Eclipse Rich Client Platform: Designing, Coding, and Packaging Java(TM) Applications
Eclipse Rich Client Platform: Designing, Coding, and Packaging Java(TM) Applications
MASON: A Multiagent Simulation Environment
Simulation
Tutorial on agent-based modeling and simulation
WSC '05 Proceedings of the 37th conference on Winter simulation
Tutorial on agent-based modeling and simulation part 2: how to model with agents
Proceedings of the 38th conference on Winter simulation
Computers & Mathematics with Applications
Particle Swarm Optimization: Basic Concepts, Variants and Applications in Power Systems
IEEE Transactions on Evolutionary Computation
Hi-index | 0.00 |
With an increasing number of small-scale renewable generator installations, distribution network planners are faced with new technical challenges (intermittent load flows, network imbalances...). Then again, these decentralized generators (DGs) present opportunities regarding savings on network infrastructure if installed at strategic locations. How can we consider both of these aspects when building decision tools for planning future distribution networks? This paper presents a simulation framework which combines two modeling techniques: agent-based modeling (ABM) and particle swarm optimization (PSO). ABM is used to represent the different system units of the network accurately and dynamically, simulating over short time-periods. PSO is then used to find the most economical configuration of DGs over longer periods of time. The infrastructure of the framework is introduced, presenting the two modeling techniques and their integration. A case study of Townsville, Australia, is then used to illustrate the platform implementation and the outputs of a simulation.