FUTURE ENERGY STORAGE SOLUTIONS

IN MARINE INSTALLATIONS

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FESSMI

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FINAL REPORT

Kimmo Kauhaniemi, Jagdesh Kumar, Jari Lahtinen, Aushiq Memon, Hayder Al-Hakeem,

Omid Palizban, Lauri Kumpulainen, N. Rajkumar

University of Vaasa

Olli Pyrhönen, Antti Pinomaa, Tuomo Lindh, Pasi Peltoniemi, Andrey Lana, Henri Monto-

nen, Kyösti Tikkanen

Lappeenranta University of Technology

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CONTENTS

SUMMARY 3

FOREWORDS 5

1. INTRODUCTION 6

2. WP 1 – LIFE CYCLE ANALYSIS FOR HYBRID MARINE TECHNOLOGY 72.1. Cruise ferry 72.2. OSV 112.3. TUG 13

3. WP 2 – HYBRID VESSEL HARBOUR SUPPORT SYSTEM MODELLING ANDANALYSIS 143.1. Harbour Area Smart Grid 143.2. Protection studies 17

4. WP 3 – HYBRID VESSEL ELECTRIC SYSTEM MODELLING AND ANALYSIS20

4.1. Diesel generator set 214.2. Battery Energy Storage System 224.3. Propulsion Drive 224.4. Cruise ferry 234.5. OSV 25

5. WP 4 – REMOTE VESSEL DATA MANAGEMENT 27

6. WP 5 – DEMONSTRATION SYSTEM DEVELOPMENT AND TESTING 296.1. AC network emulator hardware and communication structure 306.2. DC network emulator hardware and communication structure 326.3. Real time simulators 33

7. LIST OF REPORTS AND PUBLICATIONS 34

3

SUMMARY

In this research project new energy efficient solutions for marine vessels taking full advantage

of hybrid technology and battery energy storages were studied and developed. In addition,

harbour support infrastructure, which allows vessel energy storage interaction with on-shore

grid and renewable resources was investigated.

Battery technology is developing fast due to increased utilization of electric vehicles. Until

now battery energy storage has not been used in large extent in marine applications, but there

is an increasing interest towards higher utilization of electric storages for reducing emissions,

and fuel savings, and improved energy efficiency of modern all-electric and hybrid vessels.

The utilization of batteries offers power balancing, reserve power and short response times

for marine vessel power systems. In this project, both technical and economic feasibility of

using battery energy storage technology in vessels were studied by simulations and laboratory

experiments. Since load profiles and power systems have large variance in different vessel

types, three different vessel types were selected for detailed case studies. Based on the results

got from vessel hybridization studies, it was shown that by adding batteries to vessels even

with current battery price levels, remarkable total savings, measured and estimated with fol-

lowing measures; vessel CAPEX, OPEX, and improved fuel efficiency, can be reached in

each vessel type. Moreover, the effect of different vessel power distribution systems on total

savings were analyzed in the studies.

Dynamic behavior of the vessel power system was analyzed by building simulation models

of the case vessels and simulating the models with actual power data retrieved from the case

vessels. Based on the simulation results battery energy storage on board can improve fuel

efficiency by allowing diesel generator set to be run on better fuel efficiency region. Dynamic

performance of the vessel increases as the time constant of the battery is much shorter than

the time constant of a diesel engine. For instance, off-shore support vessel (one of the ana-

lyzed vessels) can shutdown one of its diesel engines during dynamic positioning while using

battery energy storage to level load fluctuations without compromising its performance.

Two emulator systems for hybrid diesel electric vessel power train were created in the project.

The first one is for testing the AC power distribution and another for the DC distribution.

4

The emulator is a tool for research of energy balancing between diesel generators and a bat-

tery energy storage. Different control laws were tested for both system energy balance and

battery energy storage control as a part of the system. Also, the emulator is used to verify the

simulation models of the hybrid power trains developed in WP3. The aim of the simulations

and emulations is further to study the fuel economy, dynamic performance and the stability

of developed control laws.

In addition to on-board energy storage systems, future vessel types can take advantage of

harbour based renewable energy production and energy storages. For that purpose an inno-

vative design concept of harbour area smart grid (HASG) was developed in this project,

which can supply shore to ship power during stay of vessels at a harbour as well as support

hybrid and fully electrified vessels. In the project, feasible alternative topologies for the

HASG was developed considering different operating scenarios. Simulation models were

used for the dimensioning of the key elements and checking the system performance.

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FOREWORDS

This report summarizes the results of the FESSMI project, which is executed as a joint action

between Lappeenranta University of Technology (LUT) and University of Vaasa (UVA). At

the LUT the responsible leader of this project was Prof. Olli Pyrhönen and in the UVA Prof.

Kimmo Kauhaniemi. The project was a part of the INKA-program of Tekes, and the funding

came from the European Regional Development Fund (ERDF).

In addition to the public funding, the project was also funded by the following industrial

partners (representatives in steering group given in parentheses):

Wärtsilä (Tuomas Linna)

Danfoss (Hannu Sarén)

VEO (Ari Pätsi)

CLS Engineering (Timo Hanhimäki)

We are very grateful for all the partners and authorities for the financial support to this pro-

ject. Also, the active engagement of the industrial partners is acknowledged.

Authors

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1. INTRODUCTIONThis project investigated new short shipping concepts for environmental friendly and energy

efficient vessel drive technology, where large-scale on-board battery storage combined with

new control concepts and topologies play a key role. In addition to that, research was fo-

cused for harbour-based support system technology for hybrid and fully electrified vessel

types, where connection to renewable energy production, harbor-based energy storages and

system grid integration are investigated on the conceptual level. Finally, the project aimed for

such results, which can be later demonstrated in a separate full vessel scale demonstration

project on an EU-level project.

The project is divided into five work packages. The work packages of the project are:

WP 1 – Life cycle analysis for hybrid marine technology (LUT, UVA)

WP 2 – Hybrid vessel harbour support system modelling and analysis (UVA)

WP 3 – Hybrid vessel electric system modelling and analysis (LUT)

WP 4 – Remote vessel data management (UVA)

WP 5 – Demonstration system development and testing (LUT)

Main results from all the WPs are summarized in the following chapters.

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2. WP 1 – LIFE CYCLE ANALYSIS FOR HYBRID MARINE

TECHNOLOGYBattery technology is developing fast due to increased utilization of electric vehicles. Marine

vessels are new and interesting application area for battery energy storages. The utilization

of batteries offers power balancing, reserve power and short response times for marine vessel

power system. Expected large volumes in electric vehicle battery production is bringing tech-

nology price down, which gives new possibilities also to other application areas, like marine

vessels. FESSMI project investigated possibilities to utilize battery technology in marine

applications. Since load profiles and power systems have large variance in different vessel

types, they are studied case by case. Three cases, from different marine segments, were stud-

ied; hybridization of cruise ferry, off-shore / platform support vessel (OSV/PSV), and TUG.

2.1. Cruise ferryThe first study case focuses on battery storage options for cruise ferry type of vessel. Both

technical and economical feasibility have been investigated. Battery technology is not the

only option for electric energy storage. Electric energy can also be stored into fly wheels or

supercapacitors etc. These technologies offer very high maximum power and low energy

density compared to batteries. In cruise ferry case, the batteries offer the best power-energy

density combination, thus other technologies are not investigated in this study.

There are various battery technologies on the market. Important features to be considered

in marine battery technology are available cycle life, energy density, maximum peak power as

well as present and future estimated price. Most favorable battery chemistry solutions are

based on lithium-ion-batteries. Strong driver for lithium-ion-battery market and technology

development are electric vehicles, where lithium technology is selected without exception.

There are several different versions of lithium-ion batteries. Most promising technologies for

vehicles as well as for marine applications are lithium iron phosphate (LFP), lithium nickel

manganese cobalt oxide (NMC) and lithium titanate (LTO). In all these battery chemistries

one electrode is made of graphite (negative in LFP and NMC, positive in LTO) and other

electrode material is according to battery name. The essential technical differences in these

battery types are maximum discharge rate C (LFP; C=1, NMC; C=2, LTO; C=10), number

of life cycle (LFP; 1000–2000, NMC; 1000–2000, LTO; 3000–7000) and energy density (LFP;

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90–120 Wh/kg, NMC; 150–220 Wh/kg, LTO; 70–80 Wh/kg). Battery investment cost –

together with cycle life and technical performance – is an important measure for applicability

in marine applications. The lithium battery technology price reduction is dependent on the

used materials. While LTO cell price estimate for year 2020 is 600 USD/kWh (2014: 800

USD/kWh), the respective estimate for LFP is 440 USD/kWh (2014: 700 USD/kWh) and

for NMC 300 USD/kWh (2014: 600 USD/kWh). In cruise ferry CAPEX and OPEX analysis

NMC battery technology price and life time estimates were used due to highest energy den-

sity and most favorable cost condition.

The battery feasibility in marine vessel depends heavily on the loading profile of the vessel.

Load profiles differ in great deal in different vessel types. While off-shore support vessels

(OSV) have high instantaneous power demand peaks e.g. due to dynamic positioning re-

quirements, the cruise ferry has dynamically much lower requirements. These kind of differ-

ences do not allow to develop general rules for marine battery selection, but more detailed

analysis is needed, where the specific requirements of the loading profile is taken into ac-

count. The basis in this study is the loading profile of cruise ferry under study. The vessel

sails through archipelago between two harbours once per day, which gives a unique 24 h

loading profile to the vessel loading. The harbor time for the vessel is just one hour at both

terminal harbors, which requires high power capacity to the battery charging. Essential tech-

nical questions in the feasibility analysis are possible battery energy capacity, maximum

power, system topology and charging method among others. When analyzing economical

feasibility, battery system price, life-time estimate and energy capacity are most important

parameters. Battery capacity relates to the possibility to reduce the total engine power, which

could be replaced by the battery stored energy. The most relevant savings are reduced com-

bustion-engine-related investment and higher fuel efficiency.

The analyzing methodology in the study was based on comparison of four different scenar-

ios, where battery size and concept has been varied. The different scenarios were:

SCENARIO 1: Battery capacity 1.5 MWh, fixed mountingSCENARIO 2: Battery capacity 2 MWh, mobile batteriesSCENARIO 3: Battery capacity 9 MWh, fixed mountingSCENARIO 4: Battery capacity 6 MWh, mobile batteries

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The fixed batteries are installed into the ship machine room, while mobile batteries are lo-

cated on a cargo deck, which enables fast change in harbor and low speed 24 h charging. The

battery capacity has effects on the battery usage during the cruising. Small battery (Scenarios

1 and 2) is used for smoothing the combustion engine power profile, where fast power

changes are handled with the battery capacity. In scenarios of large battery (Scenarios 3 and

4), the battery can be used to power leveling and diesel engine working point optimization.

In all the analyzed scenarios, it is assumed that in the harbor the ship is in cold ironing mode,

where all the power is supplied from the on-shore grid.

Battery system in MWh-range requires large volume of space. Important issue is then battery

installation options. This was analyzed for both fixed batteries and mobile versions. Mobile

batteries would be a favorable solution for existing ship, since batteries could be located on

a cargo deck and battery handling could be done using normal harbor cargo handling equip-

ment. This, on the other hand, would cause some reduction in the cargo capacity; approxi-

mately 1% for container installed 2 MWh battery module increasing linearly as a function

total battery energy capacity. Another benefit would be possibility to charge battery modules

in the harbor within a longer time period. Longer charging time might increase the battery

life time and harbor charging would allow usage of renewable energy, e.g. using local wind

or solar power. Battery connection and disconnection would cause some extra costs, but

those have not been analyzed in detail. Fixed batteries are an alternative solution for a new-

build ship. In Scenario 3 the large battery capacity would allow reduction of one diesel engine.

This would free enough space for battery package in the engine room. When looking overall

ship power system CAPEX, scenario 3 would also reduce the overall cost compared to pre-

sent cruise ferry power, if the expected near future battery system prices are used. According

to this analysis, the CAPEX for scenario 3 would be lower compared to present installation

by the year 2025. In Scenarios 1 & 2, power system CAPEX would obviously increase, since

in those scenarios the number of engines remains the same.

The OPEX analysis is the most important factor, when economical feasibility is assessed.

The biggest cost factor relates to the fuel consumption, other factors are additional electricity

costs (due to cold ironing in the harbor), maintenance costs and emission (CO2) costs. Im-

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portant question in the fuel efficiency analysis is the optimal load sharing between the bat-

teries and the combustion engines. Two different operational principles were used. In case

of small battery (Scenarios 1 and 2), single engine operation is assumed. It means, that instead

of running 2 engines at partial loads, one engine is running in the optimal point, and addi-

tional power is taken from a battery. In case of large battery energy capacity (Scenarios 3 and

4), zero emission operation is used. This means, that near the harbor engines are not running,

but the power is taken from the battery alone. When battery discharge reaches 80%, normal

engine operation is started. In practice, this might not be acceptable according to current

safety regulation, but might change in future, when energy storages are in large use in vessels.

The OPEX analysis gave yearly savings to all scenarios due to reduced 1) fuel consumption,

2) emissions and 3) maintenance. On the other hand some electricity costs were added due

to hotel load and battery charging in the harbor. The payback times for scenarios were: 6 a

for Scenario 1, 9 a for Scenario 2, 7.5 a for Scenario 3 and 20 a for Scenario 4. It is to be

mentioned, that if reduced freight capacity is taken into account, the economics of Scenario

4 get worse. In the calculation battery system price 622 €/MWh corresponding 2016 price

level was used. The battery prices are getting lower, which will give shorter payback time in

the future.

The final comparative analysis was done between medium-voltage DC and AC vessel power

systems including battery storage. The main benefit in DC compared to AC system is the

possibility to run the engine at optimal speed as a function of a varying load. Specially at the

partial loads the engine fuel consumption can be reduced using variable speed. The analysis

show, that with a large battery (8 MWh, 14 MW for DC, 20 MW for AC) combustion engines

can be driven in the optimal working point all the time giving fuel savings 8% for DC and

5.8% for AC compared to the original. In case of small battery, the purpose is to stabilize

the engine loading profile. The analyzed smoothening operation requires battery capacity of

400 kWh and 5.8 MW. This requirement could be fulfilled with 600 kWh LTO (10C), 2 MW

NMC (3C) or 6 MWH LFP (1C). The battery life time in different cases would be 4.5 a

(LTO), 6 a (NMC) or 4.5 a (LFP). The fuel saving in AC battery system case found to be

0.3% while DC battery system produced fuel saving 5.8%. The above-mentioned results,

related analysis methodology and used assumptions can be found more in detail in Life cycle

analysis for hybrid marine technology – Case: Cruise ferry public research report.

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2.2. OSVThe second study case focused on battery storage options for off-shore/platform support

vessels (OSV/PSV). This vessel type has highly dynamic loading due to dynamic positioning

requirements. This emphasis the benefit of batteries to response faster to power transient

compared to diesel or gas engine.

There are various battery technologies in the market. Important features to be considered in

marine battery technology are available cycle life, energy density, maximum peak power as

well as present and future estimated price. Most favorable battery chemistry solutions are

based on lithium-ion-batteries. Strong driver for lithium-ion battery market and technology

development are EVs where lithium technology is selected without exception. The techno-

logical variation in several lithium battery types relate to available maximum peak power vs.

stored energy and maximum life cycle. High cycle life and peak power correlates straightfor-

ward also to higher battery cell prices.

The battery feasibility in marine vessel depends heavily on the loading profile of the vessel,

since load profiles differ in great deal in different vessel types. Off-shore support vessels

have high instantaneous power demand peaks especially during dynamic positioning. For

OSV, high peak power battery would be optimal from technical point of view, but the higher

battery price due to peak power demand increases the battery cost. For that reason, analysis

has been performed for three different lithium battery types; lithium iron phosphate (LFP),

lithium nickel manganese cobalt oxide (NMC) and lithium titanate (LTO). LTO batteries

provide highest peak power and cycle life, while NMC and LFP offer lower energy storage

costs due to lower cell prices.

The basis of the analysis in this study was the loading profile of OSV under study. Two weeks

of operational vessel data has been used to simulate the detailed battery operation in different

driving modes. Also annual data was used for analyzing overall profitability. Based on sim-

ulation analysis, a sufficient battery capacity was selected for different battery chemistries.

Accordingly, investment costs (CAPEX) and operational costs (OPEX) for this particular

OSV case were derived. A few alternative load sharing control strategies between engines

and batteries were included into analysis for the sake of generality.

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The main component in the OPEX are fuel costs. The fuel savings of ESS was investigated

both in AC (alternating current, 50 Hz) and DC (direct current) grid cases. The essential

advantage in DC grid is the possibility to have variable speed in diesel-generators. The oper-

ational analysis of annual load profile showed, that battery storage brings significant savings

to the ship operation both in fuel consumption and engine running hours. In DC grid case

the fuel consumption was reduced by 22% and engine running hours by 41%, while in AC

case the corresponding numbers were 16% for fuel savings and 42% for engine running

hours. The battery cycle life analysis resulted between 11.9–20.3 a depending on the battery

type and grid topology. The additional savings in OPEX are based on reduced maintenance

costs due to lower engine running hours and also due to reduced CO2 emissions. The fuel

price range 20–60 €/MWh and emission price 0–20 €/tn has been assumed. Today, there is

no CO2 emission cost, so the emission cost has been included mainly for possible marine

vessel emission control in the future. The maintenance costs for the ICE was assumed to be

around 20 €/h. For both AC and DC grid option, the total OPEX saving vary between 175–

417 k€ per year. The CAPEX consists mainly on battery system and necessary electrical com-

ponents and system technology. As an example, additional battery investment for a newbuild

ship is in the range of 500–600 k€ using present LTO battery prices.

Combining OPEX and CAPEX calculations payback time for different battery options can

be analysed. The shortest payback time, when emission cost is 0 €, for retrofit with present

battery prices and high fuel costs (LNG: 60 €/MWh) is 1.73 years using LTO battery tech-

nology or 1.86 years using NMC batteries. If fuel price is low (LNG: 20 €/MWh), the corre-

sponding payback times are 3.17 a for LTO and 3.40 a for NMC. The estimated decrease in

battery prices (2030) would reduce the payback times further. For a new build ship at 2030

the most favorable alternative would be LTO battery with DC grid resulting payback time

0.66a for high fuel price. Even low fuel price would result short payback time 1.31 a. The

required battery storage capacity and needed floor space depends on the chemistry. For ret-

rofit LTO would be the most reasonable option due to lowest battery size, only 1.5 m x 2.6

m floor area with cabinet height 2.2 m for battery unit would be needed. The total battery

mass would be 5.44 tn. Also converter could be installed onto OSV under study. Other bat-

tery chemistries require more floor area, which is a drawback in retrofit installation. If new-

build ship is considered, then all battery chemistry alternatives can be considered.

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2.3. TUGThe third case study was on the battery energy storage feasibility in TUG type of marine

vessel. Actual TUG operational profiles were used for battery loading analysis. Vessel oper-

ation in tens of different TUG tasks were used in the analysis, the operational data containing

over 50 hours and 150 nmi of vessel operation was given with 1 minute resolution. Hybrid

system scenarios on different diesel engines, PTI/PTO, PDS and BESS were analyzed. The

inputs for analysis were: load profiles, engine efficiency and fuel consumption, PDS compo-

nents efficiency, engines and PDS investment cost, fuel and maintenance cost, hybrid vessel

configurations. Operation of TUG PDS in different operation modes was investigated.

These are full electric modes: sail out, stand-by and light assist, and hybrid modes: peak shav-

ing, load leveling and boost (light/medium/heavy assist). Next, suitable battery types were

analyzed: high energy type NMC - lithium nickel manganese cobalt oxide (Graphite/NMC)

and high power LTO - lithium titanate (LTO/NMC). The main requirement for hybrid ves-

sel PDS configuration was equal bollard pull capability. Six cases were formed, with engines

from 0.8 MW to 2 MW, and PTI/PTO from 250 kW to 1.5 MW, and BESS from 100 kWh

to 600 kWh. Vessel CAPEX was calculated from PDS configuration, and OPEX was com-

puted by time-domain computation based on actual vessel profile.

Hybrid LVDC PDS was found to be techno-economically feasible with two of six configu-

rations with equal bollard pull capability examined. In first case, 8% CAPEX reduction for

vessel powerplant and power distribution, and 54% OPEX reduction were estimated. Here,

the results showed 40% less fuel consumption and 77% less running hours and therefore

remarkable reduction of pollution. In second feasible case, 14% CAPEX reduction and 37%

OPEX reduction are estimated, with 25% less fuel consumption and 59% less running hours.

In both studied cases fuel saving were minor factor. Fuel savings during BESS lifetime were

slightly higher that BESS re-stock costs and justify the investment. Maintenance savings are

major system benefit. Depending on case, 100–625 kWh capacity was found sufficient with

requirement of 5C capability of energy storage cells. Due to vessel low annual amount of

running hours, battery should be used heavily to use cycling potential in calendar life, battery

life time estimate was 17–25 a.

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3. WP 2 – HYBRID VESSEL HARBOUR SUPPORT SYSTEM

MODELLING AND ANALYSISElectrification by renewable energy based Distributed Generation (DG) and Battery Energy

Storage (BES) on board, as well as onshore, is inevitably the best solution to increase the use

of pollution-free energy, especially at harbour areas. The process of shutting down diesel

engines of vessels, and getting power supply from shoreside for ships’ auxiliary services dur-

ing a stay at harbours is historically known as cold ironing or onshore power supply or shore

to ship power. In the future, the power supply is also needed for charging the BESS on

board, thus increasing the amount of power needed to electrify harbour area. In this regard,

the aim of this work package (WP) is to develop the design of harbour area grid in such a

way that it can supply shore to ship power supply for the vessels during a stay at harbours as

well as facilitate the charging of the batteries.

In this WP, a comprehensive state of the art survey about the technology development in

shipping, future marine solutions, and shore to ship power supply was made. As a result of

this part a paper was produced, where the review section explains the existing practice, cur-

rent standards, barriers and technical challenges in implementing shore ship power supply.

The paper also highlights on adopted voltage levels and frequencies of the power supply of

various types of ships on board and their associated voltage, power and cable requirements

from shoreside.

3.1. Harbour Area Smart GridAs a main result of this WP, an innovative design concept of the Harbour Area Smart Grid

(HASG) was developed that meets the future technical requirements. In practice, several

alternate designs of harbour grids are possible, but two appropriate design models having

features of slow and fast charging of batteries have been developed. The key features of the

distinctive design models proposed for the HASG are to support the vessels for cold ironing,

provide a facility for charging the batteries and employing the renewables and battery storage

at harbours. Each proposed design model can be suitable for a particular case depending

upon technical requirements of the ships, the space, and infrastructure available on ports.

The proposed charging scenarios can open new business models for ship owners and port

administrators.

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The designed concept also utilizes local renewable based DG. In this way, the new HASG

concept will not only provide a pollution-free environment at the harbour area but also bring

many benefits to the owners of hybrid vessels and seaports. The reliability and efficiency of

the power supply will also be increased for harbour area consumers, terminal operators, port

administration, and power utilities by employing power generation by the DGs at the harbour

area.

An example of the single line diagram of the HASG is shown in the following Figure. The

HASG supports the harbour area load, cold ironing load and facilitates the hybrid and electric

vessels for charging the batteries in the harbour area. In this design, the Harbour Area Bus

of 20 kV is the bus for common coupling, which is supplied by the main grid, the HASG,

and the wind power supply near to the harbour area. The HASG consists of photovoltaic as

a DG and the BESs at various locations for the sake of reliability and stability of the whole

power system. The hybrid vessel bus and the frequency converter stations are located nearby

the seaports in the harbour area. The frequency converter is used to convert 20 kV, 50 Hz

to 20 kV 60 Hz for supplying power to the vessels operating at 60 Hz during cold ironing.

Two shoreside transformers are connected with hybrid bus and the frequency converter sta-

tion to step down the voltage from 20 kV to 6.6 kV at 50 Hz and 60 Hz respectively. A

shoreside transformer is required according to the HVSC standard to isolate galvanically one

ship from another ship or consumer. However, this may not be mandatory in case if a dedi-

cated high voltage shore supply transformer is available onboard. Thus, two dedicated ship

buses or double bus bar are required to provide power to the ships at 50 Hz and 60 Hz. The

other promising feature of the HASG is to support the future hybrid vessels at the harbour

with the charging of the batteries for the electric and hybrid vessels. The batteries can be

charged in a container (movable) during off-peak time and replaced with discharged batteries

of the hybrid vessels during the process of cold ironing at harbour area. There are several

other possibilities of charging the batteries other than the container-based solutions, which

are presented with detail in a separate report.

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Figure 1. Harbour Area Smart Grid

The designed HASG is modelled in PSCAD/EMTDC and performance of harbour grid

including slow and fast charger models was validated by simulating different case studies in

PSCAD/EMTDC. The response of the HASG was observed both under steady state and

transient state of operation. The steady state analysis of the HASG showed that the voltage

and frequency at all buses are maintained within limits. Especially onshore bus voltage is

within the limit of 3.5% of the voltage drop of the nominal voltage as specified in the current

standard document “High Voltage Shore Connection (HVSC)”. For transient analysis, two

case studies are considered, one case of disturbance from the grid side and another case of

dynamically varying load from the ship side. The results showed that all bus voltages remain

within limits of ±10% of their nominal values, while onshore bus has voltage within specified

limits as mentioned in the HVSC standards. Furthermore, frequency of onshore power

supply remained constant, and the total harmonic distortion (THD) of charger current and

voltage were within the limit of 5%.

Ship Bus, 6.6 kV, 50 or 60 Hz

20/6.6 kV20/6.6 kV

Hybrid Vessel Bus, 20 kV, 50 Hz

6.6 kV, 50 Hz

20/0.69 kV

AC/DCConverter

AC/DCConverter

AC/DCConverter

BatteryEnergyStorage

BatteryEnergyStorage

BatteryEnergyStorage

Batteries in Container

Cold IroningNormal

charging ofbatteries

6.6 kV, 60 Hz

50/60 Hz

20/0.69 kV

0.69/20 kV

20/0.69 kV

HarbourArea Load

FrequencyConverter

Photovoltaic

0.69 kV Bus

Main Grid

110 kV Bus

115/21 kV

Harbour Area Bus 20 kV, 50 Hz

BatteryEnergyStorage Battery

EnergyStorage

20/0.69 kV

WindTurbine

0.69 kV Bus

BatteryEnergyStorage

0.69 kV Bus forcharging batteries

Harbour Area Smart Grid

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3.2. Protection studiesNormally, the harbor area supply system will be operated in grid-connected mode for a stable

operation. However, during the faults on the main grid, only the DGs and BESS will be

available to supply power, in this situation the HASG is said to be operating in islanded

mode. The overall structures essentially make HASG as AC Microgrids with DGs, energy

storage and loads which can be operated in grid-connected or islanded mode. Therefore, the

standards related to DGs and AC Microgrids are very much relevant to the proposed alter-

natives in addition to the standards applicable for “shore-to-ship connection” of marine in-

stallations.

The main objective of the protection studies made in this WP was to select and analyze the

protection schemes for the various faults scenarios for one of the proposed HASG from

here onwards called as harbor area AC Microgrid. It is known from the previous research

that the traditional protection schemes based on OC relays and fuses with single-settings will

work satisfactorily in grid-connected mode due to sufficient short-circuit current from the

main grid. However, in islanded mode, more sensitive protection strategies will be required

due to limited available short-circuit current from DGs. Therefore, the main focus of the

studies made was on the islanded-mode fault scenarios. Nevertheless, the selected cases for

grid-connected mode were also considered. In the studies made the following questions have

been addressed:

What types of faults may occur in the developed harbor area AC Microgrid during

different operational modes and what is the magnitude of short-circuit current in

those situations?

What type of protection strategies will be adequate for the considered fault types?

How effective are the considered protection strategies during grid-connected and

islanded mode of operation?

The studied HASG (see Figure 2) is a seven-bus supply system consisting of two main-grid

buses (110 kV and 20 kV), two harbor area buses (20 kV and 0.69 kV), one charger bus (0.69

kV), one port bus (0.69 kV) and one ship bus (6.6 kV). The three units of container-based

vessel-BESS each of 2 MW rating are connected with the 0.69 kV charger bus. These con-

tainer-based vessel-batteries are charged overnight with 0.1C slow charge rate (10 hours for

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full charge). The supply to the cold-ironing load of 2 MW, 6.6 kV with two different fre-

quencies of 50Hz and 60 Hz is also provided via the 20 kV harbor bus.

Figure 2. HASG used in protection studies.

The detailed results of the simulation studies made are presented in a separate report. Ac-

cording to the simulation studies made for both grid-connected and islanded modes of op-

eration in different DG-scenarios it is clear that the traditional OC protection relays and

fuses with single setting provide complete protection to HASG in grid-connected mode only

and their response is either slow or ineffective for islanded-mode of operation. The adaptive

protection settings lower than the grid-connected mode settings are necessary for islanded

mode of operation even if DGs in islanded-mode provide maximum fault contribution up

to two-times the rated current.

19

The proposed adaptive OC protection can be implemented by using fast communication

links between relays according to IEC 61850 communication standard. The scheme can be

implemented equally well for both 50 Hz and 60 Hz vessel types. However for 60 Hz vessel

type due the presence the 50 Hz/60 Hz frequency converter at 0.69 kV harbor bus the relays

at cold ironing connection require the fixed lower settings for both grid-connected and is-

landed mode because of limited fault rating of frequency converter which is only twice the

rated full load current.

The full-range fuses provide the fastest possible fault protection for the chargers and the

frequency converters for input terminal faults in grid-connected mode. The fuses and grid-

connected OC relay settings are not effective for islanded mode even if converter-based DGs

provide maximum fault current contribution of twice the rated current.

The fault analysis results were produced only for 50 Hz vessel supply in details. For 60 Hz

vessel type the modelling of the fault current limiter control of the frequency converter needs

still some further development to be done in future projects.

As a final conclusion it can be said that the adaptive protection based on IEC 61850 com-

munication standard will be required for the proposed harbor area AC Microgrid to enable

its operation in both grid-connected and islanded mode. The use of adaptive protection and

communication links will help detect, locate and clear the fault in the minimum required

time. Nevertheless some delays due to mathematical conversion (instantaneous to rms value)

and communication are unavoidable; therefore some delay tolerances/safety margins will

have to be included for the correct protection coordination. The current standards for low

voltage ride through (LVRT) also called fault ride through (FRT) allow the fault contribution

from DGs for only initial 150 ms or so after the fault depending on individual country stand-

ards. After the 150 ms fault ride through time is passed the DGs are no more bound to be

connected to the network. But for the proposed harbor area AC Microgrid operation in

islanded mode the DGs should provide fault current contribution for at least 2 s after the

fault in order to ensure complete protection coordination between relays. To meet this re-

quirement all of the DGs should be equipped with full-scale converters and the LVRT stand-

ards of DGs need to be revised for islanded mode operation.

20

4. WP 3 – HYBRID VESSEL ELECTRIC SYSTEM MODELLING

AND ANALYSISThe 3rd work package (WP3) concentrates on the modeling of the electrical grid of a marine

vessel and control of the power balance. Special interest is put on adding energy storage

(battery) onboard. Simulation blocks were created from the components of the vessel power

grid. Such blocks were generator set, propulsion, hotel load, cables, and battery energy stor-

age system (BESS). These model blocks are described in following subchapters.

Cruise ferry and offshore supply vessel (OSV) were modelled in Simulink using these blocks.

Models were simulated using different control methods for generator sets and BESS. Droop

control and isochronous control was used for gensets. Isochronous control and power con-

trol based on average load power estimation was used for BESS.

Actual recorded propulsion power data from the case vessel was used as an input to the

simulation. Figure 3 describes the top level of the simulation model of the cruise ferry.

Figure 3. Top level of the simulation model of the cruise ferry under study. It consists of three diesel genera-

tor (DG) models (blue blocks), two propulsion loads (orange blocks), hotel load and battery energy storage

(BESS, the green block) and AC grid cables, which are Pi-section lines.

21

4.1. Diesel generator setThe diesel genset model consists of the diesel engine model and the generator model. Figure

4 describes the top level of diesel genset model. The generator model in Figure 4 is a standard

Simscape library block parametrized according to the given initial data. The diesel engine

model consists of an engine model and an actuator model. Step response of the diesel engine

model (actuator and engine) is presented in Figure 5. A step is fed to the input (fuel request)

and the output is (torque) is presented.

Figure 4. Diesel genset model consists of a diesel engine model and a generator model.

Figure 5. Step response of the diesel engine model (actuator included).

0 10 20 30 40 50 60Time [s]

0

0.2

0.4

0.6

0.8

1

1.2Step response

InputOutput

22

4.2. Battery Energy Storage System

The top level of the BESS model is presented in Figure 6. The model contains a battery

model and a grid converter model. The battery model is a standard Simscape battery model,

which can be parametrized to fit each simulation case from a mask. The grid converter is

controlled by a power reference signal, which is coming from an external power reference

block. The power reference is fed to the current controller of the grid converter as current

reference. The grid converter keeps track of the grid angle by a phase-locked loop. The con-

verter model is simplified to lighten the calculation and does not contain switches. They are

simply replaced with current sources.

Figure 6. Top level of the battery energy storage system model.

4.3. Propulsion Drive

At first, it’s worth mentioning that this model does not contain model of the actual drive.

This simplified model just draws the specified power from the grid. The simplified propul-

sion drive model consists of a power transformer, two diode bridges, DC-link model and a

current source. The propulsion power data can be loaded from a file. As the grid converter,

this model also does not contain switches. The propulsion drive is modelled by a controlled

current source which sinks power from the DC-link. The propulsion data is recorded from

the actual vessel. The same data is used in all simulation cases, for comparison. Additionally,

there exists a hotel load which is all the other loads in the ship (pumps, fans, lighting, etc).

23

Figure 7. Top level of propulsion model.

4.4. Cruise ferryThe model of the cruise ferry is simulated using droop control, isochronous control and

running the diesel engines only on optimal economy point. Droop control is used in the

actual case vessel to control diesel generators. Hence, it is also simulated here to establish a

baseline.

Isochronous control is used in simulations with battery energy storage, because it allows

more flexible load sharing among generators compared to droop control. Two isochronous

control cases are simulated with two different power reference signals to the BESS converter.

1st Case: Power reference to the BESS converter is difference between current load power

and non-causal average load power, see equation (4.1)

, = (4.1)

where is calculated by non-causal moving average filter (4.2) from the total power re-

quirement.

( ) =1

[ ( 99) + + ( + 100)](4.2)

24

Of course, it is not possible to use future values of power consumption in an actual vessel.

However cruise ferry is operating on the same route every day. In this case it could be pos-

sible to use power demand estimator to calculate power demand ahead based on the vessel’s

position, speed limits, weather conditions, captain’s decisions, etc.

2nd Case: BESS converter power reference is calculated as a difference between the current

load power and the load power from the last 400 s, see equation (4.3).

, = (4.3)

This means that BESS is used to level sudden load fluctuations, but if the load power stays

on that level the BESS power reference approaches zero. Diesel gensets then produce the

power required by the load.

Third investigated case is running diesel gensets in their optimal fuel economy point. BESS

makes it possible to run gensets only on their optimal point as the battery energy storage

maintains grid frequency and power balance. This case is a modification of the isochronous

case. Genset control is similar to the isochronous case, only constant is given to gensets.

Simulation results indicate that BESS can be used to balance marine vessel PDS. Time con-

stant of a battery is much faster than time constant of a diesel engine. This helps when trying

to keep the grid frequency constant as the load changes rapidly. The difference between the

two isochronous cases is the power reference to the BESS converter. In the 1st case it is

calculated from the difference between the current load power and the load power estimate,

which takes future values into account. In the 2nd case the BESS converter power reference

is calculated from the difference between current load power and averaged load power from

the last 400 s. The 1st case causes the gensets to increase power by charging the BESS just

before load power demand increases. When the load power demand actually rises, BESS

changes from charging to discharging. The time constant of the BESS is fast compared to

the time constant of the gensets. This keeps the network frequency more stable. In the 2nd

case, when a load spike occurs, the BESS reacts to this, but if the spike is high enough and

the nominal power of the BESS is not enough to cover this power demand, frequency starts

25

to drop and due to the long time constant of gensets it takes to time to respond to this power

demand. The 1st isochronous case makes better use of the short time constant of the BESS.

BESS can be used to increase fuel efficiency by allowing the gensets to run on high fuel

efficiency region. In this case BESS is handling the grid frequency control by sinking or

sourcing power. This control method is prone to BESS converter fault. Fault situation was

simulated where BESS converter fails, and gensets go to normal isochronous operation. The

dynamic behavior of this size cruise ferry is limited. The load in the case of this vessel is quite

static. Also, the massive rotational inertia in the gensets helps as an energy storage.

4.5. OSVModel of the OSV is simulated running gensets in isochronous control mode. Input data to

the model is dynamic positioning power data recorded from the generators of the actual case

vessel. Simulations are done using one and two gensets without BESS and using different

isochronous control parameters. In the second case BESS is added, and the model is simu-

lated while running one genset and BESS. BESS is controlled by running it in isochronous

control mode, as it would be a diesel genset. Other used method is average power estimate.

The average consumed power over a period of time is estimated and the difference between

current consumed power and this estimate is fed to the BESS as a power reference signal.

Simulation results of these cases are presented below in the Figures 8 and 9.

Simulation results suggest that OSV can shut down one genset while in dynamic positioning

(DP) mode and use BESS to compensate load fluctuation. Load power in dynamic position-

ing mode is not high, but it contains fast changes. In our data, load was between 400 kW and

700 kW, with some spikes up to 1100 kW. Although only genset could produce the needed

power, it cannot respond to the rapid load changes causing frequency fluctuation in the AC-

grid. BESS can be used to level the load fluctuation while the diesel genset produces the

required base load. This also improves fuel efficiency in the DP-mode because the genset

can operate on a higher load (and higher efficiency) area.

26

1st Case: OSV is using 1 and 2 generators, no BESS is added to the system (Figure 8).

Figure 8. Generator speed (network frequency) on the left and generator torque on the right while running

the OSV model without BESS using 1 and 2 generators.

2nd Case: OSV is using one genset and BESS is used to level load fluctuation (Figure 9).

Figure 9. Generator speed (network frequency) on the left and generator and BESS power on the right

while running the model using only one genset and BESS.

Spee

d[p

.u.]

Torq

ue[p

.u.]

Spee

d[p

.u.]

Powe

r[p.

u.]

27

5. WP 4 – REMOTE VESSEL DATA MANAGEMENTIn WP4 the target was to study the IOT applications and communication protocols in ves-

sels. As a separate task also the communication based link between the laboratories between

LUT and Vaasa was supposed to be investigated.

At the beginning the system platform provided by CLS Engineering was tested at the Uni-

versity of Vaasa. The core of the system is COSMOSX10 unit which is capable of collecting

data and handling the communication to cloud where the data is then stored. The COS-

MOSX10 is based on Beaglebone Black with Linux operating system. In the tested system

the connection to cloud was established with 4G modem and measurement of analog and

digital signals was successfully demonstrated. The platform supports wide variety of proto-

cols but at the time of the tests there was not yet IEC-61850 support available so data from

power grid automation system cannot be collected.

As an interesting option the possibility to extend the processing power of the data collection

platform by using a separate FPGA board for processing the measured data was developed

at conceptual level with only some tests of the available interfaces. In this kind of system

certain features can be extracted from data and then only limited amount of data is necessary

to transfer over the communication link.

The FPGA is claimed to have better energy efficiency when considering tasks requiring more

computing power. Relating to this aspect a detailed study was also made where the power

consumption of the FPGA circuit was analysed. The focus was on analysis methods and the

main outcome wss that the software based power analyser is still rather inaccurate.

Considering the IoT platform it was realized during the project that there is no specific needs

for further development of the existing platform. On the other hand, processing the data for

some specific purpose in the context of the project would provide some novelty. Therefore

the potential applications were tried to find in the discussions with project partners. As a

conclusion the optimization of the engine load turned out to be the most interesting appli-

cation, but due to the lack of time and resources only brief background survey was made.

The basic idea is that by controlling the battery output in a suitable way the peaks of the

engine load can be reduced. Possibly some optimization method can be used which utilizes

28

e.g. weather data. There exist also various advanced methods for fuel consumption estima-

tion that can also be utilized. Developing this kind of solution would be suitable topic for

some next projects.

Due to the delays in commissioning of the engine laboratory at the University of Vaasa the

remote connection between the laboratories was not possible to accomplish during this pro-

ject. Instead of that a brief analysis of potential ways to make the connection was made. At

the top level the remote connection to the automation system is possible. On the other hand,

direct transfer of some specific measurement quantity could be more practical depending on

the operating scenario. Some further research will needed to plan the actual implementation.

29

6. WP 5 – DEMONSTRATION SYSTEM DEVELOPMENT AND

TESTINGIn the 5rd work package (WP5), a hybrid vessel power train emulator was constructed. The

purpose of the laboratory setup is to give answers to two different research question classes.

The first class deals with the vessel hybrid power train development. The second class is

more general. It deals with questions of hardware-in-loop (HIL) simulations where loads and

prime movers are replaced by electric motor drives or by power electronics alone. In addi-

tion, the laboratory setup aims to form a concept to be used in conjunction with Vaasa En-

ergy Labs later on.

In the research of the power train development, the purpose of the laboratory setup is A) to

verify simulation models, B) to test energy balancing and control of vessel hybrid power train

when battery energy storage is used, and C) to test different normal operation modes and

fault cases.

In the research of the HIL simulation, the research concentrates in finding the benefits, lim-

itations and dynamic performance of hardware-in-loop simulation. In normal simulations,

made without HIL, there exists no limitations of presenting dynamics of mechanical loads.

In mechanical level HIL setup, the dynamics of load emulator and the drive under study

(DUT), in this case e.g. propulsion drive, form a dynamic system that inevitably differs from

actual drive by nature. The dynamics of HIL setup is affected both by the DUT drive and

by the load emulator drive. In order to achieve similar dynamics between HIL and actual

drive at control bandwidth, the performance and stability issues have to be carefully consid-

ered. Further, it is required that different controller tuning of load emulator drive has to be

used for different DUT controller parameters. The research is used to give guidelines for

dimensioning and for controller tuning of such HIL setups.

The laboratory level demonstration systems offers tools to verify the simulation results and

to understand model uncertainties and technical challenges, which a real marine hybrid sys-

tem will include. From scientific point of view, laboratory analysis of simulation results are

essential to be able to produce high level scientific articles about the studies generated in the

earlier work packages. The laboratory test will include following subtasks:

30

• Laboratory analysis and testing of different operational modes

• Comparison of laboratory tests and simulation results, model improvements

• Evaluation of dynamic performance and accuracy of emulator

6.1. AC network emulator hardware and communication structureThe emulator consists of diesel emulator (800 kW induction motor) connected to synchro-

nous generator (800 kVA), a LLC-type (Wärtsilä Low Loss Concept) AC-network, battery

energy storage system, propulsion emulator, and multi-purpose emulator (4Q inverter) that

is used as the second genset and propulsion emulator. Rotating propulsion emulator com-

promises of 110 kW induction motor and propulsion load emulator (315 kW induction gen-

erator). Main components are presented in schema of Fig. 10 and in Fig. 11.

Figure 10. A laboratory setup for testing a power train of a future hybrid vessel. The main components in

addition to network itself are a genset emulator unit *C1, a propulsion emulator *C2 , a multi-purpose

emulator *C3 and a battery energy storage.

SG

AMACS850

ACS880

DCS880

200 kW

AM 800 kW

800 kVA

400 V

n. 200 kVA

AM

AM

315 kW@3000 RPM

12p

110 kW@1500 RPM

PROPULSIONEMULATOR

GENSETEMULATOR

BATTERY ENERGYSTORAGE135 kWh, 180 kVA

*C1 *C2

4Q(AFE/GRID)

*C3 *C4

PLC

PLC

Mainsconnection

Mainsconnection

31

Figure 11. Devices, software and communication media of the AC-network hybrid power drive emulator.

The main controller of the emulator setup is an industrial PC. The propulsion emulator and

the battery energy storage have their own programmable controllers so that they can execute,

if so set, their own emulator algorithms in a distributed manner but all the emulations can be

calculated in main controller also. The distributed emulations are required only if very fast

dynamics is emulated. At the moment, all emulations are executed in main controller, which

limits the control cycle of load emulator to 1-2 milliseconds and of battery energy storage

control to 100 milliseconds. The emulations can be implemented by programs made using

C- or IEC61131-3 languages. In addition, Simulink models can be used when compiled using

PLC coder from Mathworks inc. or using Bechoff TwinCat 3 Matlab/Simulink interface.

The latter option enables one to visualize simulations in real-time. The emulation results can

be graphically displayed in real time and recorded with 1 millisecond time resolution.

32

6.2. DC network emulator hardware and communication structure

The DC network emulator is smaller scale emulator than AC network emulator, but more

complex. The DC network emulator consists of two diesel genset emulators. In the first

emulator a 55-kW induction motor is used as diesel emulator. This motor is connected to

synchronous generator (110 kVA) feeding the DC network via diode rectifier. Another,

multi-purpose emulator can be used as a diesel genset and propulsion emulator. It consists

of two back-to-back connected 5.5-kW induction machines. One machine is connected to

mains via 4Q-inverter setup so that it can be used as a load (generator) as well as a motor.

Similar 4-kW setup is as a main propeller load emulator. The setup does not include actual

battery energy storage but, instead, uses a grid inverter to emulate battery. Battery character-

istics can be programmed as emulator code in the main controller or battery energy storage

of AC-setup can be used in parallel with the emulator when battery energy storage is con-

nected with mains instead of vessel network. In this case, emulator code calculates scaling

between voltages and currents of actual BESS and emulated one. This way the battery em-

ulator can emulate both controlled BESS or BESS that is directly connected to DC vessel

network. It is worth mentioning that emulation is not restricted to battery storage but other

storages, such as super capacitor storages can be emulated as well. The DC- and AC-network

emulators share same main controller, DAQ and supervisory control (See Fig. 12).

Figure 12. Hardware and software components of the DC-network hybrid power drive emulator.

33

6.3. Real time simulators

The emulation setups (AC and DC) include various real time simulators. Some are pure sim-

ulators and others emulate diesel, propulsion or BESS as a part of mechanical-level hardware-

in-the-loop (MHIL) emulations.

Marine vessels include several diesel gensets as well as several propeller drives, usually of

different sizes. The simulation model of whole vessel as presented in Chapter 4 Fig. 3 can be

simulated in real time when simplified enough. This enables one to emulate individual genset

or BESS as a part of system while other part of the system is purely simulated. However, one

back-to-back drive can emulate several gensets or propeller drives so that whole power train

can be emulated independent of the number of actual devices in vessel.

The basic version of emulation procedure is the following. The sum of propeller load (power)

time series is read from input file. The real time simulator calculates torque and rotational

speed and give these values as refrences to propeller emulator. System measures voltage and

frequency of network and using e.g. droop or isochronous control share torque, rotational

speed or power references to diesel emulator(s) and battery energy storage.

34

7. LIST OF REPORTS AND PUBLICATIONS

During the project the results were disseminated by public reports and papers listed in the

following:

LUT:

Lana A., Lahtinen, J., Peltoniemi, P., Pinomaa, A., Montonen, H., Lindh, T., Pyr-

hönen, O., “Efficiency improvements in future hybrid cruise ferries,” Electric & Hy-

brid Marine World Expo 2017 Conference, 6-8th June 2017, Amsterdam, Netherlands

Pinomaa, A., Lana, A., Peltoniemi, P., Lahtinen, J., Montonen, H., Lindh, T., Pyr-

hönen, O., Life cycle analysis for hybrid marine technology – Case: Cruise ferry, Public report

of FESSMI project WP1, Lappeenranta University of Technology.

Pyrhönen, O., Lana, A., Lahtinen, J., Peltoniemi, P., Pinomaa, A., Montonen, H.,

Lindh, T., “Batteries for energy efficiency improvements in hybrid vessels,” Laivako-

neistoklubin asiantuntijaseminaari, Energiansäästö laivakoneistoissa, 22nd – 23rd Nov. 2017,

Turku. Suomi.

UVA:

Kumar J., Palizban O., Kauhaniemi K., "Designing and analysis of innovative solu-

tions for harbour area smart grid," 2017 IEEE Manchester PowerTech, Manchester, UK,

2017, DOI: 10.1109/PTC.2017.7980870

Kumar J., Kumpulainen L., Kauhaniemi K., “Technical Design Aspects of Harbour

Area Grid for Shore to Ship Power: State of the Art and Future Solutions”, Submit-

ted 28th Sept. 2017 to International Journal of Electrical Power and Energy Systems (under

review)

Palizban O., Kauhaniemi K., Energy Storage Systems in Maritime Grids: Hierarchical Con-

trol, Power Management and Energy Balancing, FESSMI project WP2 report (unpublished,

originally an extended abstract submitted to an journal), University of Vaasa

35

Al-Hakeem H., Stenman E., “Comparing Intel’s PowerPlay’s Estimations to Meas-

ured Power on a Cyclone IV FPGA”, Au-22: Automaatiopäivät22, Vaasa, Finland,

March 23-24, 2017

Rajkumar N., Remote Connection between Laboratories, FESSMI project WP4 re-

port (unpublished literature survey), University of Vaasa

Al-Hakeem H., On the estimation of fuel consumption in ships: Literature review,

FESSMI project WP4 presentation, University of Vaasa

At the end of the project the following reports and papers are yet to be finalized and pub-

lished then later on in appropriate forums:

LUT

Pinomaa, A., Lana, A., Peltoniemi, P., Lahtinen, J., Montonen, H., Lindh, T., Pyr-

hönen, O., Life cycle analysis for hybrid marine technology – Case: OSV, Public report of

FESSMI project WP1, Lappeenranta University of Technology.

Lana, A., et al., “Dimensioning, benefits and LCA of the battery energy storage sys-

tem in different marine segments – Case studies,” (Scientific journal paper to be de-

veloped from FESSMI project WP1 vessel case studies)

Lindh, T., et al., “Vessel emulator concept for verification of hybrid vessel simulation

models,” (Scientific journal paper to be developed from WP5 laboratory emulator)

Montonen, H., et al., “Dynamic controlling method for power balancing in hybrid

marine vessels,” (Scientific journal paper to be developed from FESSMI project WP3

vessel case simulations)

Lana, A., et al., “Hybrid marine vessel data-based fuel efficiency optimization,” (Sci-

entific journal paper to be developed from FESSMI project WP1 vessel case studies)

Lana, A., et al., “Comparison of DC & AC topologies in marine vessels,” (Scientific

journal paper to be developed from FESSMI project WP3 vessel case simulations)

36

UVA

Kumar J., Memon A., Kumpulainen L., Kauhaniemi K., Single Line Diagram of Harbour

Area Smart Grid and Alternative Charging Systems of Batteries for Hybrid and Electric Vessels,

FESSMI project WP2 Report (unpublished), University of Vaasa

Kumar J., Memon A.A., Kumpulainen L., Kauhaniemi K., “Designing and analysis

of innovative solutions of charging scenarios for modern vessels at harbours”, (sci-

entific journal paper to be developed from the above FESSMI project WP2 report)

Memon A.A., Kauhaniemi K., Protection Strategies for Harbor Area AC Microgrid with

Battery Energy Storage Systems for Future Marine Installations, FESSMI project WP2 report

(unpublished), University of Vaasa

Memon A.A., Kauhaniemi K., “Adaptive overcurrent protection for harbour area

AC Microgrid with Renewable DGs and Battery Energy Storage Systems for Future

Marine installations”, (scientific journal paper to be developed from the above

FESSMI project WP2 report)