The field of energy management and optimization is moving towards increased integration of renewable energy sources and advanced control systems to improve efficiency and reduce costs. Researchers are exploring innovative approaches to optimize energy consumption and production in various sectors, including manufacturing, district heating, and water distribution networks. A key trend is the development of model predictive control (MPC) frameworks that can adapt to changing energy availability and demand in real-time. These frameworks are being applied to optimize production scheduling, pump scheduling, and thermal energy storage systems. Noteworthy papers include:

• A bi-level MPC framework that jointly optimizes product prices and production scheduling with explicit consideration of renewable energy availability, demonstrating the potential to reduce grid energy costs while increasing profit.
• A robust predictive control method for pump scheduling in water distribution networks, which surpasses nominal and constraint-tightening MPC approaches in terms of meeting constraints and provides comparable economic outcomes.