Optimal Electrical Dispatch by Time Blocks in Systems with Conventional Generation, Renewable, and Storage Systems Using DC Flows
Source abstract
Abstract
Sustained demand growth and the increasing share of renewable energy sources pose challenges for the operation of modern electrical systems. The variability in wind and solar photovoltaic generation causes temporary imbalances between supply and demand, requiring the incorporation of energy management and storage strategies to guarantee supply. In this context, the need arises to develop optimization models that allow for efficient energy dispatch, minimizing costs and promoting the appropriate use of both conventional and renewable resources. This study formulated a time block dispatch optimization model implemented in the IEEE 24-node system, integrating thermal, hydroelectric, photovoltaic, wind, and energy storage systems. The methodology was based on DC power flows and was developed in MATLAB R2024b, incorporating nodal balance constraints, transmission and generation capacity limits, as well as the operating conditions of the storage systems. The model allowed for the evaluation of both energy and economic performance, validating its behavior under conditions of peak demand and renewable variability. The results demonstrate that the inclusion of energy storage systems allows for a reduction in high-cost thermal generation, optimizing demand coverage with a greater share of renewable energy. An average storage efficiency of 85.5% was achieved, and total system costs were reduced by USD 40,392.39 per day, equivalent to annual savings of USD 14.75 million. Furthermore, power flows remained below 85% of transmission capacity, confirming the proper operation of the grid. In this sense, the model fulfills the proposed objectives and proves to be a tool for energy planning and the technical-economic integration of storage in electrical networks.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Integrated Energy Systems Optimization · Electric Power System Optimization · Optimal Power Flow Distribution
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Department of Electrical Engineering, Universidad Politécnica Salesiana, Quito 170517, Ecuador
GIPI Group, Department of Electrical Engineering, Universidad Politécnica Salesiana, Guayaquil 090150, Ecuador
Funding
Universidad Politécnica Salesiana
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