ESS and Bidirectional EV Charging Schedules for Lower Grid Power Costs
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Solution Overview
Problem
Conventional energy storage systems (ESS) fail to optimize operations to minimize grid electric power purchase costs while considering PV power generation, load power requirements, and EV charger demands, leading to suboptimal energy management.
Innovation Solution
An energy management device that interworks with an electric power grid, power generation device, and bidirectional EV charger, using a processor to collect data and establish schedules for ESS and EV battery operations, minimizing grid power costs through optimized charging and discharging based on defined constraints and objective functions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional ESS operation methods are used to maximize PV power generation or battery performance, then battery performance is improved, but power purchase costs are not minimized
Solution Approach 1:
The invention changes the operational parameters of the ESS system by introducing an objective function that prioritizes power purchase cost minimization over battery performance maximization. The control device adjusts charging/discharging schedules, power allocation ratios, and operational timing based on real-time parameters including electricity prices, PV generation forecasts, and load demands, thereby resolving the contradiction between battery performance and cost efficiency
Solution Approach 2:
The invention implements dynamic operation scheduling where the ESS control device continuously adjusts operational strategies based on changing conditions such as real-time electricity prices, forecasted PV generation, and varying load demands. This dynamic approach allows the system to optimize power purchase costs while maintaining acceptable battery performance through adaptive rather than static operational parameters
2Productivity
If ESS operation focuses on maximizing PV power utilization, then PV power generation is improved, but overall energy cost efficiency deteriorates
Solution Approach 1:
The invention changes the optimization parameter from PV power maximization to cost efficiency minimization. The objective function incorporates electricity price signals, allowing the system to strategically choose when to charge/discharge based on price arbitrage opportunities rather than simply maximizing PV utilization, thereby improving energy cost efficiency while maintaining productive PV generation
Solution Approach 2:
The control device performs preliminary actions by forecasting PV generation and load demands in advance, then pre-planning optimal charging/discharging schedules that minimize power purchase costs. This preliminary optimization allows the system to anticipate cost-effective operational windows rather than reactively managing PV power, improving overall energy cost efficiency
3Loss of energy
If the system considers multiple factors including PV generation, load requirements, and battery state, then operational complexity increases, but cost optimization capability improves
Solution Approach 1:
The ESS control device performs multiple functions simultaneously: it forecasts PV generation, predicts load demands, calculates optimal charging/discharging schedules, manages battery state of charge, and minimizes power purchase costs all through a single integrated control system. This multi-functional approach consolidates operational complexity into one universal controller rather than requiring separate systems for each function
Solution Approach 2:
The invention introduces an intermediary objective function that mediates between multiple conflicting factors (PV generation, load requirements, battery state, electricity prices). This objective function serves as a mathematical intermediary that synthesizes all these factors into a unified optimization problem, simplifying the management complexity while achieving cost optimization
Data Source
AI summary
An energy management device that interworks with an electric power grid, a power generation device, an Energy Storage System (ESS), and a bidirectional Electric Vehicle (EV) charger includes: at least one processor; and a memory storing at least one instruction executed via the at least one processor. At least one instruction may include: an instruction for collecting basic information including information regarding a power generation state and a power consumption state, and grid electric power cost information; an instruction for establishing, by using the collected basic information, an ESS operation schedule for controlling charging and discharging operations of an ESS battery and an EV operation schedule for controlling charging and discharging operations of an EV battery; and an instruction for controlling the ESS battery and the EV battery to be charged/discharged in accordance with the ESS operation schedule and the EV operation schedule.