EV Depot Charging Schedules Under Distribution Network Constraints
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Solution Overview
Problem
Energy management systems in electric vehicle (EV) depots face challenges in preventing voltage and current violations in distribution networks, especially with the integration of renewable energy resources, which can lead to penalties and network instability.
Innovation Solution
A method using hardware processors to simulate power schedules in a distribution network model, generate constraints to prevent violations, and adjust charging schedules based on load priorities to ensure compliance with grid codes, thereby scheduling power generation and load charging to avoid violations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of energy
If maximum power generation from renewable energy resources is utilized to reduce electrical costs, then electrical cost reduction is improved, but voltage violations (over-voltage) in the distribution network increase
Solution Approach 1:
The system performs preliminary simulation of power schedules before actual execution to predict and prevent voltage violations. By simulating the distribution network model with the proposed power schedule and identifying potential violations in advance, the system adjusts the schedule proactively to avoid over-voltage conditions while still maximizing renewable energy utilization.
Solution Approach 2:
The system implements a feedback mechanism where simulation results of power schedules are fed back into the scheduling process. When voltage violations are detected in the simulation, the system generates constraints and re-executes the economic dispatch application to produce adjusted power schedules that eliminate violations while maintaining cost-effectiveness.
2Loss of energy
If distributed energy resources are integrated into the EV depot to reduce costs, then electrical cost reduction is improved, but distribution network stability deteriorates due to increased violation probability
Solution Approach 1:
The system introduces an intermediary simulation model that acts as a mediator between the economic dispatch application and the actual distribution network. This simulation model predicts the impact of power schedules on network stability, allowing the system to optimize renewable energy utilization while preventing stability issues before they occur.
Solution Approach 2:
The system uses feedback from simulation results to continuously refine power schedules. By monitoring predicted voltage and current conditions in the simulation and feeding this information back into the scheduling process, the system maintains distribution network stability while maximizing the use of distributed energy resources.
3Reliability
If power schedule simulation and constraint generation are performed iteratively to prevent violations, then violation prevention is improved, but computational complexity and processing time increase
Solution Approach 1:
The system performs preliminary simulation and constraint generation in advance of actual power schedule execution. By identifying potential violations and generating appropriate constraints before implementation, the system ensures reliable violation prevention while organizing the computational complexity in a structured, manageable sequence.
Solution Approach 2:
The system dynamically adjusts the level of simulation detail and constraint generation based on the specific conditions detected. The iterative process adapts to the complexity of each scenario, performing more detailed analysis only when necessary to prevent violations, thereby balancing reliability with computational efficiency.
Data Source
AI summary
Network constraint energy management system for electric vehicle (EV) depot charging and scheduling. In an embodiment, a power schedule is received from an economic dispatch application for a charging depot comprising EV charging station(s) and distributed energy resource(s). The power schedule may be simulated on a distribution network model of the charging depot, according to load flow analysis, to determine whether any grid-code violations occur. In response to the detection of violation(s), a constraint may be generated for each violating node, and the economic dispatch application may be re-executed with the constraint(s) to produce a new power schedule, until no violations are detected. When not all load demand can be satisfied by the power schedule, a charging schedule may be adjusted to ensure that critical energy requirements are satisfied. The final power and charging schedules may be used to schedule and control power generation and charging in the charging depot.