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Use Case: KIT/BESS optimization for production process

Description Of The Use Case

Name of use case

*Use case identification*
ID	*System configuration(s)*	*Name of use case*
UC7	TBD	Optimization of Battery Electric Storage Systems (BESS) for production processes

Version management

*Version management*
*Version No.*	*Date*	*Author(s)*	*Changes*	*Approval status*
1.0	10/07/2017	T. Blank	First version	Draft

Scope and objectives of use case

*Scope and objectives of use case*
*Scope*	[Why? Motivation and high-level objectives] Industrial production processes rely on a predictive and stable energy supply. Setting up production processes on volatile renewable energy is a challenge, which is seldom stressed to the limits of 100% renewable energy. As most production processes currently are not compatible to a volatile energy supply, lithium-ion battery storage systems can be used to mitigate the effects of the energy fluctuation on the production processes. Thus, there is a high common interest in optimizing the electric energy supply by adding huge storage systems to renewable energy sources. [What? System under discussion, main functions, main actors] The use case “Optimization of Battery Electric Storage Systems (BESS) for production processes“ considers processes to manufacture electronic and hybrid electronic systems. The processes are meant to be powered by electrical energy from solar panels (or generators operated with a solar profile) and from medium sized lithium-ion batteries up to a capacity of 70 kWh. The stakeholders are the shop floor personal running the production as well as the management, setting the aims for the short and long term production. Multiple smart meters and sensors are monitoring the machinery, processes and the stored and generated energy. The data is aggregated and centrally evaluated by a PC, which controls the overall processes.
*Objective(s)*	O1: Identification of the optimization parameters of Li-Ion storage systems for a given electronic production plant (according to system configuration SC1-IPE), a given battery and production process O2: Understanding the communication and power controller infrastructure needs for the integration of real-time controllable BESS in production plants according to SC1-IPE
*Belongs to use case group (if applicable)*	Electrical Energy Storage

Narrative of use case

*Narrative of use case*
*Short description*
To aim to optimize lithium-ion battery storage systems for industrial production processes is based on controller technology, which can modify production and battery charging schedule. The optimization is based on the data of the generated regenerative power, the stored energy and the current energy profile of the production. By means of use case KIT-UC7 various parameters can be adopted to modify, investigate and improve the power flow between the production processes (load) and the power generation and storage devices. Next to detailed information on the load, the properties of the storage system as well as weather and generator data have to be accurately gathered, evaluated and controlled.
*Complete description*
Electrical systems with a large amount of renewable energy are subject to fluctuations in energy generation on multiple time scales. Production plants and processes, however, are significantly depending on a stable and predictable power supply. Short-term instabilities from seconds to hours can be buffered by lithium-ion battery systems as well as production schemes adoptable to the available energy. The system configuration SC1-IPE will be used to understand the power needs of the electronic production plant and its various processes. The purpose of the use case KIT_IPE 7 are on the one hand to derive optimization criteria for the BESS and on the other hand to develop operational strategies for the production under limited power generation and storage capacities. Hence, the production processes will have to be classified into various groups like long or short running processes, high or low energy processes, high and low power processes, harmlessly interruptible processes, urgent processes (due to customer request or other strategic issues). Based on the classification, control algorithms and adaptive cost functions will be derived to optimize the production flow and processes. All data of the production machinery and the overall power consumption of the production plant is centrally collected by a data base system. The smart meters transfer the power data via a ModBus link to a custom PC. The PC runs a LabView program transforming the data in the appropriate data base format and sends it via a TCP/IP link to the database. The production processes aim for a hybrid thick-film power module and include high temperature sintering processes to manufacture copper thick-film substrates, pick’n place and low temperature silver sinter die attach processes, thick aluminum wire bonding as well as soldering and automatic optical inspection processes. The control algorithms to optimize the plant operation uses data of the generated power (solar plant/profile), the power consumption data of the machinery and processes, battery data like power, capacity and stored energy, weather forcast data. By optimizing the plant operation, the optimal BESS topology with respect to storage capacity and power will be derived. Additionally, technologies to control the power flow between the generator, the BESS and the production assets can be validated and optimized. Thus, the plant and the processes will be operational under real-time power distribution.
Network Layout The readout is integrated into the network via dedicated routers. They are providing the port forwarding to the smart-meters and easily split the all infrastructure in separate branches.
Hardware Each smart meter bank consist of EEM-MA600 energy meter from Phoenix Contact and current transformers
Data Logging The data logging organized in a MS-SQL platform as an autoexecutable application in the separate account. The application program has three main branches: A data readout from each smart meters using ModbusTCP interface A queue-based writing data with corresponding time-stamps into the data base stack Storing all data from the stack using dot net technology. This technic provides a lossless, reliable collecting of data. Stored database is replicated in a public database server, which is connected with the “ADEI” (Advanced Data Extraction Infrastructure) software tool (programmed by IPE). ADEI is used in numerous experiments allowing many terminals to have a full overview of multi-channel data within different time frames. The system is running in full automatic logging mode, needs neither control nor GUI. In case of network or power black outs the system is recovering itself.

Optimality Criteria

*Optimality Criteria*
ID	*Name*	*Description*	*Reference to mentioned use case objectives*
OC1	Optimal power profile of battery	Optimize the battery system to provide the required power for the production process	O1
OC2	Optimal capacity of battery	Optimize the BESS to provide the required energy for the selected production process	O1
OC3	Optimal plant operation and layout	Critical processes must be terminable without corrupting the products	O1, O2

Use case conditions

Use case conditions

Assumptions

[Assumption; assumed relation to other systems: e.g. higher level controller sends a signal]

Data of the machinery, the processes, the battery and the generation are available in real time
Accurate weather forecast is available
Data base is running and accessible in real-time
Control devices are installed and accessible

Prerequisites

General remarks

*General remarks*

Graphical RepresentationS Of Use Case

Graphical representation(s) of use case

Examples of typical diagram types associated with use cases:

Technical Details

Actors

*Actors*
*Grouping*		*Group description*
KIT-ACT-Generators		Groups all power generating devices
KIT-ACT-BESS		Groups all lithium-ion storage systems
KIT-ACT-Machinery		Groups all production machines
KIT-ACT-Other		Groups other actors
KIT-ACT-Operators		Groups the operators performing the production processes
*Actor name*	*Actor type*	*Actor description*	*Further information specific to this use case*
Li-Bess1 14 kWh	Energy storage	LiTec, 96S1P, 40Ah
Li-Bess2 19 kWh	Energy storage	Litarion, 120S1P, 45Ah
Li-Bess3 19 kWh	Energy storage	Litarion, 120S1P, 45Ah
Solar Plant/Generator	Energy generation	Tbd.
Grid Supply	Energy generation	3x400V, 400 A
AOI S2088-II	Machinery/Process	Automatic optical inspection
EVO 2200	Machinery/Process	Flip-chip die bonder
Paraquda 4	Machinery/Process	SMD pick and place machine
MP50_1_VK	Machinery/Process	Heated PCB lamination press
PEO 604	Machinery/Process	High temperature sinter oven
SMT XXS	Machinery/Process	Reflow soldering oven
Inverter/Charger	Energy Flow Control Device	Tbd.
SMD Operator	Human
Hybrid Operator	Human
Weather forcast	Data generation	Data aggregator extracting radiation data from weather forcast data

Step By Step Analysis Of Use Case Optional

Overview of use case scenarios

*Scenario conditions*
*No.*	*Scenario name*	*Scenario description*	*Primary actor*	*Triggering event*	*Pre-condition*	*Post-condition*
Scen1	High Power Generation	Production is running fully, the solar panel deliver high power	Hybrid process operator SMD process operator	Start of production (SoP)	Battery fully charged	Production completely finished
Scen2	Low Power Generation	Production is running fully, the solar panel deliver low power	Hybrid process operator SMD process operator	Start of production (SoP)	Battery fully charged	Production completely finished
Scen3	Low Power Generation	Production is running fully, the solar panel deliver low power	Hybrid process operator SMD process operator	Start of production (SoP)	Battery partly charged	Production partly finished

Steps – Scenarios

*Scenario*
*Scenario name :*		Scen1
*Step No.*	*Event*	*Name of process/ activity*	*Description of process/ activity*	*Service*	*Information producer (actor)*	*Information receiver (actor)*	*Information exchanged (IDs)*	*Requirements R-ID*
1	SoP	Start of production	All assembly processes sequentially started		All actors	All actors except Grid supply and weather forcast
2	EoP	End of Production	Assembly process successfully finished		All actors	All actors except Grid supply and weather forcast

*Scenario*
*Scenario name :*		Scen2
*Step No.*	*Event*	*Name of process/ activity*	*Description of process/ activity*	*Service*	*Information producer (actor)*	*Information receiver (actor)*	*Information exchanged (IDs)*	*Requirements R-ID*
1	SoP	Start of production	All assembly processes sequentially started		All actors	All actors except Grid supply and weather forcast
2	EoP	End of Production	Assembly process successfully finished		All actors	All actors except Grid supply and weather forcast

*Scenario*
*Scenario name :*		Scen3
*Step No.*	*Event*	*Name of process/ activity*	*Description of process/ activity*	*Service*	*Information producer (actor)*	*Information receiver (actor)*	*Information exchanged (IDs)*	*Requirements R-ID*
1	SoP	Start of production	All assembly processes sequentially started		All actors	All actors except Grid supply and weather forcast
2	EoP	End of Production	Assembly process successfully finished		All actors	All actors except Grid supply and weather forcast