In a developing country such as India, 44% of the population does not have access to power and for many others, the power supply is unreliable. A nanogrid, defined as “a single domain for voltage, reliability and administration”, is a possible solution to distribute power to such off-grid areas. Built from the bottom up, nanogrids have the ability to function independently, using locally generated power (such as solar power) as the power source. Such grids enable residents to lead more productive lives, with improved access to power. This thesis designs a new communication protocol for nanogrids to enable matching demand to short-term limited supply. A review of the existing local grid projects in off-grid areas in developing countries is covered – outlining the cost per kWh incurred by the customer, the communications (if any) defined in each local grid and the supply duration of the local grid. A communication protocol for a nanogrid is presented, defining a list of messages required to enable communication and the use of the Link Layer Discovery Protocol (LLDP) to implement this list. A simulation evaluation of a nanogrid deployed in an off-grid rural area of a developing country is presented. Keeping three distinct days – a sunny, cloudy and rainy day and three months – summer, monsoon and winter in mind, we demonstrate how communication about the local power price of the nanogrid can be used to modulate demand in connected loads, matching present demand with short-term limited supply. Simulation results show that the nanogrid model with communication enabled results in ~95% reduction in unmet demand for the month of December with an initial battery level of 20% (the worst case scenario). These results indicate that a grid can distribute adequate power to the loads attached to it for a month in different seasons. Such a grid, with communication about power can have a great impact in developing countries, where reduced power supply or a brownout is preferred to no power supply or a blackout.

Simultaneously as the societal trends of urbanization, digitalization and electrification of society are moving at a high speed, the Swedish power grid is undergoing a necessary transition to a renewable energy system. Even though there are difficulties on all grid levels, the lack of capacity in some local grids is among the most present problems and originates from the long lead time of grid expansion as well as the challenges within long-term planning of grids. This thesis aims to improve the understanding of future trends’ impact on grid capacity needs. More specifically, a scenario-based and data driven method, with an accompanying model, is derived to target local capacity challenges. The trends identified to pose impact on the future grid capacity were electrification of different sectors, energy efficiency actions, decentralized energy generation, energy storage solutions, flexibility, smart grids, urbanization and climate. The thesis concludes that the impact of a trend on national level is not simply equal to the impact on a local level. Similarly, a long-term increase of the national electricity consumption does not necessarily worsen local capacity challenges. Furthermore, the developed model in this project shows potential to provide more detailed and accurate information about consumption than currently used methods based on standardized power estimations, which could favor more transparent decision making when dimensioning local grids.