Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Maximum Power Flow and Line Loadability01:23

Maximum Power Flow and Line Loadability

574
The maximum power flow for lossy transmission lines is derived using ABCD parameters in phasor form. These parameters create a matrix relationship between the sending-end and receiving-end voltages and currents, allowing the determination of the receiving-end current. This relationship facilitates calculating the complex power delivered to the receiving end, from which real and reactive power components are derived.
574
Multimachine Stability01:25

Multimachine Stability

532
Multimachine stability analysis is crucial for understanding the dynamics and stability of power systems with multiple synchronous machines. The objective is to solve the swing equations for a network of M machines connected to an N-bus power system.
In analyzing the system, the nodal equations represent the relationship between bus voltages, machine voltages, and machine currents. The nodal equation is given by:
532
Distributed Loads: Problem Solving01:21

Distributed Loads: Problem Solving

1.1K
Beams are structural elements commonly employed in engineering applications requiring different load-carrying capacities. The first step in analyzing a beam under a distributed load is to simplify the problem by dividing the load into smaller regions, which allows one to consider each region separately and calculate the magnitude of the equivalent resultant load acting on each portion of the beam. The magnitude of the equivalent resultant load for each region can be determined by calculating...
1.1K
Fast Decoupled and DC Powerflow01:24

Fast Decoupled and DC Powerflow

708
The fast decoupled power flow method addresses contingencies in power system operations, such as generator outages or transmission line failures. This method provides quick power flow solutions, essential for real-time system adjustments. Fast decoupled power flow algorithms simplify the Jacobian matrix by neglecting certain elements, leading to two sets of decoupled equations:
708
Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving01:29

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

261
Mechanistic models play a crucial role in algorithms for numerical problem-solving, particularly in nonlinear mixed effects modeling (NMEM). These models aim to minimize specific objective functions by evaluating various parameter estimates, leading to the development of systematic algorithms. In some cases, linearization techniques approximate the model using linear equations.
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
261
Maxwell-Boltzmann Distribution: Problem Solving01:20

Maxwell-Boltzmann Distribution: Problem Solving

2.8K
Individual molecules in a gas move in random directions, but a gas containing numerous molecules has a predictable distribution of molecular speeds, which is known as the Maxwell-Boltzmann distribution, f(v).
This distribution function f(v) is defined by saying that the expected number N (v1,v2) of particles with speeds between v1 and v2 is given by
2.8K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Genetic variants of p21 and p27 and hepatocellular cancer risk in a Chinese Han population: a case-control study.

International journal of cancer·2012
Same author

Inhibition of TGF-β/Smad signaling by BAMBI blocks differentiation of human mesenchymal stem cells to carcinoma-associated fibroblasts and abolishes their protumor effects.

Stem cells (Dayton, Ohio)·2012
Same author

MAIGO2 is involved in abscisic acid-mediated response to abiotic stresses and Golgi-to-ER retrograde transport.

Physiologia plantarum·2012
Same author

The internal dynamics of mini c TAR DNA probed by electron paramagnetic resonance of nitroxide spin-labels at the lower stem, the loop, and the bulge.

Biochemistry·2012
Same author

Electrochemical depassivation of zero-valent iron for trichloroethene reduction.

Journal of hazardous materials·2012
Same author

Derivation of quantum work equalities using a quantum Feynman-Kac formula.

Physical review. E, Statistical, nonlinear, and soft matter physics·2012

Related Experiment Video

Updated: Jan 8, 2026

Experimental Investigation of the Hierarchical Control in DC Microgrids Using a Real-time Simulator
06:04

Experimental Investigation of the Hierarchical Control in DC Microgrids Using a Real-time Simulator

Published on: February 14, 2025

983

Multiagent game-theoretic robust optimization for power system planning under source-load uncertainty.

Jinliang Mi1, Min Xu2, Juan An1

  • 1Economic and Technological Research Institute of State Grid Qinghai Electric Power Company, Xining, China.

Scientific Reports
|December 19, 2025
PubMed
Summary
This summary is machine-generated.

This study introduces a new game theory model for power system planning, considering stakeholder goals and uncertainties. It shows robust planning accelerates coal phase-out and boosts storage investment, enhancing grid stability.

Keywords:
Electricity system planningMulti-agent game theoryRenewable integrationRobust optimizationSource–load uncertaintyStakeholder interactions

More Related Videos

Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm
11:53

Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm

Published on: December 9, 2012

13.4K

Related Experiment Videos

Last Updated: Jan 8, 2026

Experimental Investigation of the Hierarchical Control in DC Microgrids Using a Real-time Simulator
06:04

Experimental Investigation of the Hierarchical Control in DC Microgrids Using a Real-time Simulator

Published on: February 14, 2025

983
Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm
11:53

Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm

Published on: December 9, 2012

13.4K

Area of Science:

  • Power Systems Engineering
  • Game Theory
  • Optimization

Background:

  • Increasing renewable energy and demand volatility necessitate uncertainty-aware power system planning.
  • Traditional planning overlooks diverse stakeholder objectives and interactions, impacting feasibility and cost-effectiveness.
  • Centralized planning models fail to capture the complex dynamics of multiple independent actors in the electricity sector.

Purpose of the Study:

  • To develop a novel multi-agent game-theoretic framework for electricity system planning under uncertainty.
  • To integrate stakeholder strategies and robust optimization into a hierarchical game model.
  • To analyze the impact of regulatory signals and market responses on planning outcomes.

Main Methods:

  • A multi-agent game-theoretic framework conceptualizing power planning as a hierarchical game.
  • Integration of robust optimization to address uncertainties in renewable generation and load demand.
  • Modeling strategic interactions of regulators, grid operators, renewable producers, and large load users.

Main Results:

  • Robust equilibrium accelerates coal retirements (15-20%) and increases storage investments (30-40%).
  • Load-serving entities reduce price volatility by reshaping demand, cutting tail-event prices by 20-25%.
  • Carbon penalties lead to significant emission reductions (45-55%) with limited shortfall risks (<2 GW).

Conclusions:

  • Electricity planning should be redefined as a multi-agent game, not a centralized optimization problem.
  • Robust optimization embedded within strategic equilibrium mitigates physical shortfalls and economic volatility.
  • The framework highlights the crucial interplay between regulatory signals and market-based stakeholder responses.