This information booklet provides information to municipalities that are experiencing an increase in the number of SSEG on their networks. The booklet focuses on the grid impacts of SSEG by introducing two tools: (1) an SSEG load from tool, and (2) an SSEG hosting capacity tool. (CSIR, 2022)

This paper provides a practical step-by-step guide to performing a COS study, using the National Energy Regulator of South Africa (NERSA)-endorsed simplified COS tool. The methodology described is based on NERSA’s COS Framework and draws on the NRS 058 where needed. The input data is kept as simple as reasonably possible, and assumptions are explicitly described. These assumptions are the crux of where COS approaches differ vastly, and this paper brings these assumptions to light for others to replicate and build on. (SEA & NERSA, 2021)

This paper analysis the impact of small-scale embedded generation (SSEG) on the cost of running South Africa’s power system. It investigates whether utility-scale solar PV is cheaper than embedded generation. SSEG reduces overall system costs by reducing electricity losses and resulting fuel expenditure, and, in instances where peak demand is reduced, by reducing capital expenditure on network upgrades and peaking power plants. However, the upfront capital cost of utility-scale solar PV is lower (due to economies of scale) and usually has a higher capacity factor (due to optimum location and orientation, and the use of trackers) when compared to SSEG. This paper quantifies the tradeoffs associated with installing SSEG in various sectors in South Africa compared to installing the same amount of utility-scale PV. A comprehensive full-system model was built to answer this question. (SEA, 2021)

Recommendations for simulation studies as part of Grid Code compliance for Renewable Energy Power Plants and Hybrid Power Plants (P13906).  MPE.

Legal Opinion by Pinsent Masons on the application of the ERA Schedule 2 license exemption (of 5 October 2021) in the context on the MFMA, MSA, ERA Section 34 determination, and New Generation Regulations.  Pinsent Masons, 22 November 2021.

The Deterministic Hosting Capacity Analysis tool is a DIgSILENT programming language (DPL) script that calculates the hosting capacity of a LV network through deterministic means. It computes the generation capacity that can be accommodated on each bus out of a set of selected buses (determined by the user) of a LV network without violating any voltage or thermal limits. However, it does not compute the hosting capacity of the whole network. The hosting capacity of each bus is calculated assuming that no generators are connected any else on the network. For each bus, the tool also determines where network strengthening can be applied to increase the bus hosting capacity.

The Stochastic Hosting Capacity Analysis tool is a DIgSILENT programming language (DPL) script that calculates the hosting capacity of a LV network using stochastic methods. The tool computes the generation capacity that can be accommodated by the whole LV feeder network without violating any voltage or thermal limits. Additionally, the tool provides results for a configuration that describes how this generation capacity can be distributed between a given set of buses/nodes (determined/identified by the user). The tool also provides information on where network strengthening can be applied to increase its hosting capacity. The nature of the algorithm applied is such that is closely mimics events as seen in real networks where small-scale embedded generators of random sizes are connected at random locations.

This user guide is intended to help the reader with using the hosting capacity analysis tool for both the deterministic and stochastic method. The hosting capacity analysis tool is meant for use in LV networks to assess the amount of generation capacity that can be integrated into LV networks without compromising the power quality and reliability of the networks under existing control configurations and without requiring network strengthening. This guide covers the requirements needed/prerequisites that need to be met to use the tool, how to import the scripts of into DigSILENT project, and steps on how to use the stochastic and deterministic hosting capacity analysis methods/scripts. (CSIR, 2021)

The following test cases can be used to test the load flow assessment tool. The parameter for each network are given together with the expected results for each scenario (CSIR, 2021).

This user guide is a reference for use of the Load Flow Assessment tool for Small Scale Embedded Generation (SSEG) into medium and low voltage networks. It is intended for small radial distribution networks with a maximum of four buses and a minimum of two buses. Its purpose is to calculate steady-state currents, bus voltages, real and reactive power flows through branches in a network. It offers insight into how a network performs in a various operating conditions. The tool also gives insight into over and under voltage situations and thermal limit violations (CSIR, 2021).