In this paper, power losses of a multiport DC -DC converter are analysed. The converter has four bidirectional ports and consists of a triple active bridge and four half bridge converters. As a result, sixteen different operating modes, defined by all combinations of power flow direction, are possible. The converter power losses and resulting efficiencies vary widely with operating conditions. This paper presents methods to accurately calculate the efficiency of the four-port converter in each operating mode using component datasheet information, taking into account losses in the transformer of the triple active bridge converter, passive components and semiconductors. A 200 W converter prototype is used to experimentally validate the loss model for one specific operating mode.

Interconnection of two autonomous swarm grids (DC clusters) which are designed for energy access can increase power supply availability for power hungry appliances such as water pumps. Here, a surplus or a deficit power in one cluster is balanced by a second cluster through power exchange. Usually, the clusters are connected by a tie line if bus voltages in both clusters are equal and constant. If the bus voltages are different and constant, a single converter is used to interconnect the clusters and to control the power flow between them. In both interconnections, power flow is triggered by bus voltage variations from their constant values. However, if the bus voltages are different and are not constant, the coordination of the power exchange between the clusters is a challenge. In this paper, two buck-boost converters are proposed to interconnect the clusters that have different and unregulated bus voltages. To control the power exchange while reducing transmission line loss, a decentralized control approach which is composed of a voltage droop control method and a mid-point voltage control method is proposed. Simulations of two interconnected clusters carried out in MATLAB/Simulink software show how the proposed control method can efficiently coordinate the power exchange.

Decentralized battery and solar photovoltaic (PV) system organized in the form of an autonomous low voltage DC nanogrid is a potentially low cost and scalable solution for electrifying rural areas without access to the national grid. Each DC nanogrid can be installed on a single home and used to supply basic lighting, charge mobile phones and power a television set. To provide enough power to meet productive energy uses such as irrigation, the DC nanogrid can be connected to neighboring DC nanogrids to form a cluster and exchange power. However, to achieve a coordinated power exchange in the cluster, new control strategies are required. In this paper, we propose a decentralized droop control method which uses a state of charge of the battery to coordinate the power exchange. The power exchange is achieved by scheduling a terminal voltage set point at each DC nanogrid based on the state of charge of the battery. The performance of the proposed method at achieving the power exchange is analyzed through simulations in Matlab/Simulink. The method does not require inter-unit communication. Therefore, the method is reliable, robust and scalable. Also, the method maintains low amounts of power flow in distribution lines during power exchange to reduce distribution line power losses.

Peer-to-peer interconnection of households having on-site batteries, multi-port converters and solar panels to form a multi-port converter-enabled solar DC nano-grid is an emerging approach for providing affordable energy access in rural areas. Battery charge and discharge losses, distribution losses and converter losses are significant problem when operating such nano-grids. This paper presents a centralized control algorithm that can help address the power loss problem. The proposed algorithm uses a new problem formulation where the power loss problem is formulated as a two-stage convex optimization problem. The first stage of the optimization problem is an optimal battery dispatch problem for determining optimal battery charge and discharge currents. The second stage is an optimal current flow problem for determining optimal distribution voltages which corresponds to the optimal battery currents. Simulation results of the nano-grid show that the proposed algorithm can minimize the nano-grid power losses while facilitating the power exchange between the households. The proposed algorithm is suitable for small nano-grids where privacy of households is not a concern. In Part II of this paper we propose a distributed control algorithm that preserves the privacy of the households especially where the size of the nano-grid is large.