production becomes feasible only when its cost decreases by 36% or the system energy operation costs are reduced by 90%. The findings of this research provide strong evidence for the impact of parameter uncertainty on the optimal system design and performance, demonstrate the effectiveness of the proposed waste-to-energy technology selection framework, and identify the conditions under which the optimal technology mix changes.