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Page 10 of 15 Li et al. Complex Eng Syst 2023;3:1 https://dx.doi.org/10.20517/ces.2022.46

5. INTELLIGENT CONTROL METHOD AND ENERGY MANAGEMENT STRATEGY OF NEAR
PORT MICROGRID SYSTEM
Because the port scale expands unceasingly, the traditional port will bring more energy consumption and
harmful gas emissions, noise, such as environmental pollution. Marine exhaust has become one of the
major air pollution sources in China’s port cities. Construction of green ports and improving port energy
using clean purification rate are around the corner. It is necessary to adjust measures to local conditions for
the development of distributed photovoltaic (PV) in the harbor and distributed wind. Exploring effective
energy management strategies is one of the key aspects when constructing a port microgrid in the future.

5.1. Distributed control method
A harbor microgrid is designed to manage all energy-related issues within a harbor area. However, so far,
research on this topic has been limited. Ahamad et al. modeled the harbor microgrid and simulated the
steady-state and transient behaviors of the harbor microgrid when it provides shore power supply to
[40]
berthing ships . As the ship enters and leaves the port continuously, there will always be an insertion
operation, which may bring a large pulse to the power grid. From this perspective, seaport controls are
similar to electric car charging stations. However, since the port microgrid is usually composed of many
subsystems, most of which operate independently, the traditional centralized control framework may lead to
inefficiency. Distributed control architecture has great advantages in realizing real-time coordination and is
not restricted by the above problems. Distributed scheme distributes computing and communication
burden to distributed controller and has stronger robustness to communication failure. At present,
distributed framework has been widely used in distributed control and automation of land-based power
systems. Because of this huge advantage, the distributed control method is also suitable for the control of
harbor microgrids. It has good flexibility for network reconfiguration, and its voltage/frequency adjustment
facilitates plug and play of the ship in cold ironing mode.

Zhong et al. analyzed the problems caused by voltage overlimit and network loss increase caused by large-
scale distributed new energy generation access to the safe and stable operation of the distribution network
and proposed a data-driven distributed voltage control method for high-proportion new energy generation
[43]
cluster . Li et al. and Deng et al. studied the impact of large-scale new energy access on the distribution
network and proposed different methods [44,45] . Ma et al. and Liu et al. put forward a new distributed control
method for the current and voltage sharing problem of a DC microgrid [46,47] . Yang et al. and He et al. applied
distributed control technology to port lighting control [48,49] , which improved the intelligent management
level of port lighting control and reduced the energy consumption of port lighting facilities.

5.2. Energy management for demand response at multiple time scales
Renewable energy generation and load demand change in real time, and thus considering multi-time scale
[50]
energy management has gradually become the mainstream . Roy et al. list the main components of port
microgrid, and then review the research on the scale and energy management of port microgrid .
[51]
For the study of energy management at a long time scale, Chen et al. adopt stochastic energy network
theory to deal with the power balance problem to optimize the capacity of islanded microgrid for the
[52]
uncertainty of source and charge . Hu et al. propose a two-stage day-ahead energy management strategy
[53]
including centralized control and distributed control . Li et al. consider day-ahead load forecasting and
[50]
renewable energy forecasting and set the interval as 1 h to propose a distribution optimization strategy .
Huang et al. propose a scheduling framework based on the two-level model, which adopts the advanced
real-time two-stage stochastic optimization method combined with the TOF price mechanism to fully
coordinate the energy management decisions of various market stakeholders .
[54]