4 Presentations

• 
  03:30 PM - 03:55 PM

  Studying the Impact of Reserve Capacity in Transmission Lines

  • Sophia Watret, presenter, McGill University

  Many countries have committed to expanding renewable energy generation, such as wind and solar power, in the coming decades. Wind and solar power are variable renewable energy sources (VRE). The uncertainty inherent in the variable renewable energy sources presents a need for high flexibility in power systems to maintain the delicate balance between generation and demand of power. Traditionally flexibility comes from the scheduling of reserve capacity in generation. This research explores the impact of adding flexibility in the transmission system through reserve capacity on the transmission lines. Four case studies of transmission systems are studied using two optimization models. One optimization model is stochastic with uncertainty of the wind and one is without uncertainty. The two optimization model results are compared financially and operationally to determine the impact of reserved headroom in the transmission lines.

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  03:55 PM - 04:20 PM

  Optimal Placement of Wind Sensors for Enhancing the Airflow Field Reconstruction and Prediction around High-Rise Buildings

  • Arash Kamaliha, presenter, Concordia University
  • Fuzhan Nasiri, Concordia University

  Urban wind patern analysis can help determine the movement and characteristics of wind in the urban landscape. These characteristics are crucial for studying the urban climate, improving eco-friendly urban design, and creating sustainable inventions. Moreover, urban wind affects building performance, air condition, pedestrian experience, and even the capacity of green energy. Field measurements is essential to get accurate and real-world wind paterns in densely populated cities. However, sensors cannot be placed randomly owing to costs, accessibility, and work to assemble and relocate them. Hence, an optimal sensor placement approach substantitially enhances the efficiency of capturing the information from sensor for the high-resolution flow field reconstruction. In this work, an optimal sensor placement is applied based on a QR factorization extracted from sparsity-promoting dynamic mode decomposition (SP-DMD) algorithm. SP-DMD can idenfify the dominant spatial and temporal airflow paterns from high-dimensional fluid dynamic data around tall buildings. The trade-of between the accuracy of reconstructed data and the number of dynamic modes is achieved by modifying the least-squares error between snapshot matrices and DMD mode combinations, with the addition of a penalty mechanism to effectively promote sparsity. The results show this method leads to a large increase in sensors’ performance and more effective and precise reconstructions of wind velocity data.

• 
  04:20 PM - 04:45 PM

  Optimizing Solar Energy Storage in Africa: The Case of the Noor 4 photovoltaic power plant

  • Meryam Chafiq, presenter, PhD student- Mohammadia School of Engineering, Rabat Morocco

  The expansion of solar photovoltaic power plants in Africa, illustrated by ambitious projects such as Noor 4 in Ouarzazate, Morocco, marks a significant advance in the renewable energy sector. However, this sector faces a major challenge: the lack of efficient energy storage systems, which limits the management of variations in solar energy production. Nevertheless, there has been a noticeable evolution with the progressive integration of storage systems, notably using batteries, improving the reliability and efficiency of photovoltaic installations.
  The main objective of this work is to provide a decision-making framework for stakeholders and operators of photovoltaic power plants. This proposal is based on multi-objective optimization. The goal is to achieve both optimal battery capacity, an appropriate energy dispatch strategy, and a judicious selection of the most appropriate battery technology, while emphasizing the long-term performance of the storage system. This approach seeks to maximize financial viability, seamless integration into the grid and the lifetime of the storage system. Through the analysis of various mathematical models, this work focuses on the case of Noor 4, offering a conceptual model relevant to the African context and serving as a methodological guide for decision makers facing similar challenges.

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  04:45 PM - 05:10 PM

  A Novel Approach to Nonlinear Short-Term Hydropower Optimization using a Combination of Heuristic and Meta-heuristic Algorithms

  • Mohammad Jafari Aminabadi, presenter,
  • Sara Séguin, Université du Québec à Chicoutimi
  • Issouf Fofana,

  A Mixed Integer Nonlinear Programming (MINLP) formulation is proposed for optimizing short-term hydropower operations, taking into account various operational constraints such as demand and startup costs. In view of the difficulty of solving the MINLP and the fact that it is often considered impossible, three methods are proposed based on reducing the complexity, which are hybridized with the exact solver. Method A is a binary genetic algorithm, Method B is an iterative heuristic method, and Method C is a genetic algorithm that utilizes the iterative heuristic method.
  In the case study, all three methods are compared, and Method C, which combines the advantages of both Methods A and B, achieves better results in the majority of cases. While Method B is a fast method that converges to the result after several iterations, the objective function value is lower than those of Methods A and C.
  The evaluation of the proposed methods involves comparing them with optimal solutions, which demonstrate their efficacy in achieving favorable outcomes.