Achieving Emission-Reduction Goals: Multi-Period Power-System Expansion under Short-Term Operational Uncertainty
نویسندگان
چکیده
Stochastic adaptive robust optimization is capable of handling short-term uncertainties in demand and variable renewable-energy sources that affect investment generation transmission capacity. We build on this setting by considering a multi-year horizon for finding the optimal plan capacity expansion while reducing greenhouse gas emissions. In addition, we incorporate multiple hours power-system operations to capture hydropower flexibility requirements utilizing such as wind solar power. To improve computational performance existing exact methods problem, employ Benders decomposition solve mixed-integer quadratic programming problem avoid computationally expensive big-M linearizations. The results realistic case study Nordic Baltic region indicate which investments transmission, power, flexible are required Through out-of-sample experiments, show stochastic model leads lower expected costs than under increasingly stringent environmental considerations.
منابع مشابه
A multi-period distribution network design model under demand uncertainty
Supply chain management is taken into account as an inseparable component in satisfying customers' requirements. This paper deals with the distribution network design (DND) problem which is a critical issue in achieving supply chain accomplishments. A capable DND can guarantee the success of the entire network performance. However, there are many factors that can cause fluctuations in input dat...
متن کاملMulti-period supplier selection under price uncertainty
We consider a problem faced by a procurement manager who needs to purchase a large volume of multiple items over multiple periods from multiple suppliers that provide base prices and discounts. Discounts are contingent on meeting various conditions on total volume or spend, and some are tied to future realizations of random events that can be mutually verified. We formulate a scenario-based mul...
متن کاملMulti-Objective Optimization for Multi-Product Multi-Period Four Echelon Supply Chain Problems Under Uncertainty
The multi-objective optimization for a multi-product multi-period four-echelon supply chain network consisting of manufacturing plants, distribution centers (DCs) and retailers each with uncertain services and uncertain customer nodes are aimed in this paper. The two objectives are minimization of the total supply chain cost and maximization of the average number of products dispatched to custo...
متن کاملShort-Term Scheduling Under Uncertainty: Sensitivity Analysis
Synonyms Indices i = tasks j = units n = event points s = states k = scenarios Parameters price(s) = price of state s ρ(s, i), ρ(s, i) = proportion of state s produced, consumed from task i, respectively r(s) = market requirement for state s at the end of the time horizon Vmin(i,j) = minimum capacity of unit j when processing task i Vmax(i,j) = maximum capacity of unit j when processing task i ...
متن کاملDistributed Generation Expansion Planning Considering Load Growth Uncertainty: A Novel Multi-Period Stochastic Model
Abstract – Distributed generation (DG) technology is known as an efficient solution for applying in distribution system planning (DSP) problems. Load growth uncertainty associated with distribution network is a significant source of uncertainty which highly affects optimal management of DGs. In order to handle this problem, a novel model is proposed in this paper based on DG solution, consideri...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: IEEE Transactions on Power Systems
سال: 2023
ISSN: ['0885-8950', '1558-0679']
DOI: https://doi.org/10.1109/tpwrs.2023.3244668