High-level control algorithms for maximising energy efficiency of solar nano-grids designed for energy access
Keywords: solar nano-grids
distributed control algorithm
energy efficiency
energy access
centralised control algorithm
four-port DC-DC converter
power losses
state-of-charge balancing

Peer-to-peer interconnection of households having on-site batteries, four-port DC-DC converters and solar panels to form four-port DC-DC converter-enabled solar nano-grids is an emerging bottom-up approach for providing affordable energy access to rural areas. However, power losses which include battery charge and discharge losses, distribution losses and converter losses are one of the technical barriers hindering the practical deployment and operation of solar nano-grids in rural areas. Power losses reduce the energy efficiency of solar nano-grids. This research aimed to answer the following research question:
What control algorithms can be developed to address the problem of maximising the energy efficiency of four-port DC-DC converter-enabled solar nano-grids that are designed for energy access?
Solar nano-grids with star and hybrid distribution network configurations were considered in this research. Three novel high-level control algorithms were developed to answer the research question. The first one was a centralised control algorithm, the second one was a quasi-consensus based distributed control algorithm and the third one was a distributed state-of-charge based droop control algorithm. Numerical and simulation results carried out in Python showed the effectiveness of the developed control algorithms for addressing the research question through the considered solar nano-grid configurations.
The first and second control algorithms addressed the research question for the star solar nano-grid configuration through optimisation. Firstly, a high fidelity steady-state model of the solar nano-grid was developed and a new two-stage convex power loss optimisation problem was formulated. The formulated optimisation problem did not require either linearisation or convex relaxation of power flow equations, making it scalable and computationally efficient. Then, the first and second control algorithms were developed to solve the formulated optimisation problem in a centralised and quasi-distributed manner respectively.
The third algorithm addressed the research question for both the star and hybrid solar nano-grid configurations through balancing the state-of-charge of the batteries in a distributed manner. In this algorithm, household distribution voltages were adjusted in proportional to the state-of-charge of their local batteries, creating an automatic power flow between the households each time there was a slight change in the battery state-of-charge. Due to the automatic power flow between the households, the magnitude of current flow at every time instant in the solar nano-grid was low, thus, keeping the power losses to a minimum.
The present work aimed to contribute towards the universal energy access agenda by focussing specifically on the third target of the United Nation’s Sustainable Development Goal 7 - doubling the global rate of improvement in energy efficiency by 2030. There is a lot of work that still needs to be done to achieve this goal. Nonetheless, the present research has made a significant step towards improving energy efficiency by developing control algorithms that minimise the solar nano-grid power losses.