Exploring the Dynamic Landscape of Economic Dispatch: A Comprehensive Review of Stochastic Programming Techniques

Ensuring the provision of high-quality and continuous power at an affordable rate stands as the primary objective of power systems. To achieve this goal, utilities devise economic dispatch schedules for each quarter-hour time slot, leveraging stochastic programming methodologies. This becomes imperative due to the inherent uncertainty associated with renewable energy sources, heavily reliant on weather and climate conditions. Dynamic Programming, Stochastic Dynamic Programming, and Stochastic Dual Dynamic Programming techniques are deployed to formulate real-time economic dispatch schedules. Notably, while cost remains a pivotal factor, the emphasis shifts towards economic value, particularly water value, during the dispatch process. Various methodologies have been introduced to ascertain the optimal economic dispatch schedule, considering the dynamic landscape of economic dispatch. This landscape plays a crucial role in the design, analysis, planning, and modelling of smart energy systems, facilitating informed decisions for the green transformation of energy supply and demand systems towards future smart renewable energy solutions. This research paper offers a comprehensive literature review of stochastic programming techniques applied in economic dispatch, shedding light on their implications for smart energy systems.