Maximize the operational efficiency of the hybrid low voltage power network

Abstract

Renewable energy sources have become of great importance in the last decade as a result of the environmental global awareness. In Australia, renewable energy is a political hot topic where all major parties recognize the importance of taking a stance on environmental issues. Solar power is the fastest-growing source of renewable energy, and countries with favorable solar irradiance are seeing increasing levels in commercial and residential photovoltaic PHV installations. The low voltage LV (0.415 kV) rooftop PHV system installations in particular have swelled in the few recent years. Although most power industry key-players focus on large-scale renewable applications like microgrids and concentrated plants, the use of small rooftop PHV generations have become increasingly attractive for the general public individuals due to the existing governmental incentives and energy policies. PHV generations are intermittent by nature as their output powers are dependent on different environmental time-changing variables. The low penetration levels of rooftop PHV generations do not produce network problems, however, it is expected to see a high penetration of those generations in the near future which will create new challenges in power management of the distribution networks. The insufficiency of knowledge, researches and experience on the potential impacts of high installation rate of rooftop PHV generations may jeopardize the security and reliability of the distribution power grid and may reduce the network efficiency by increasing power losses. This research will approach the problem of hybrid network management which is a combination of a conventional power network and PHV rooftop generation ix on LV. The aim of this research is to develop an algorithm and a mathematical model for power optimization problem which reduce energy losses, and maximize the yield of PHV generation without violating the network constraints. The algorithm suggests power curtailment applied to PHV generation; however, this curtailment is minimized by the power optimization solution. The use of battery energy storage systems (BESSs) is discussed in detail, and an algorithm is developed to determine the minimum required BESS sizes and numbers which are needed to capture curtailed PHV energy. Finally, BESS power dispatch schedules are created to maintain the lowest network losses. The algorithms presented in this work are validated using a simulation on a real 29-buses LV system, with highly penetrated rooftop generation. The grid is assumed to operate in parallel with the main distribution grid. Different software tools are used in this work; General Algebraic Modeling System GAMS is used to solve the nonlinear mathematical power optimization model, Power Factory 2018 is used to model and run the dynamic power flow analysis. MATLAB is used to create load curves, irradiance profiles based on real data of solar irradiance and load in Sydney. The current rooftop PHV installations are neither controlled nor monitored, the control algorithms and operational methodologies presented in this work can be integrated into the energy management system EMS to enhance the hybrid network efficiency and maximize the PHV benefits which will have positive impacts on the network availability and energy prices as well.

Date of Award	2019
Original language	English