Literature Review: DC Nano grid

This literature review is for the ongoing research on the DC Nano grid which is a possible approach toward achieving electrification in certain areas where grid connectivity is still unavailable. It can generate and distribute power to a cluster of households in close proximity reliably.

This literature review is in support of the following article:

• S. Khan and Md. M. Rahman, "Design and Simulation of Solar DC Nano Grid System from Bangladesh Perspective," in 2021 International Conference on Automation, Control and Mechatronics for Industry 4.0 (ACMI), Jul. 2021, pp. 1–6. doi: 10.1109/ACMI53878.2021.9528159.

Literature Review of Selected Literatures on DC Nano grid:

Sizing of PV array in a DC nano-grid for isolated households after alteration in time of consumption^[1]

Summary:

P. Muthuvel, S. Arul Daniel, and S. K. Paul proposed two approaches in 2017 for sizing the PV array in DC Nano grid.  

• The first method is a simple approach, which directly obtains the size of PV panels based on highest monthly consumption in the year, irradiation and ambient temperature.
• The second method is analytical approach suitable for experts which uses particle swarm optimization (PSO) technique. It is based on detail cost equation with all design variables.
• The size of PV array was determined considering appropriate time shifting of loads.

Results:

• This paper concluded that that alternation of time of consumption of various load profile has resulted in reduced size of PV array as well as the cost of battery storage system significantly
• Again, in case of DC Nano grid design in a rural area, it is adequate to use the simple intuitive method for sizing the PV array.

Bus voltage level choice for standalone residential DC nanogrid^[2]

Summary:

In 2019, S. Moussa, M. J.-B. Ghorbal, and I. Slama-Belkhodja presented a guideline in order to choose appropriate voltage level for standalone residential DC Nano grid to ensure user safely, efficiency and cost saving.

• They have considered power consumption, area of application deployment, cable size and transmission losses as elements to find the suitable bus voltage of DC Nano grid.
• Also, in this paper they have compared results between five suitable voltage levels for DC Nano grid (12V, 24V, 48V, 60V and 100V DC).

Results:

• Most commercialized DC load generally run on 12 or 24V and some on 48V.Hence use of higher voltage level is not suitable as they will require step down converter as interface between bus and the load.
• Using voltage less than 15V is safe for user and for voltage level ranging for 15 to 100V, protection must be implemented only if the power is greater than 1000W only. So in this paper voltage level ranging from 12V to 100V is considered as it requires basic protection.
• 12V DC presents worst performance in terms of voltage drop, power loss and maximum allowed cable length while 100V DC presents the best. The performance increases with the increase of DC voltage level bus except 60V which presents a poorer performance than 48V DC.
• Finally taking the into consideration the cost and performance, they concluded that 48V voltage level is the best choice for their case of study.

A testbed for experimental validation of a low-voltage DC nanogrid for buildings^[3]

Summary:

In 2012, I. Cvetkovic et al presented the testbed for DC Nano grid for its system-level operation analysis with initial experimental results and conclusion.

Testbed Specification:

The testbed comprises 5kW Suntech's Solar Panels, 3.5kW Clean Field Energy's vertical axis wind turbine and 45Ah Saft's Li-ion battery bank, interface to grid (10kW) and Plug in to hybrid vehicle (5kW).

• Total Sourcing Capability of Nano grid is 33.5kW
• Assuming, Source coincidence factor n_SC=80%
• Load Co incidence factor n_LC=50%
• Peak Load Power=13.4kW ≈15kW
• Maximum current for Given Peak Load= 40A
• Bus wire gauge corresponding to current value is AWG 8 (8.37mm²)
• Maximum Voltage drop 7.2 V
• And Maximum Length of bus is 24m.

Converter Specification:

a. The grid interface converter –Energy control center (ECC)

• Two stage, single phase PWM converter.
• Comprises three phase legs: two are used in H bridge configuration to interface with the grid and third one is used as a bidirectional synchronous rectifier dc-dc converter.

b. The battery interface converter:

• The 10kW three phase interleaved, bidirectional buck/boost converter.
• The single, two switch buck/boost converter suffers from relatively large switch turn on, turn off and diode reverse recovery losses. Almost 22% of savings in the total loss can be achieved by three phase interleaved, bidirectional buck/boost converter.
• three phase interleaved, bidirectional buck/boost converter has three times higher frequency compared to single.

c. The PV inverter converter:

• The PV interface converter is a 5kW three phase interleaved boost converter of the same topology as the battery interface converter.
• It features two independent control. One is MPPT loop and another is low bandwidth droop control loop.

System level Tests:

1. First test is with a grid and a battery interface converter connected on the bus and loaded with a 1.8kW resistive load.
2. Second one is battery shut down test.

Control Scheme for a Bidirectional Converter in a Self-Sustaining Low-Voltage DC Nanogrid^[4]

Summary:

In 2015, S. I. Ganesan, D. Pattabiraman, R. K. Govindarajan, M. Rajan, and C. Nagamani proposed the control algorithm for the Energy Management System (EMS) to provide uninterrupted power supply to the DC loads and achieve self – sufficiency by minimizing grid power consumption.

• They have developed a control scheme for a cascaded two stage bidirectional converter interface between the Nano grid and the AC distribution network. The topology they have used is a bidirectional DC-DC converter followed by a three phase inverter. As bidirectional DC-DC converter, Dual Active Bridge (DAB) converter is used which consist of voltage source inverters on either side of a HF transformer.
• An empirical relation for the power flow through converter.
• And optimal link voltage ranges to achieve power transfer between rated limits.

Operation:

• To control the power flow through DAB converter, a simple open loop control is used, by appropriately choosing the capacitor DC link voltage, inherent power flow control between rated limit was achieved. It overcomes circulating current and switching issues without using complex circuit.
• The three phase inverter uses double loop control to regulate the DC capacitor link voltage at the reference value, thereby facilitating power exchange with AC grid.
• The bidirectional converter operates in three modes namely power surplus mode, power deficit mode and idle mode and transition between different modes were achieved based on four level control scheme based on battery voltage.

Result:

• The proposed scheme was compared with existing two mode control method/Power management method and two band control method.
• The proposed system operates idle mode for 17.4 hours while an idle operating for two band control method is 4.1 hour which ensures no power was transferred through DAB during idle mode.
• For a single day the proposed scheme is consumed only 1.83kWhr on the other hand power management control method consumed 2.87kWhr and two mode operation consumed 4.26kWhr.

Model of a hybrid distributed generation system for a DC nano-grid^[5]

Summary:

In 2016, E. Hamatwi, I. E. Davidson, J. Agee, and G. Venayagamoorthy designed, simulated and optimized for a hybrid DC Nano grid, with storage and a backup diesel generator for Umzinyathi district of South Africa.

• Based on simulation using HOMER, the optimal system comprises of a 100kW PV array, thirteen 7.5kW wind turbine, 20kW diesel generator and 96 Trojan T-105 deep cycle batteries.
• The area is estimated to have 80 houses and 15shops. The maximum power consumption for the household and shops is 6.79kWh/day/household and 4.85kWh/day/shop respectively. And total 615.95 kWh/Day power consumed by the DC Nano grid.

Result:

• The net present Cost (NPC) of the system is $459,545, Cost of Energy $0.248/kWh and Payback period of the optimal system obtained is 4 years.
• The PV array, wind turbines and diesel generator generated 50%, 21% and 29% of the total energy respectively where system's renewable fraction is 71%.

DC nanogrids: A low cost PV based solution for livelihood enhancement for rural Bangladesh^[6]

Summary:

In 2014, M. R. Khan and E. D. Brown proposed alternative to diesel based irrigation system in perspective of Bangladesh.

• The solar PV based irrigation system is integrated with DC Nano grid/Rural grid to maximum utilization of the PV power.
• The proposed Nano grid uses battery only to backup for supply of energy during the nigh hours, irrigation can be done during the day time without battery backup.
• The proposed Nano grid system consist of 1.1kW pump with 10 households in cluster. 1.9kW PV system was installed with 500Ah, 12V battery as storage.
• The 1.1kW (1.5HP) irrigation pump with 50% efficiency can run satisfactorily driven by an inverter can pump 90,000 liter of water per day (4hour run time), which can irrigate 67acre of rice field for a whole season.

Feasibility analysis of solar DC Nano grid for off grid rural Bangladesh^[7]

Summary:

In 2015, M. M. H. Sajeeb, A. Rahman, and S. Arif discussed about Nano grid and surveyed an installed DC Nano grid in Kushtia district of Bangladesh.

• The grid was set up to houses clustered in 300m long and 100m wide land.
• The distribution network served 20 households each containing 12V DC fan, light and TV
• 16 batteries of 12V volt 130Ah are used.  The panels used are of 250Wp, 24 volts. The Nano consists of a backup diesel generator.

Review of Control Strategies for DC Nano-Grid^[8]

Summary:

In 2022, H. Fan, W. Yu, and S. Xia have investigated on differnt control technologies for the DC Nano grid from two aspects: local control and coordinated control.

Local Control: Local control is mainly used for voltage/current control, source side control e.g. output power control of RESs and local power sharing. It has shortest response time. In this paper they have mainly discussed about the following control methods:

1. Current/ Voltage control.
2. Maximum power point tracking control.
3. Active load sharing.
4. Passive load sharing.

Coordinated Control: Coordinate control collects the electrical information of each component, enhance the performance of power sharing and switch operating modes. The following methods have been discussed:

1. Centralized Control
2. Decentralized Control
3. Distributed Control
4. Hybrid control (Centralized/ Distributed)

Result:

• The local control realizes the voltage/ current control method and primary power sharing of the units.
•  Droop control has been widely used in local control due to its precise current sharing and excellent voltage regulation abilities.
• ·On the other hand, coordinated control can be used to further improve the accuracies of power sharing and power quality of the grid system.
• The distributed control scheme and communication strategy should be further studied with multi agent based AI algorithms so that these control strategies can operate DCNG stably in all kind of operation mode.

Proposed smart DC nano-grid for green buildings — A reflective view^[9]

Summary:

In 2014, M. H. Shwehdi and S. R. Mohamed proposed a DC Nano grid for smart home which composed of smart loads and home area network with a smart meter. Their proposed green building has the following characteristics:

1. Smart meter, smart load and power flow will be managed by some wireless nodes.
2. There will be coordination between smart loads and smart meter to monitor the power flow, which will be achieved by algorithms.
3. Total load of the building will be managed in such a way that the algorithm can manage the loads in the peak hours.

Conclusion:

1. ZigBee wireless technology will be used for communication of smart meter in DC smart homes. ZigBee is designed for high radio frequency applications which has low data rate, long battery life and secure networking.
2. Standers for DC power distribution is being developed by E-Merge Alliance.
3. Though the proposed DC house is not a direct alternative to AC house but it can bring energy independence with security.

Optimal Integration of a Hybrid Solar-Battery Power Source into Smart Home Nanogrid with Plug-In Electric Vehicle^[10]

In 2017, X. Wu, X. Hu, Y. Teng, S. Qian, and R. Cheng developed an framework for efficient energy management and components sizing of a single smart home with home battery, plug-in vehicle and photovoltaic (PV) arrays.

• The plug-in vehicle system battery allows bidirectional and unidirectional power flow.
• The smart home management system controls power flow between PEV battery, home appliances, PV arrays, home battery, and the utility grid.
• Convex programming (CP) is used for optimal energy management.

Result

• The proposed CP method can effectively solve the optimization problem,
• The total cost in V2H (Vehicle to home/ Bidirectional) mode is 2.6 % lower than that in H2V (Home to vehicle) mode

References: