Impact of energy efficiency and renewable energy on electricity master planning and design parameters

Abstract

At the core of network planning and designs, after diversity maximum demand (ADMD) is routinely used to define network conditions at peak periods. This dissertation explores the impact of distributed generation and energy efficient measures on the parameters used in the planning and design of residential distribution networks through an appliance-based load profile simulation and load flow studies. Traditionally, low voltage networks are operated radially in South Africa and the power flow direction is from the utility source to the customer load. Networks are designed for compliance with the lower end of the voltage regulation requirement (0.9 per unit) and to ensure that currents do not exceed transformer capacity, cable or line ratings. With distributed generation, especially when the load is low and generation is not restricted, voltage may rise and the power flow direction may be reversed so that it flows towards the utility source. Not all utilities have policies in place, and in many instances, distributed generation is implemented by households without knowledge of the utility. Methods to determine ADMD when it is not directly calculated through measurement of the maximum demand, involves using a load factor and estimated energy consumption, or the application of coincidence factors to individual household maximum demand. Load factor, as seen by the utility, generally reduces when energy is generated during periods not coinciding with peak demand, for example when electricity is generated by photo voltaic panels in a predominantly evening-peak network. Off-peak generation will result in lower load factor and energy consumption. When the utility is unaware of the distribution generation embedded in the network and the ADMD is calculated using the load factor and energy consumption method and, the calculated ADMD will be lower than required for design purposes of similar areas. Similarly, too much distributed generation increases the coincidence factors. Increased coincidence factors indicate a lack of diversity, which may result in a reverse ADMD higher than the original ADMD for which the network was designed. This may lead to previously acceptable networks no longer complying with regulations.