scholarly journals Global Time-Independent Agent-Based Simulation for Transactive Energy System Dispatch and Schedule Forecasting

2000 ◽  
Author(s):  
Shawn Chandler
Author(s):  
Mengqi Hu ◽  
Jin Wen ◽  
Fan Li ◽  
Moeed Haghnevis ◽  
Yasaman Khodadadegan ◽  
...  

Extensive research has been done on the centralized building energy system modeling and simulation. However the centralized structure is limited to study and simulate the energy interaction between different buildings at different locations. This paper reviews the building energy consumption model, energy storage system and energy generation system in the Net-zero buildings. Incorporate with the real-time price rate model, this paper develops an agent based simulation framework for distributed building energy system under uncertainty. Each sub system is developed as an agent in the simulation model, and a virtual decision agent is designed to simulate the operation strategy. The energy flow between different agents can be easily monitored from the simulation. The differences between on-peak and off-peak control are demonstrated from the simulation result.


2021 ◽  
Vol 12 (1) ◽  
pp. 18
Author(s):  
Lennart Adenaw ◽  
Markus Lienkamp

In order to electrify the transport sector, scores of charging stations are needed to incentivize people to buy electric vehicles. In urban areas with a high charging demand and little space, decision-makers are in need of planning tools that enable them to efficiently allocate financial and organizational resources to the promotion of electromobility. As with many other city planning tasks, simulations foster successful decision-making. This article presents a novel agent-based simulation framework for urban electromobility aimed at the analysis of charging station utilization and user behavior. The approach presented here employs a novel co-evolutionary learning model for adaptive charging behavior. The simulation framework is tested and verified by means of a case study conducted in the city of Munich. The case study shows that the presented approach realistically reproduces charging behavior and spatio-temporal charger utilization.


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