scholarly journals Nanogrid topology, control and interactions in a microgrid structure

2021 ◽  
Author(s):  
◽  
Daniel Burmester

<p>Distributed generation, in the form of small-scale photovoltaic installations, have the potential to reduce carbon emissions created by, and alleviate issues associated with, centralised power generation. However, the major obstacle preventing the widespread integration of small-scale photovoltaic installations, at a residential level, is intermittency. This thesis addresses intermittency at a household/small community level, through the use of "nanogrids". To date, ambiguity has surrounded the nanogrid as a power structure, which is resolved in this thesis through the derivation of concise nanogrid definition. The nanogrid, a power distribution system for a single house/small building, is then used to implement demand side management within a household. This is achieved through the use of a hybrid central control topology, with a centralised coordinating controller and decentralised control nodes that have the ability to sense and modulate power flow. The maximum power point tracker is used to observe the available photovoltaic power, and thermostatically controlled loads present in the household are manipulated to increase the correlation between power production and consumption. An algorithm is presented which considers the expected power consumption of the thermostatically controlled loads over a 24 hour period, to create a hierarchical ratio. This ratio determines the percentage of available photovoltaic power each load receives, ensuring the loads that are expected to consume the most power are serviced with the largest ratio of photovoltaic power. The control system is simulated with a variety of household consumption curves (altered for summer/winter conditions), and a week of realistic solar irradiance data for both summer and winter. In each simulated scenario, a comparison was made between controlled and uncontrolled households to ascertain the extent grid power consumed by a household could be reduced, in turn reducing the effect of intermittency. It was found that the system had the ability to reduce the grid power consumed by as much as 61.86%, with an average reduction of 44.28%. This thesis then explores the concept of interconnecting a small community of nanogrids to form a microgrid. While each nanogrid within the network has the ability to operate independently, a network control strategy is created to observe the possibility of further reducing grid power consumed by the community. The strategy considers the photovoltaic power production and thermostatically controlled loads operating within the network. A ratio of the network's photovoltaic power is distributed to the thermostatically controlled loads, based on their expected consumption over a 24 hour period (highest consumption receives largest ratio of power). This was simulated with a range of household cluster sizes, with varied consumption patterns, for a week with summer/winter solar irradiance. The tests show that, compared to an uncontrolled nanogrid network, the combined control can reduce grid power consumed by as much as 55%, while a 7% decrease is seen when comparing the combined control to the individually controlled nanogrid networks. When compared to an uncontrolled individual house scenario, the combined control interconnected nanogrids can reduce the power purchase from the grid by as much as 61%.</p>

2021 ◽  
Author(s):  
◽  
Daniel Burmester

<p>Distributed generation, in the form of small-scale photovoltaic installations, have the potential to reduce carbon emissions created by, and alleviate issues associated with, centralised power generation. However, the major obstacle preventing the widespread integration of small-scale photovoltaic installations, at a residential level, is intermittency. This thesis addresses intermittency at a household/small community level, through the use of "nanogrids". To date, ambiguity has surrounded the nanogrid as a power structure, which is resolved in this thesis through the derivation of concise nanogrid definition. The nanogrid, a power distribution system for a single house/small building, is then used to implement demand side management within a household. This is achieved through the use of a hybrid central control topology, with a centralised coordinating controller and decentralised control nodes that have the ability to sense and modulate power flow. The maximum power point tracker is used to observe the available photovoltaic power, and thermostatically controlled loads present in the household are manipulated to increase the correlation between power production and consumption. An algorithm is presented which considers the expected power consumption of the thermostatically controlled loads over a 24 hour period, to create a hierarchical ratio. This ratio determines the percentage of available photovoltaic power each load receives, ensuring the loads that are expected to consume the most power are serviced with the largest ratio of photovoltaic power. The control system is simulated with a variety of household consumption curves (altered for summer/winter conditions), and a week of realistic solar irradiance data for both summer and winter. In each simulated scenario, a comparison was made between controlled and uncontrolled households to ascertain the extent grid power consumed by a household could be reduced, in turn reducing the effect of intermittency. It was found that the system had the ability to reduce the grid power consumed by as much as 61.86%, with an average reduction of 44.28%. This thesis then explores the concept of interconnecting a small community of nanogrids to form a microgrid. While each nanogrid within the network has the ability to operate independently, a network control strategy is created to observe the possibility of further reducing grid power consumed by the community. The strategy considers the photovoltaic power production and thermostatically controlled loads operating within the network. A ratio of the network's photovoltaic power is distributed to the thermostatically controlled loads, based on their expected consumption over a 24 hour period (highest consumption receives largest ratio of power). This was simulated with a range of household cluster sizes, with varied consumption patterns, for a week with summer/winter solar irradiance. The tests show that, compared to an uncontrolled nanogrid network, the combined control can reduce grid power consumed by as much as 55%, while a 7% decrease is seen when comparing the combined control to the individually controlled nanogrid networks. When compared to an uncontrolled individual house scenario, the combined control interconnected nanogrids can reduce the power purchase from the grid by as much as 61%.</p>


Author(s):  
Hasham Khan

The rapid increase in the population and fastest development in the industrial sector has increased the energy demand throughout the world. Frequent outages and load shedding has seriously deteriorated the efficiency of the electrical power distribution system. Under such circumstances, the implementation of Distributed Generation (DG) is increasing. Small hydel generators are considered as the most-clean and economical for generating electrical energy. These are very complex nonlinear generators which usually exhibits low frequency electromechanical oscillations due to insufficient damping caused by severe operating conditions. These DGs are not connected to the utility in many cases because, under varying load, they cannot maintain the frequency to the permissible value. This work presents detailed analysis of operating characteristics and proposes a hybrid frequency control strategy of the small hydel systems. The simulation and testing is performed in MATLAB, the results verified the improved performance with the recommended method. The proposed method conserves half of the power consumption. The control scheme regulates the dump load by connecting and disconnecting it affectively. The application of presented methodology is convenient in the deregulated environment, especially under the severe shortage of energy. The proposed model keeps the frequency of system at desired level. It reduces the noise, thereby improving the response time of the designed controller as compared to conventional controllers. The innovative scheme also provides power for small scale industrial, agricultural and other domestic application of far-off areas where the supply of utility main grid is difficult to provide. The recommended scheme is environmental friendly and easy to implement wherever small hydel resources are available.


2019 ◽  
Vol 125 ◽  
pp. 14006
Author(s):  
Ahmed Jumui Sumoi Fomba ◽  
Hermawan Hermawan ◽  
Trias Andromeda ◽  
Mochammad Facta ◽  
Iwan Setiawan

This paper presents a simulation of a grid-connected photovoltaic power system. A complex model of power distribution system is developed in MATLAB Simulink, then it will be simulated to determine an amount of power delivered to the grid based on irradiance and temperature. Solar irradiance data collection is conducted using a solar irradiance meter. These weather data (solar irradiances and temperatures) are transformed into signal inputs and model through a grid-tied Photovoltaic (PV) model system which consists of PV, incremental conductance Maximum Power Point Tracking (MPPT) method, DC-DC boost converter, inverter, voltage source converter (VSC) control algorithms, and grid equipment. The output variables can be related to current, voltage or power. However, tracing of the current-voltage (I-V) characteristics or power-voltage (P-V) characteristics are the vital need to grid-tied PV system operation. Changes in solar irradiance and temperature imply changes in output variables. Detailed modelling of the effect of irradiance and temperature, on the parameters of the PV module and the output parameters will be discussed. With the aid of this model, one can have a feasible idea about the solar energy generation potential at given locations. This comprehensive model is simulated using MATLAB/Simulink software.


Author(s):  
V. Mohanbabu ◽  
◽  
Sk. Moulali ◽  
Ju Chan Na ◽  
Peng Cheng ◽  
...  

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