Abstract
The escalating challenges posed by fossil fuel reliance, climate change, and increasing energy expenses have underscored the critical importance of optimizing energy systems. This paper addresses the economic dispatch (ED) challenge, which directs the optimization of the output of generation units to satisfy electricity and heat requirements while reducing operational expenses. In contrast to conventional economic dispatch methods, this research incorporates renewable energy sources (RESs), energy storage systems (ESSs), and combined heat and power (CHP) systems. This integrated strategy facilitates the concurrent optimization of electrical and thermal generation, culminating in a more comprehensive and efficient solution. A sophisticated scheduling model for combined heat, power, and electrical energy dispatch (CHPEED) has been devised, minimizing generation expenses. The suggested model accounts for practical constraints inherent in real-world power systems, such as prohibited operating regions, while also addressing the intricate relationships between heat and power generation in CHP units. Also, the nature of wind energy, photovoltaic systems, and load requirements within the realm of stochastic dynamic ED are considered. The general algebraic modeling system (GAMS) was utilized to solve the optimization problem. The cost without RES or ESS is $250,954.80, indicating a high reliance on costly energy sources. Integrating RES reduces costs to $247,616.42, highlighting savings through decreased fossil fuel dependency. The combination of RES and ESS achieves the lowest cost of $245,933.24, showcasing improvements in efficiency and supply-demand management via optimized energy utilization. Hence, the findings demonstrate the model's effectiveness in addressing uncertainties associated with renewable generation, ensuring reliability in meeting energy demands and validating the possible capability to enhance the sustainability and efficiency of energy systems.