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Main Functions and Components of EMS, PCS, and BMS

January 23 , 2026

The main functions of the three core systems in an energy storage power station: EMS (Energy Management System), PCS (Energy Storage Converter), and BMS (Battery Management System).

Coordination Relationship

BMS defines and safeguards the battery’s safety boundaries.
PCS acts as the fast and precise execution unit.
EMS serves as the “brain,” making optimal system-level decisions.

These three systems are tightly integrated through high-speed communication networks (such as CAN and Ethernet), forming a complete closed-loop of “perception – decision – execution.”

Parametric Evolution Trend
With technological advancement, system performance requirements continue to increase:

PCS: faster response, higher efficiency
BMS: more accurate estimation, finer-grained management
EMS: more intelligent algorithms, increasingly incorporating AI-based prediction and optimization

Scenario Convergence
Single-function energy storage stations are gradually being replaced by multi-functional systems.

For example, a grid-side energy storage plant may simultaneously provide frequency regulation, peak shaving, and backup services, which places higher demands on EMS strategy complexity and PCS multi-mode switching capability.

1. Overview of Core System Functions

System	Role Metaphor	Core Functions	Key Focus Areas
BMS(Battery Management System)	The battery’s “bodyguard and doctor”	Monitoring, protection, balancing, and state evaluation to ensure safe, reliable, and long battery life	Safety first:• Voltage monitoring• Temperature monitoring• Insulation detection• Cell balancing
PCS(Power Conversion System)	The energy “translator and executor”	Bidirectional conversion between DC (battery) and AC (grid/load), precise control of charge/discharge power	Efficient, stable, controllable:• Conversion efficiency• Power response speed• Grid-connected / off-grid switching
EMS(Energy Management System)	The station’s “brain and commander”	Global optimization and dispatch based on operating strategies, coordinating PCS and BMS for economic and efficient operation	Strategy & optimization:• Dispatch algorithms• Economic analysis• Multi-objective coordination

2. Application Scenarios
Energy storage applications are typically divided into generation-side, grid-side, and user-side scenarios. Each scenario imposes different functional priorities and parameter requirements on EMS, PCS, and BMS.

Scenario 1: Grid-Side Energy Storage
(e.g., standalone ESS, grid frequency regulation)

Core Objective: Support grid operation and enhance stability, security, and regulation capability.
Typical Applications: Primary/secondary frequency regulation, peak shaving, reserve, black start.

System	Function Examples	Key Parameter Examples
BMS(Battery Management System)	1. High-accuracy SOE estimation: Provides EMS with accurate available energy data to support power commands from minute-level to hour-level execution. 2. Fast status reporting: Real-time reporting of battery charge/discharge power limits to support rapid PCS power response. 3. Redundant safety protection: Multi-layer protection mechanisms to prevent thermal runaway during frequent charge/discharge switching.	• SOC / SOE estimation accuracy: < ±3%• Status update rate: ≥ 1 Hz• Voltage / temperature sampling accuracy: ±0.5% FS
PCS(Power Conversion System)	1. Millisecond-level power response: Receives AGC commands and responds precisely to grid frequency regulation demands within hundreds of milliseconds. 2. High overload capability: Supports short-term power surges to meet rapid ramping requirements during frequency regulation. 3. Seamless grid / off-grid switching: Supports black start and serves as a start-up power source during grid fault recovery.	• Power response time: < 200 ms• Overload capability: 150% for 10 s• Conversion efficiency: > 98.5% (rated condition)• V/F control accuracy: Voltage ±0.5%, Frequency ±0.05 Hz
EMS(Energy Management System)	1. Dispatch command reception and decomposition: Receives AGC / AVC commands from the upper-level dispatch center and decomposes them into control commands for each PCS unit. 2. Frequency regulation strategy optimization: Dynamically adjusts regulation coefficients based on SOC to avoid overcharge and overdischarge, extending battery life. 3. Multi-objective coordinated control: Priority management and resource allocation among frequency regulation, peak shaving, and reserve services.	• AGC command response delay: < 1 s• Dispatch strategy cycle: second-level / minute-level• Supported communication protocols: IEC 60870-5-104, IEC 61850

Scenario 2: Renewable Generation-Side Energy Storage
(e.g., PV/Wind + ESS)

Core Objective: Smooth output, reduce curtailment, and improve predictability and dispatchability.
Typical Applications: Output smoothing, planned power tracking, peak shaving and valley filling.

System	Function Examples	Key Parameter Examples
BMS(Battery Management System)	1. Cycle life management: Optimizes depth of discharge (DOD) to maximize battery cycle life while meeting power smoothing requirements. 2. Inconsistency early warning: Provides early warnings for battery clusters operating long-term at low or high SOC levels, enabling proactive intervention and maintenance decisions.	• Support for DOD optimization strategies• Battery inconsistency warning thresholds:Voltage difference > 50 mVTemperature difference > 3 °C
PCS(Power Conversion System)	1. Power smoothing control: Uses low-pass filtering and related algorithms to compensate for minute-level fluctuations in renewable generation output in real time. 2. Planned power curve tracking: Controls ESS charging and discharging according to the generation plan, ensuring total plant output follows the planned curve. 3. Weak-grid adaptability: Maintains stable operation under weak grid conditions, such as remote renewable plants.	• Smoothing control algorithm response time: < 500 ms• Planned curve tracking error: < 2%• Supported short-circuit ratio (SCR) for weak-grid operation: < 2
EMS(Energy Management System)	1. Joint optimized dispatch: Integrates PV and wind power forecasting to generate optimal ESS charge and discharge schedules. 2. Curtailment mitigation strategy: Charges in advance when curtailment risks are forecasted and discharges during load peaks. 3. Plant-level AGC / AVC: Acts as a unified control unit to receive grid dispatch commands and coordinate renewable generators and energy storage systems internally.	• Support for power forecast data input:Short-term / ultra-short-term• Curtailment mitigation strategy calculation cycle: 15 minutes• Communication interfaces with wind turbine / inverter monitoring systems

Scenario 3: User-Side Energy Storage
(e.g., industrial parks, data centers)

Core Objective: Reduce electricity costs, ensure power reliability, and participate in demand response.
Typical Applications: Peak-valley arbitrage, demand management, backup power, dynamic capacity expansion.

System	Function Examples	Key Parameter Examples
BMS(Battery Management System)	1. Economic lifetime management: Optimizes charge and discharge strategies with the objective of minimizing lifecycle levelized cost of energy (LCOE), balancing battery lifetime and economic returns. 2. Fine-grained management: Independent SOC and health status management for each battery cluster to maximize available system capacity.	• SOH estimation accuracy: < ±5%• Support for independent cluster-level management
PCS(Power Conversion System)	1. Off-grid operation (UPS function): Switches to off-grid mode within milliseconds during a main grid outage, ensuring uninterrupted power supply for critical loads. 2. Multi-unit parallel operation and load sharing: Multiple PCS units operate in parallel and automatically distribute power based on load variations, suitable for large industrial parks and plants. 3. Anti-backflow control: Precisely controls output power during grid-connected operation to prevent reverse power flow to the grid, in compliance with local grid regulations.	• Grid / off-grid switching time: < 10 ms• Circulating current suppression: < 1% of rated current• Anti-backflow control accuracy: < 1% of rated power
EMS(Energy Management System)	1. Economic strategy core: Automatically executes peak–valley arbitrage strategies based on time-of-use (TOU) electricity pricing models. 2. Demand control: Continuously monitors customer demand and discharges energy in advance of peak demand to reduce demand charges. 3. Demand response: Adjusts operating modes based on demand response signals from the grid or aggregators to generate additional revenue. 4. Multi-energy coordination: Coordinates PV, energy storage, diesel generators, and other energy sources for integrated energy optimization.	• Configurable electricity price models:Peak / Flat / Valley

3. Internal Architecture of EMS, PCS, and BMS

BMS Architecture
Battery Management System (BMS) is the "smart manager" of the battery pack, and its core tasks are to ensure safety, extend lifespan, and inform users of the battery status.

For battery safety and lifetime management, ACEY Battery Management System (BMS) provides high-precision SOC/SOH estimation, cell-level monitoring, and multi-layer protection, ensuring safe and reliable operation across different application scenarios.

1. Hardware (Slave → Master → Central)

Layer	Unit	Core Hardware	Core Functions
Lower	Slave Unit	High-precision AFE, passive/active balancing circuits, isolated communication	Cell voltage/temperature acquisition, cell balancing
Middle	Master Unit	High-performance MCU, CAN/Ethernet, IMD, current sensors	SOC/SOH/SOP calculation, relay control, insulation monitoring
Top	Central Controller	Industrial PC / high-end processor, communication gateways	System-level state calculation, EMS/PCS communication, protection logic

2. Software Functional Module Composition

Data Acquisition Module: Real-time, synchronous acquisition of voltage, temperature, and current.
State Estimation Module: Core algorithm module, using ampere-hour integration, Kalman filtering, neural networks, and other algorithms to estimate SOC, SOH, and SOP.
Safety Protection and Alarm Module: Sets thresholds (overvoltage, undervoltage, overtemperature, overcurrent, insulation fault) and triggers graded protection (alarm, power reduction, disconnection).
Balance Management Module: Controls the balance circuit to reduce inconsistencies between battery cells.
Thermal Management Module: Controls the cooling/heating system (fan, liquid pump) based on temperature data.
Data Storage and Communication Module: Stores historical data and communicates with external systems (PCS, EMS) via protocols such as CAN and Ethernet.

PCS (Energy Storage Converter) Composition
The PCS is the "executor" that completes energy form conversion; its core is power conversion.

1. Hardware Physical Composition

Power Conversion Unit:

Core: A full-bridge or half-bridge circuit composed of IGBT (Insulated Gate Bipolar Transistor) or SiC (Silicon Carbide) modules. This is the "heart" of the AC/DC conversion system.
Support: DC support capacitors, filter inductors, transformers, etc.

Control Unit:

Core: DSP (Digital Signal Processor) or FPGA (Field Programmable Gate Array). Responsible for generating PWM (Pulse Width Modulation) drive signals to achieve fast and precise power control.

Sampling and Drive Unit:

Voltage/Current Sensors: Real-time acquisition of electrical parameters from both AC and DC sides.
Driver Board: Amplifies the weak electrical signals from the control unit to drive the IGBT switches.

Grid Connection Interface Unit:

Circuit Breakers, Contactors: Enable grid-connected/off-grid switching.
Filtering Circuit: Filters out switching harmonics to ensure output power quality.

Human-Machine Interface and Communication Unit:

Touchscreen (HMI): Local parameter setting and status display.
Communication Interfaces: Ethernet, CAN, RS485, etc., for communication with EMS and BMS.

2. Software Functional Module Composition

Core Control Algorithm Module:

Grid-connected Mode: Implements PQ control (active/reactive power decoupling control) and V/F control (establishes voltage and frequency during off-grid or black start).
Phase-Locked Loop (PLL) Module: Tracks grid voltage phase in real time to ensure synchronization.
Protection Module: Overcurrent, overvoltage, short circuit, islanding protection, etc.
Mode Switching Logic Module: Enables seamless switching between grid-connected and off-grid modes.
Communication Protocol Stack Module: Supports standard protocols such as Modbus TCP/IP, IEC 61850, and IEC 104.
Advanced Application Module: Integrates algorithms based on specific scenarios, such as primary frequency regulation, virtual inertia, and harmonic compensation.

EMS (Energy Management System) Composition

The EMS is the "brain" of the power plant, responsible for information processing and decision-making.

1. Hardware Physical Composition

Server/Workstation: Deploys the core EMS software platform, typically using redundant configuration (dual-machine hot standby) to ensure high reliability.
Network Equipment: Industrial switches, routers, firewalls, constructing the station's internal communication network.
Communication Gateway: Used for protocol conversion, connecting devices with different communication protocols (e.g., converting the BMS's CAN protocol to Ethernet).
Uninterruptible Power Supply (UPS): Ensures the EMS continues to operate during power grid failures.
Display Terminals: Monitoring screens, engineer workstations, operator workstations.

2. Software Functional Module Composition

SCADA (Supervisory Control and Data Acquisition) Module:

Basic functions, real-time acquisition of station-wide data (voltage, current, power, status, alarms), and provision of a human-machine interface.

Energy Management Core Module:

Strategy Engine: Automatically generates charging and discharging plans based on preset strategies (e.g., peak shaving, frequency regulation, plan tracking).
Optimization Algorithm Library: Includes algorithms for economic dispatch, multi-objective optimization, etc., to maximize revenue or minimize costs.
Forecasting Module (especially suitable for renewable energy): Integrates or has built-in load forecasting and photovoltaic/wind power forecasting algorithms.

Advanced Application Module:

AGC/AVC Substation: Receives power grid dispatch instructions and automatically controls power generation/voltage.
Electricity Market Trading Interface: Connects to the spot market and ancillary services market, enabling the submission of power output and prices.
Virtual Power Plant (VPP) Aggregation Module: Manages multiple distributed energy storage systems, participating in grid interaction as a whole.
Data Management and Analysis Module: Stores historical data, generates reports, performs performance analysis, and diagnoses faults.
Security and Management Module: Manages user access rights, audits operation logs, and provides network security protection.

Compositional characteristics

System	Grid-Side	Renewable-Side	User-Side
BMS	High-rate, high-precision SOP; high computing power; ultra-low latency	Focus on cycle life and SOH	Focus on economic lifetime and cost
PCS	DSP/FPGA, ms-level response, high overload, thermal design	Fast tracking, advanced algorithms, weak-grid support	High reliability, UPS, anti-backflow
EMS	AGC/AVC core, real-time grid communication	Forecast-driven rolling optimization	Economic strategy engine, TOU pricing, ROI tools

The core of a Battery Management System (BMS) is "precision sensing + intelligent algorithms," which manages battery data and safety in a hierarchical manner.
The core of a Power Processing System (PCS) is "power semiconductors + high-speed controllers," enabling efficient and controllable energy conversion.
The core of an Energy Management System (EMS) is "high-performance computing platform + intelligent decision-making software," which performs information fusion and optimized scheduling.

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