Open Source, Agent-based Energy Market Simulation with Python']Python

被引:0
|
作者
Lincoln, Richard W. [1 ]
Galloway, Stuart [1 ]
Burt, Graeme [1 ]
机构
[1] Univ Strathclyde, Dept Elect & Elect Engn, Glasgow G1 1XW, Lanark, Scotland
关键词
Steady-state simulation; Energy markets; Agent-based simulation; Open source software; Reinforcement learning; AC Optimal Power Flow;
D O I
暂无
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
Increasingly, the electric energy transmitted and distributed by national power systems is traded competitively in free markets. Long-term decisions must be made by authorities as to the structure of energy markets and the regulations that govern interactions between participants. It is not practical to experiment with real energy markets and in order to establish the potential effects of making these decisions there are few options but to simulate the markets computationally. This paper proposes that the complexity of power systems and the associated energy markets necessitates an open approach in their modelling and simulation. It presents an open source software package for simulating electric energy markets using the Python programming language. Power systems and their associated constraints are modelled using traditional steady-state analysis techniques. While market participants are represented by reactive agents that learn through reinforcement. The software and all of its dependencies are open and freely available to the scientific community.
引用
收藏
页码:551 / 555
页数:5
相关论文
共 50 条
  • [1] CppyABM: An open-source agent-based modeling library to integrate C plus plus and Python']Python
    Nourisa, Jalil
    Zeller-Plumhoff, Berit
    Willumeit-Roemer, Regine
    [J]. SOFTWARE-PRACTICE & EXPERIENCE, 2022, 52 (06): : 1337 - 1351
  • [2] Review of Agent-Based Evacuation Models in Python']Python
    Janda, Josef
    Stekerova, Kamila
    [J]. PROGRESS IN ARTIFICIAL INTELLIGENCE, EPIA 2023, PT I, 2023, 14115 : 511 - 522
  • [3] Soil: An Agent-Based Social Simulator in Python']Python for Modelling and Simulation of Social Networks
    Sanchez, Jesus M.
    Iglesias, Carlos A.
    Fernando Sanchez-Rada, J.
    [J]. ADVANCES IN PRACTICAL APPLICATIONS OF CYBER-PHYSICAL MULTI-AGENT SYSTEMS: THE PAAMS COLLECTION, PAAMS 2017, 2017, 10349 : 234 - 245
  • [4] Parallel Python']Python for Agent-Based Modeling at a Global Scale
    Blandin, Nicole
    Colglazier, Carl
    O'Hare, John
    Brenner, Paul
    [J]. CSS 2017: THE 2017 INTERNATIONAL CONFERENCE OF THE COMPUTATIONAL SOCIAL SCIENCE SOCIETY OF THE AMERICAS, 2017,
  • [5] Experiences in Developing a Distributed Agent-based Modeling Toolkit with Python']Python
    Collier, Nicholson T.
    Ozik, Jonathan
    Tatara, Eric R.
    [J]. PROCEEDINGS OF PYHPC 2020: 2020 IEEE/ACM 9TH WORKSHOP ON PYTHON FOR HIGH-PERFORMANCE AND SCIENTIFIC COMPUTING (PYHPC), 2020, : 1 - 12
  • [6] Application of Open-Source, Python']Python-Based Tools for the Simulation of Electrochemical Systems
    Molel, Evans Leshinka
    Fuller, Thomas F.
    [J]. JOURNAL OF THE ELECTROCHEMICAL SOCIETY, 2023, 170 (10)
  • [7] Agent-Based Model of Celtic Population Growth: Net Logo and Python']Python
    Olsevicova, Kamila
    Cimler, Richard
    Machalek, Tomas
    [J]. ADVANCED METHODS FOR COMPUTATIONAL COLLECTIVE INTELLIGENCE, 2013, 457 : 135 - 143
  • [8] psst : An Open-Source Power System Simulation Toolbox in Python']Python
    Krishnamurthy, Dheepak
    [J]. 2016 NORTH AMERICAN POWER SYMPOSIUM (NAPS), 2016,
  • [9] mango: A modular python']python-based agent simulation framework
    Schrage, Rico
    Sager, Jens
    Hoerding, Jan Philipp
    Holly, Stefanie
    [J]. SOFTWAREX, 2024, 27
  • [10] Novel Open Source Python']Python Neutrosophic Package
    El-Ghareeb, Haitham A.
    [J]. NEUTROSOPHIC SETS AND SYSTEMS, 2019, 25 : 136 - 160