Simulation modeling for energy systems analysis: a critical review

Q2 Energy Energy Informatics Pub Date : 2024-08-27 DOI:10.1186/s42162-024-00374-8

M. M. Mundu, S. N. Nnamchi, J. I. Sempewo, Daniel Ejim Uti

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Abstract

Introduction

Energy system simulation modeling plays an important role in understanding, analyzing, optimizing, and guiding the change to sustainable energy systems.

Objectives

This review aims to examine energy system simulation modeling, emphasizing its role in analyzing and optimizing energy systems for sustainable development.

Methods

The paper explores four key simulation methodologies; Agent-Based Modeling (ABM), System Dynamics (SD), Discrete-Event Simulation (DES), and Integrated Energy Models (IEMs). Practical applications of these methodologies are illustrated through specific case studies.

Results

The analysis covers key components of energy systems, including generation, transmission, distribution, consumption, storage, and renewable integration. ABM models consumer behavior in renewable energy adoption, SD assesses long-term policy impacts, DES optimizes energy scheduling, and IEMs provide comprehensive sector integration. Case studies demonstrate the practical relevance and effectiveness of these models in addressing challenges such as data quality, model complexity, and validation processes.

Conclusions

Simulation modeling is essential for addressing energy challenges, driving innovation, and informing policy. The review identifies critical areas for improvement, including enhancing data quality, refining modeling techniques, and strengthening validation processes. Future directions emphasize the continued importance of simulation modeling in achieving sustainable energy systems.

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用于能源系统分析的仿真建模：重要综述

能源系统仿真建模在理解、分析、优化和指导可持续能源系统变革方面发挥着重要作用。本综述旨在研究能源系统仿真建模，强调其在分析和优化能源系统以促进可持续发展方面的作用。本文探讨了四种关键的仿真方法：基于代理的建模（ABM）、系统动力学（SD）、离散事件仿真（DES）和综合能源模型（IEM）。通过具体案例研究说明了这些方法的实际应用。分析涵盖能源系统的关键组成部分，包括发电、输电、配电、消费、存储和可再生能源整合。ABM 模拟消费者采用可再生能源的行为，SD 评估长期政策影响，DES 优化能源调度，IEM 提供全面的行业整合。案例研究证明了这些模型在应对数据质量、模型复杂性和验证过程等挑战方面的实用性和有效性。仿真建模对于应对能源挑战、推动创新和提供政策信息至关重要。回顾指出了需要改进的关键领域，包括提高数据质量、完善建模技术和加强验证过程。未来发展方向强调了仿真建模在实现可持续能源系统方面的持续重要性。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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