代写一个电动车充电调度系统，实现一个prototype的demo即可。
Goal of the assignment
The goal of this assignment is to implement and demonstrate a simple
intelligent scheduling system for the coordinated charging of a number of
plug-in electric cars in a precinct/neighbourhood.
Description
Design and implement a simple intelligent system for coordinated scheduling of
a number of plug-in electric cars in a precinct/neighbourhood, in such a way
that all the cars are efficiently and fairly charged according to the
different time preferences of the individual owners, the car charging
constraints and the maximum electricity load constraints.
An electric car charge scheduling system should involve agents with the
following roles:
- Master scheduling agent
- Collects requirements and preferences from other agents (i.e. from car agents)
- Produces a coordinated schedule for all the cars (can use e.g. KBR, GA, ACO or other intelligent search/optimisation/reaoning techniques from the unit)
- Sends the individual schedules to car agents
- Car agents (at least 6 agents)
- Send the requirements and preferences to the master scheduling agent
- Receives the individual schedule
- Car scheduling agents (at least 3 – instead of a master agent) (optional)
- Exchange the requirements and preferences with other agents
- Collaboratively produce a schedule for all the cars (e.g. iteratively exchange individual schedules and improve/alter them until all the individual schedules are valid)
The master scheduling agent assists the households in a neighbourhood with
producing a schedule for the coordinated charging of all plug-in electric cars
in such a way that all the cars are efficiently (e.g. shortest overall time,
etc) and fairly (e.g. similar waiting time for individual cars, user
preferences satisfied to a similar level, etc) charged according to the
different time preferences of individual owners (e.g. earliest time to start
charging, latest time for a car to be fully charged, etc), car charging
constraints (e.g. minimum time and min/max energy for a charge in multi-step
charging) and the maximum electricity load constraints (e.g. maximum total
load at any time). The car agents send their requirements and preferences to
the master scheduling agent and are notified about their individualschedules
produced by the master scheduling agent. Optionally, each charging station can
have a car scheduling agent that interact with each other to produce schedules
for individual cars (that satisfy all the local and global
preference/constraints). The agents can exchange their preferences and
individually schedule charging their cars. Alternatively, they can iteratively
exchange individual schedules and improve/alter them until all individual
schedules are valid.
Assumptions and options (can’s and or’s)
- The master scheduling agent (or car scheduling agents) can use any search/optimisation technique from the unit (e.g. KBR, genetic algorithm, ant colony, etc) or combination of them
- The car scheduling agents can also use negotiation or other distributed mechanism (e.g. KBR, auction, CNP etc)
- Provide GUI for the user input, parameter settings and visualisation (and a config file for the defaults)-
- Use and compare different approaches/techniques (e.g. KBR vs ACO vs GA) (optional)
- For agent communication any interaction protocols can used such as FIPA predefined (e.g. CNP, iterated CNP), nested or newly specified; any standard content language is ok; display the massage exchanged between the agents (e.g. sniffer agent)
- Try to demonstrate the system with a well designed and realistic example
- Be creative but keep it simple!!!
