Integrated Energy and Vehicle Dispatch Scheduling in V2G Networks
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Solution Overview
Problem
Current systems for managing power and delivery operations in a V2G (Vehicle-to-Grid) setting face challenges in efficiently coordinating power supply and demand between electric vehicles and business establishments, leading to suboptimal energy management and delivery scheduling.
Innovation Solution
An integrated management apparatus and method that coordinates power control and vehicle dispatch plans across multiple business establishments and electric vehicles, using a communication network to adjust departure and arrival times, and power transmission/reception to meet both power demand and delivery schedules, with modes for normal, special, and emergency conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If power control and vehicle dispatch plans are coordinated across multiple business establishments and electric vehicles, then energy management efficiency and delivery operation optimization are improved, but system complexity and coordination difficulty increase
Solution Approach 1:
The system is divided into multiple independent control units, each managing specific business establishments or vehicle groups. Each control unit operates autonomously to handle local power control and vehicle dispatch, reducing the complexity of centralized coordination while maintaining overall system efficiency through standardized communication protocols.
Solution Approach 2:
A communication network acts as an intermediary layer between power control systems and vehicle dispatch systems. This mediator enables information exchange and coordination without requiring direct complex interactions between all system components, simplifying the overall system architecture while achieving integrated management.
2Reliability
If departure and arrival times are adjusted to meet power demand and delivery schedules, then energy and delivery service reliability are improved, but scheduling flexibility and operational complexity increase
Solution Approach 1:
The system implements dynamic scheduling that automatically adjusts departure and arrival times based on real-time power demand and delivery requirements. This dynamic adaptation allows the system to maintain high service reliability while reducing manual scheduling complexity, as the adjustment logic is embedded in automated control algorithms rather than requiring manual intervention.
Solution Approach 2:
The system incorporates feedback mechanisms that monitor power demand, vehicle status, and delivery performance in real-time. This feedback enables automatic adjustments to departure and arrival times, improving service reliability through data-driven decisions while simplifying operations by eliminating the need for manual scheduling revisions.
3Use of energy by moving object
If power transmission and reception are coordinated with vehicle movement, then energy utilization efficiency is improved, but control complexity and communication requirements increase
Solution Approach 1:
The system performs preliminary coordination of power transmission and reception schedules with vehicle movement plans. By pre-coordinating these operations based on predicted vehicle arrivals and power demand forecasts, the system maximizes energy utilization efficiency while reducing real-time control complexity, as major decisions are made in advance rather than requiring complex real-time adjustments.
Data Source
AI summary
An integrated management apparatus includes: an acquisition unit which acquires (I) a first demand including a demand amount, and a demand time related to an energy demand, and (II) a second demand including a demand amount, a demand time, and a demand position related to a demand of a moving body; a processing unit which performs at least one of processing for deciding a position and a time at which the moving body moves, or processing for determining whether both the first and second demands can be met, based on the first and second demands; and a mode determination unit which switches between a plurality of modes including first and second modes in which the first demand is met to an extent possible while the second demand is met and the second demand is met to an extent possible while the first demand is met, respectively.