Researchers Create a Port Energy-Flow Management System
Scientists at the Solomenko Institute of Transport Problems of the Russian Academy of Sciences have developed an algorithm for forecasting energy consumption across maritime port infrastructure.
The principal source of the information is the Ministry of Science and Higher Education of the Russian Federation. The ministry’s announcement was also distributed by BelTA and TV BRICS.
The organisation’s official name is the N. S. Solomenko Institute of Transport Problems of the Russian Academy of Sciences. Its research covers transport systems, logistics, safety, intelligent management and environmental aspects of transport.
The research group produced a mathematical model and used it to create computer software capable of forecasting demand and supporting the management of energy flows within ports.
Its principal advantage is the ability to adjust to changing equipment-operation patterns instead of applying one permanently fixed set of forecasting parameters.
Port Energy Demand Changes Continuously
Electricity consumption inside a seaport rarely remains stable throughout the day.
Sharp changes can occur when a vessel berths, shore power is connected, ship pumps are activated, container cranes begin operating or several electric vehicles start charging simultaneously.
Demand is influenced by:
- the number of vessels at berth;
- vessel type and size;
- duration of port stays;
- cargo-handling intensity;
- refrigerated-container volumes;
- terminal lighting;
- warehouse heating and ventilation;
- electric tractors and handling equipment;
- weather and seasonal conditions;
- solar and wind generation.
A terminal may handle one small vessel with limited crane activity in the morning and receive a containership and ferry simultaneously several hours later.
A forecast based only on average historical consumption can therefore produce a substantial error.
UN Trade and Development describes ports as both major energy consumers and sources of emissions. Their digital and energy transition is increasingly important to capacity, resilience and competitiveness.
The Algorithm Does Not Use One Fixed Template
A conventional forecasting system may analyse a predetermined number of historical observations and apply the same time interval under every operating condition.
The Russian method is designed differently. It dynamically identifies how many similar consumers or operating patterns should be included in each calculation.
It also selects the appropriate depth of time-series analysis. Several recent hours may be sufficient in one situation, while another forecast may require comparison with similar days, seasons or equipment cycles.
According to the developers’ description, the algorithm adapts to local data characteristics in real time.
This is important because the energy profiles of neighbouring terminals can be entirely different.
Container terminals depend on vessel calls, cranes and refrigerated boxes. Liquid-bulk terminals rely heavily on pumps and transfer equipment. Passenger ports experience pronounced peaks when ferries and cruise ships arrive.
A single rigid model may not perform consistently across all these facilities. An adaptive system can modify the forecasting context to match actual operations.
Forecasts Must Be Integrated With Port Management
A forecast does not itself start or stop generators, storage systems or cranes.
For practical operation, the algorithm must be connected to a port energy-management system.
The software could provide advance warning that demand is likely to rise sharply. The management platform could then:
- reserve additional grid capacity;
- start another generator;
- change battery-charging schedules;
- retain more energy in storage;
- postpone non-critical consumption;
- redistribute load between energy sources;
- warn operators about a possible overload.
When a containership approaches a berth, for example, the port could prepare both shore power and sufficient capacity for several ship-to-shore cranes.
Without a reliable forecast, operators may have to keep reserve generators running or maintain unnecessarily high available capacity. Both approaches increase costs.
Shore Power Is a Major Potential Application
The system may be particularly relevant to shore-side electricity.
A ship continues to consume energy after berthing. Ventilation, heating, cooling, lighting, pumps, control systems, refrigeration and cargo equipment may all remain operational.
Where shore power is unavailable, auxiliary diesel generators commonly supply this electricity.
An onshore power supply allows the vessel to switch off those generators and connect to the land-based grid.
The International Maritime Organization identifies shore power as one method of reducing air pollution, emissions and local noise from ships at berth.
The electricity requirement of an individual vessel can range from below 100 kW to approximately 10–15 MW.
Serving large ships may require a high-voltage grid connection, transformers, frequency converters, control panels and specialised cable systems.
A forecasting error at that scale can be expensive. Insufficient capacity may interrupt shore power or require emergency generation, while excessive reserve capacity raises investment and operating costs.
Emissions Can Be Reduced Near Urban Areas
Many large ports are located close to densely populated communities.
Diesel-powered ships, trucks and handling machinery emit nitrogen oxides, sulphur oxides, particulate matter and carbon dioxide.
The environmental benefit of electrification can therefore be particularly significant near terminals.
The United States Environmental Protection Agency notes that ports concentrate substantial quantities of diesel equipment. Shore power allows vessels to switch off auxiliary engines and reduce emissions during their port stay.
The European Commission also describes onshore power supply as strategic infrastructure for decarbonising berth operations and reducing local CO₂, NOₓ, SOₓ and particulate emissions.
The total carbon benefit nevertheless depends on the source of the electricity.
Where port electricity is produced mainly from coal or natural gas, some emissions are transferred from the quay to the power plant.
The greatest climate benefit is achieved when shore power is supplied by nuclear, hydroelectric, solar, wind or other low-carbon generation.
The System Could Manage a Hybrid Microgrid
A modern port is gradually becoming an energy system rather than a conventional consumer.
A port microgrid may combine:
- the national electricity network;
- diesel or gas generators;
- rooftop solar panels;
- onshore or offshore wind generation;
- tidal power;
- battery storage;
- hydrogen-based systems;
- shore power;
- charging infrastructure for trucks and equipment.
Each source has limitations.
Solar output depends on cloud cover and time of day, wind power depends on weather, and tidal generation follows water cycles.
A battery can respond rapidly to a demand spike but has limited stored energy. A diesel generator provides reliability but creates additional costs and emissions.
An adaptive forecast can identify a likely shortage or surplus in advance and support selection of the most efficient energy combination.
Renewable Energy Would Be Easier to Integrate
One potential role for the new method is the safer integration of renewable generation into port microgrids.
Both supply and demand are variable. Solar and wind output changes with the weather, while demand changes with vessel calls and terminal activity.
If wind generation falls when a large vessel connects, the system must compensate quickly. When renewable production exceeds demand, the surplus can be sent to batteries, electric equipment or other consumers.
Accurate forecasting allows storage and reserve generation to be prepared before frequency or voltage reaches a critical level.
The technology forms part of a broader maritime transition. K2Cargo News previously reported how eco-friendly vessels and new energy systems are supporting the development of offshore wind power.
Avoiding Unnecessary Generator Use Can Cut Costs
Port diesel generators may operate as primary, backup or peak-power sources.
Without accurate demand forecasts, operators may start them too early and leave them running longer than necessary.
More precise forecasting could reduce:
- idle operation;
- inefficient generator starts;
- diesel consumption;
- low-load running;
- engine wear;
- maintenance costs;
- excessive emergency reserves.
The financial result will depend on port size, electricity and fuel prices, microgrid design and data accuracy.
The researchers have not published a specific cost-saving percentage for an operating terminal. A guaranteed level of financial benefit therefore cannot yet be established.
Cranes Create Sharp Power Peaks
Container cranes are among the most powerful electrical consumers inside a port.
Lifting a container creates a short-duration peak. When a load is lowered, modern regenerative systems may return part of the energy to the grid or a storage system.
Demand can increase sharply when several cranes lift containers at the same time.
Automated stacking cranes, conveyor systems, pumps and electric terminal tractors create additional loads.
The algorithm could analyse recurring operating cycles and estimate their combined effect before the peak occurs.
In the future, forecasting could be connected to task scheduling. Crane operations could be distributed to maintain terminal productivity without producing several maximum electricity peaks simultaneously.
Refrigerated Containers Require Separate Treatment
Refrigerated containers require continuous electricity to maintain cargo temperature.
The number connected at a terminal changes as ships, trains and trucks arrive. Seasonal flows of fruit, vegetables, meat, fish and pharmaceuticals can increase demand substantially.
Even a limited power interruption can damage cargo and produce significant insurance claims.
Refrigeration systems are therefore critical consumers that cannot simply be disconnected during a power shortage.
A forecasting platform must distinguish flexible demand from loads requiring guaranteed uninterrupted electricity.
Low Computing Requirements Could Support Wider Deployment
The developers state that the algorithm does not require high-performance computing infrastructure.
This could make it more accessible to small and medium-sized ports without major data centres or large technology budgets.
The software could potentially operate on a conventional industrial server or an edge-computing device inside the control centre.
Local processing would also reduce the delay between receiving operational data and producing a management decision. A port would not necessarily have to transmit its entire technical data stream to an external cloud platform.
Commercial deployment would still require equipment redundancy, cybersecurity and secure connections to operational systems.
Data Quality Will Determine Forecast Accuracy
No forecasting model can produce reliable results from inaccurate or incomplete information.
Ports need smart-meter readings, vessel-call schedules, crane-operating data, weather forecasts, storage status and berth-allocation plans.
Problems may arise when:
- meters transmit data late;
- some equipment is not connected;
- vessels arrive earlier or later than scheduled;
- cargo plans change;
- sensors produce incorrect readings;
- terminals use incompatible data formats.
Implementation will therefore require more than installing new software. Ports need a common system for collecting, cleaning and synchronising operational information.
Investor interest in these capabilities is already increasing. K2Cargo News previously reported that the future maritime analytics market was valued at $3.85 billion.
European Rules Will Increase Forecasting Demand
The European shore-power market is expected to expand significantly.
According to the European Commission, 71 of the 179 TEN-T core maritime ports already have OPS, covering 461 berths.
Within the TEN-T comprehensive network, shore power is installed at 78 berths across 31 of 371 ports.
FuelEU Maritime requires containerships and passenger ships above 5,000 gross tonnes to use shore power or another zero-emission technology at berth from January 1, 2030, in ports covered by the Alternative Fuels Infrastructure Regulation.
From 2035, the obligation will extend to all EU ports that have developed the relevant infrastructure.
Connecting more vessels will make demand forecasting a central element of port-grid management.
Operators will need to understand not only the maximum power requirement of one vessel but also the probability that several major consumers will connect simultaneously.
Critical Infrastructure Could Become More Resilient
Navigation, security, firefighting, communications, access control and dangerous-goods systems all depend on reliable electricity.
During an external-grid failure, a port must preserve power for critical consumers and shut down secondary equipment safely.
An adaptive algorithm could identify an approaching power deficit and prepare the system to enter backup operation.
It could also help determine how much energy should remain permanently available in battery storage.
A reserve that is too small creates operational risk, while an unnecessarily large reserve prevents the battery from being used efficiently for peak reduction.
At terminals handling dangerous or temperature-sensitive cargo, resilience may be more important than immediate financial savings.
Industrial Trials Are Still Required
The Ministry of Science and Higher Education states that the method achieved greater accuracy than several contemporary forecasting models.
However, the announcement does not provide specific error measurements, dataset size or the names of ports used for validation.
It also does not disclose:
- the forecast horizon;
- how frequently calculations are updated;
- which equipment categories were included;
- whether the system was tested with operational shore power;
- whether the software has been formally registered;
- when commercial deployment could begin.
Pilot operation at a working port will be necessary before the research can become an industrial product.
The system should be tested across different seasons, vessel-schedule disruptions, sensor failures and sudden terminal-mode changes.
It must also be demonstrated that an incorrect forecast cannot interrupt critical equipment or compromise safety.
The Development Reflects a Global Trend
Ports worldwide are undergoing simultaneous digital and energy transitions.
The International Maritime Organization describes ports as essential participants in maritime decarbonisation. Potential measures include renewable shore power, alternative fuels and improved logistics-chain planning.
UN Trade and Development also highlights the role of digital technologies in anticipating operational changes, supporting faster decisions and improving infrastructure resilience.
The Russian development combines these two directions by applying digital analysis to an energy and environmental challenge.
If its stated accuracy is confirmed in operational conditions, the algorithm could become part of a smart-port system linking vessel calls, terminal operations, electricity generation, energy storage and consumption.
Practical Deployment Will Determine the Final Result
The model addresses one of the most difficult problems in port energy management: forecasting demand under continuously changing operating conditions.
Adaptive data selection prevents the system from being tied to one rigid template. Low computing requirements could make it available beyond the world’s largest ports.
The most promising applications include shore power, hybrid microgrids, renewable-energy integration and diesel-generator optimisation.
Its ultimate effectiveness can only be established through industrial trials. Port operators will require verified information covering accuracy, savings, resilience and cybersecurity.
Successful implementation could allow ports to reduce operating costs, maintain reliable power and cut air pollution in neighbouring coastal communities.
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