SDDP - Energy Systems Operation Planning
SDDP is a stochastic dispatch model to optimize power systems, with flexible and detailed analysis of networks, fuels, and operation.
Explore SDDP 18: Now an Integrated Energy Planning Platform
Experience the future of energy planning with SDDP 18
SDDP is a stochastic dispatch model for electric power systems, with a detailed representation of transmission and fuel networks. It is used in long, medium, and short-term operational studies, being highly flexible regarding temporal and spatial detail levels. SDDP determines the optimal operating policy for systems involving various types of technologies.
SDDP 18
A unified experience for integrated energy planning
Modeling capabilities
Hydropower Plants
Variable production coefficient, evaporation, seepage, uncontrollable spill, etc.
Thermal Power Plants
Unit dispatch, combined cycle thermal power plants, non-linear specific consumption curve, fuel contracts.
Renewable Modeling
Detailed modeling and generation of synthetic scenarios for variable renewable energy sources with Time Series Lab.
Energy Efficiency
Regulations to reduce energy waste and environmental impact through power generation optimization.
Demand Side Management
Price response, signals by segment, by system, area, or bus level.
Reliability Analysis
Stochastic reliability study focusing on renewable sources and storage using Coral.
Storage Devices
Storage capacity, charge and discharge capabilities, efficiencies, ramp constraints.
Operational Reserves
Dynamic Probabilistic Reserve (DPR) based on renewable source scenarios.
Maintenance
User-defined or optimized plant maintenance.
And much more…
SDDP finds the system's optimal operating policy
The objective of SDDP is to minimize the sum of fuel purchase and transportation costs for thermal power plants, pollutant emission costs, operation and maintenance costs of hydropower and thermal power plants, transmission system use fees, unsupplied energy costs, and other penalties. In other words, the model calculates the lowest-cost operating policy for the system, considering all mentioned aspects.
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PSR solves large-scale multi-stage optimization problems under uncertainty
SDDP stands for Stochastic Dual Dynamic Programming, an algorithm developed by PSR in the 1980s to solve large-scale multi-stage optimization problems under uncertainty. It is not necessary to enumerate all combinations of reservoir levels, and the approximation of the future cost function is done through a Benders decomposition scheme.
The SDDP algorithm has been extended to various areas and has become the industry standard globally, with over 1,700 citations in scientific literature. It has been successfully applied for over thirty years in the optimal stochastic medium and long-term scheduling of highly complex real systems, with multi-scale storage and probabilistic modeling, such as hydrological inflows, renewable intermittency, demand, and fuel prices.
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