What's The main functions and components of EMS PCS and BMS?
The main functions of the three core systems in the energy storage station, namely EMS (Energy Management System), PCS (Energy Storage Converter), and BMS (Battery Management System).
Collaborative relationship:
BMS ensures the safety boundary of the battery itself, PCS is the rapid and precise execution unit, and EMS is the brain that makes the optimal decision. The three work closely together through a high-speed communication network (such as CAN, Ethernet), forming a complete "perception - decision - execution" closed loop.
Parametric trend:
With the development of technology, the parameter requirements are getting higher and higher. For example, PCS has a faster response and higher efficiency; BMS has more accurate estimation and more detailed management; EMS has more intelligent algorithms (introducing AI for prediction and optimization).
Scenario integration:
Single-function power stations are decreasing, and "one machine with multiple functions" has become the mainstream. For example, a grid-side energy storage station may simultaneously undertake frequency regulation, peak shaving, and backup tasks, which puts higher requirements on the strategy complexity of EMS and the multi-mode switching ability of PCS.
I. Overview of Core System Functions
System | Character Metaphor | Main Functions | Key Points |
BMS | The "guardian" and "doctor" of the battery | Monitor, protect, balance, and evaluate the battery status to ensure the safety, reliability and long lifespan of the battery. | Safety first: voltage, temperature, insulation, balance. |
PCS | The "translator" and "executor" of energy | Carry out the bidirectional conversion between direct current (battery) and alternating current (power grid/load), and control the charging and discharging power. | Efficient, stable, controllable: Conversion efficiency, power response, grid-connected/disconnected switching. |
EMS | The "brain" and "commander" of the power station | Carry out global optimization scheduling based on strategies, coordinate devices such as PCS and BMS, and achieve the economic and efficient operation of the power station. | Strategies and Optimization: Scheduling algorithms, economy, multi-objective coordination. |
II. Scene Examples
The application scenarios of energy storage mainly include: power generation side (power supply side), grid side and user side. In different scenarios, the functional emphasis and parameter requirements of the three systems are all different.
Scene 1: Grid-side Energy Storage (such as: independent energy storage stations, grid frequency regulation)
Core objective: Serve the power grid, enhance the stability, safety and regulation capabilities of the power grid.
Typical applications: one-time/secondary frequency modulation, peak load regulation, backup, black start.
System | Functions Exmples | Key parameter example |
BMS | 1. High-precision SOE estimation: Provides accurate available energy for EMS, supporting power command execution within minutes to hours. | - Accuracy of SOC/SOE estimation: < ±3% - Frequency of status refresh: ≥ 1Hz - Sampling accuracy of voltage/temperature: ±0.5%FS |
PCS | 1. Millisecond-level power response: Upon receiving the AGC command, it precisely responds to the frequency regulation requirements of the power grid within a hundred milliseconds. | - Power response time: < 200ms - Overload capacity: 150%, 10 seconds - Conversion efficiency: > 98.5% (at rated point) - V/F control mode accuracy: Voltage ±0.5%, Frequency ±0.05Hz |
EMS | 1. Receive and decompose grid dispatch instructions: Receive AGC/AVC instructions from the superior dispatch center and decompose them into control instructions for each PCS unit. | - AGC instruction response delay: < 1 second - Scheduling strategy cycle: second-level/minute-level - Supported communication protocols: IEC 60870-5-104, IEC 61850 |
Scene 2: Energy storage on the power generation side of new energy (such as: power plants with on-site energy storage for photovoltaic or wind power)
Core objective: To smooth out power output, reduce power waste, and enhance the predictability and schedulability of new energy sources.
Typical applications: smoothing fluctuations, tracking planned output, peak shaving and valley filling.
System | Functions Exmples | Key parameter example |
BMS | 1. Cycle life management: Optimize the depth of discharge (DOD) to maximize battery lifespan while ensuring smooth operation. | - Support DOD optimization strategy - Battery inconsistency warning threshold: voltage difference > 50mV, temperature difference > 3℃ |
PCS | 1. Power smoothing control: Utilizing algorithms such as low-pass filtering, it compensates for the minute-level fluctuations in the output of new energy sources in real time. | - Smooth control algorithm response time: < 500ms - Planned curve tracking error: < 2% - Support for weak network operation of SCR: < 2 |
EMS | 1. Joint Optimization Scheduling: Incorporate power predictions of photovoltaic and wind power to formulate the most optimal charging and discharging plan for energy storage. | - Power prediction data integration (short-term/ultra-short-term) - Calculation cycle for power curtailment strategy: 15 minutes - Communication interface for communication with wind turbines/inverters monitoring system |
Scene 3: User-side Energy Storage (such as industrial and commercial parks, data centers)
Core objectives: Reduce electricity costs, ensure power supply reliability, and participate in demand response.
Typical applications: Peak-valley arbitrage, demand management, backup power supply, dynamic capacity expansion.
| System | Functions Exmples | Key parameter example |
BMS | 1. Economic life management: Aim for the lowest cost per kilowatt-hour throughout the entire life cycle, and optimize the charging and discharging strategies. | - Estimated accuracy of SOH: < ±5% - Supports independent management of clusters |
PCS | 1. Off-grid operation (UPS function): In the event of a power outage in the main grid, it switches to off-grid mode within milliseconds to supply power to critical loads. | - Time for disconnection and reconnection: < 10ms - Parallel circulating current suppression: < 1% of rated current - Anti-backflow control accuracy: < 1% of rated power |
EMS | 1. Core of economic strategy: Based on the time-of-use electricity pricing model, automatically execute the "low charge-high discharge" peak-valley arbitrage strategy. | - Electricity price model configuration (peak, off-peak, and off-peak periods and prices) - Demand control prediction algorithm and execution cycle - Support for demand response protocols such as OpenADR |
The core component of BMS is "precise sensing + intelligent algorithms", which manages battery data and safety in a hierarchical manner.
The core component of PCS is "power semiconductor + high-speed controller", which enables efficient and controllable conversion of electrical energy.
The core composition of EMS is "high-performance computing platform + intelligent decision-making software", which performs information fusion and optimization scheduling.