Apartment Power Management With EV Charging Scheduling and CVR
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Solution Overview
Problem
In apartment complexes, managing the charging demand of electric vehicles is challenging due to the difficulty in coordinating charging schedules across multiple residents, leading to potential system instability and the need for costly transformer upgrades to meet peak demands, while existing conservation voltage reduction methods are typically unilateral and do not account for distributed energy sources like solar power or V2G.
Innovation Solution
A power management device that includes a charging scheduler, pattern analyzer, prediction voltage calculator, and controller to adjust electric vehicle charging times, spread demand patterns, and implement conservation voltage reduction, thereby stabilizing the power system and maintaining existing transformer capacity by optimizing voltage distribution and reducing peak loads.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If electric vehicle charging demand is concentrated at the same time to meet user needs, then user convenience is improved, but system stability deteriorates and transformer capacity is exceeded
Solution Approach 1:
The charging management device performs preliminary actions by analyzing predicted charging demands and calculating optimal charging schedules in advance. The controller determines charging schedules before peak demand periods occur, spreading charging loads across different time periods to prevent system overload while ensuring users can charge their vehicles conveniently.
2Productivity
If additional electric vehicle chargers are installed to meet increased demand, then charging capacity is improved, but infrastructure cost increases requiring transformer replacement
Solution Approach 1:
The system changes operational parameters by implementing intelligent charging schedules that control when and how fast vehicles charge. The controller adjusts charging rates and timing based on predicted demand patterns and available transformer capacity, enabling the existing infrastructure to handle increased charging demand without requiring costly hardware upgrades.
Solution Approach 2:
The charging management device introduces dynamic scheduling that adapts to varying demand patterns. The controller continuously analyzes predicted charging demands and adjusts charging schedules in real-time, allowing the system to flexibly accommodate increased charging capacity needs while maintaining transformer load within safe operating limits.
3Power
If conservation voltage reduction is performed unilaterally by power supply side, then peak load reduction is achieved, but adaptability to distributed energy sources deteriorates
Solution Approach 1:
The system inverts the traditional unilateral CVR approach by implementing a distributed control mechanism. Instead of the power supply side unilaterally reducing voltage, the charging management device autonomously schedules charging operations to achieve voltage reduction effects. This inverted approach naturally adapts to distributed energy sources like solar power and V2G by incorporating them into the scheduling algorithm.
Solution Approach 2:
The charging management device performs multiple functions: it schedules charging to reduce peak loads, manages distributed energy sources, and optimizes voltage levels. This multi-functional approach makes the system universally adaptable to various energy sources and grid conditions, replacing the need for unilateral CVR with a more versatile intelligent scheduling system.
Data Source
AI summary
A power management device includes a pattern analyzer configured to analyze a demand pattern that is a power pattern for consumption by an apartment complex, a charging scheduler configured to receive a first demand pattern from the pattern analyzer, and to calculate a second demand pattern obtained by adjusting charging time of an electric vehicle charger, a prediction voltage calculator configured to receive power data from the pattern analyzer, and to calculate a prediction voltage of the apartment complex, and a controller configured to calculate a recommendation voltage for conservation voltage reduction (CVR) by using the prediction voltage, wherein the controller may be configured to perform control such that the recommendation voltage is an operation power of the apartment complex, and the operation power may satisfy the second demand pattern.


