Where does the literature stand on optimization regarding thermal controls to reduce the energy price?
Best insight from top research papers
The literature on thermal control optimization to reduce energy prices is advancing towards more efficient and cost-effective solutions. Various studies propose innovative methods to optimize heating, ventilation, and air-conditioning (HVAC) systems, utilize real-time optimization strategies for Ice Thermal Energy Storage (ITES) systems in commercial buildings, and introduce algorithms like the greedy variable neighborhood algorithm (GVNA) for demand response control in residential buildings. These approaches aim to minimize energy costs by improving control systems based on simulation results, shifting cooling loads to off-peak periods, and optimizing thermal storage controllers. By incorporating advanced techniques such as Markov decision processes (MDP), gradient-based learning (GB-L), and model predictive control (MPC), researchers are striving to enhance energy efficiency while maintaining thermal comfort levels under uncertain conditions.
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| Papers (5) | Insight |
|---|---|
| The literature proposes stochastic optimal control using a Markov decision process and gradient-based learning to reduce energy costs while enhancing human comfort in HVAC systems. | |
30 Mar 2019 | The literature emphasizes optimizing thermal systems to reduce energy consumption and environmental impact, focusing on efficiency, material consumption, and multi-objective design optimization. |
01 Oct 2018 7 Citations | Literature suggests real-time optimization tools like Fuzzy logic, Neural network, Closed-loop, and Model Predictive Control enhance thermal controls for reducing energy costs in commercial buildings. |
2 Citations | The literature supports using the Greedy Variable Neighborhood Algorithm for demand response control in residential thermal storage, reducing daily heating electricity costs by 3.5% to 11.4%. |
| The paper proposes optimizing thermal control through data collection, simulation, and training to monitor and control cooling and heat-generating elements, potentially reducing energy costs. |
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