Browsing by Author "Ramdhin, Avinash"

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    Creating additional network capacity on constrained medium voltage networks utilizing distributed generation (specifically PV technology)
    (2024) Ramdhin, Avinash; Chowdhury, Sunetra
    Medium voltage (MV) networks are designed for forward power flow and they radially distribute power to various types of electrical loads. With electrical load growth driven by economic growth, aging networks have limited network capacity to supply the increase in load demand and non-technical losses, such as theft, further exacerbate the problem. This incremental load growth results in the network feeder having unacceptable voltage regulation and/or thermal limitations and such a network is defined as a constrained network where no new load or increase of existing load can be connected. Short-term and long-term mitigation solutions are implemented on these constrained networks to create more electrical capacity to meet the rising load demand. These solutions and investment thereof are also influenced by strategic load forecasting and may include the installation of voltage regulators, shunt compensation, new substations and/or various other network strengthening solutions. Long-term solutions are generally quite costly and the timeline for implementation is extremely long (>3 years). Short-term solutions are limited by equipment ratings and as such the network capacity is improved but by a relatively lower percentage. Due to the fixed and limited output of these devices, an alternate, additional un-constraining mechanism is required. Integrating distributed generation (DG) to medium voltage (MV) networks can improve or worsen the operating level of the network. However, linking this balance of network improvement to the amount of generation would improve the operating level. This research therefore utilizes the integration of DG, specifically solar photovoltaic (PV) installations, as an alternate approach to improve the capacity of constrained electricity networks. Solar PV technology is becoming practically feasible in its installation and cost; and is being supported by industrial and residential load types. The literature review compiled in this thesis highlights the various network improvement solutions utilized to assist MV networks in operating within their grid code regulations. The research then develops a coded method to be utilized for network analysis in DIgSILENT Powerfactory supported by a data analytic interface in Microsoft Excel. This analysis optimally places PV to the network to maximize network capacity and is quantified by defining an objective function that relates network capacity improvement to DG power generation. Technical guides, policies, distribution standards and grid codes that govern the integration of DG to MV and LV (low voltage) networks determine the mathematical constraints of the objective function. The non-linear solutions to the function results in optimizing the amount and allocation of distributed DG along the MV feeder hence creating additional capacity on constrained networks. Particle Swarm Optimization (PSO) was found to be best suited for this research due to its efficiency to solving non-linear optimization problems and is proposed as the appropriate method of optimally integrating DG to un- constrain MV networks. Suitable applications of the assessment tool are placing microgrids and electric vehicle charging infrastructure. Two realistic and practical electrical networks (11 kV and 22 kV) supplying rural, commercial and industrial type loads were chosen as test networks. These networks were modelled in DIgSILENT Powerfactory by firstly using the manual method of connecting DG to the network and then secondly by applying the developed DPL script to the same network. Then results were compared to investigate what optimal PV magnitude and point of connection led to what increase in network capacity for both methods. These results are summarized below. For Network 1, a very interesting relationship was seen when calculating the objective function to achieve the percentage improvement per MW of PV generation added to the network. Different scenarios were used such as, a constrained feeder during a light load scenario was modelled using the above methodology. The network capacity to PV generation ratio (objective function) indicates that the network capacity improvement of 67% could be achieved per MW of generation added. Similarly, for the normal feeder peak load scenario, the objective function (%/MW) was approximated around 40%/MW. The developed tool results correlated closely with the results from the manual method of placing PV on MV networks to maximize network capacity. The applicability of the derived results can be, for example interpreted as such, if one is to install 400 kW of PV on Network 1, the objective function for the peak times is 39%/MW so for 0.4 MW, the network capacity improvement is calculated by 39% x 0.4 = 15.6%. A similar approach was applied to Network 2 and similar results were derived albeit Network 2 having a voltage regulator as the voltage controlling device on the network. It was concluded from the analysis that there is no linear relationship on the amount of generation and position on a network to which it may be installed. The many tee-off points on the backbone and the variation of load with respect to its location, speaks to the uniqueness of every network and no general rule can be made for PV integration. However, the ratio of the network capacity increase to the amount of generation is more or less consistent for every scenario.
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    Grid integration of distributed renewable energy sources: a network planning perspective
    (2014) Ramdhin, Avinash; Chowdhury, S
    With the drive for cleaner energy, Independent power producers (IPP’s) have to find suitable potential land sites that meet their renewable project needs and that prove to be technically feasible to integrate into the nearest distribution electrical infrastructure. Project feasibility for utility grid connection can in certain instances be directed to a specific area due to resource availability and existing electrical plant capability. This invariability leads to multiple establishments of renewable energy plants in the same geographic location. Distribution substations and high voltage (HV) lines in the South African National utility, Eskom, are planned and constructed based on simulation models derived from power system models built in DIgSILENT Powerfactory analysis software. For a Network Planning Engineer, planning for this integration can be become quite complex in a multi-machine scenario as above. This dissertation provides network planning criteria that a planning engineer in the utility can successfully use to plan for this integration. Three sets of criteria are established. With the inclusion of widespread distributed generation in close proximity of each other, sharing the same grid electrical infrastructure, a critical path of HV electrical elements exists, which the effects of the combined generation control. The first set of planning criteria is derived from the analysis of locating this critical path. This is determined by means of using iterative programming and calculations. Grid voltage stability is one the most important factors in determining the feasibility of generator grid integration. The voltage stability effects of the Eskom Distribution network to which these generating plants connect to, are analysed and tabulated results established. This will enable the utility to determine the location of a specific size of renewable plant, just by knowing the grid strength and not going into detail voltage stability studies. For the second set of planning criteria three sets of network range strengths are identified with corresponding ratios of grid strengths to generator short circuit current contributions. Successfully integrating DG to the grid also has many technical and cost solutions of network configurations. The third set of planning criteria identifies four generic network configurations and the building blocks of physically costing the engineering integration. Solar density maps provide an indication of proposed MW output in a particular area. In this research, solar density maps are used to identify the maximum connecting generation to the electrical grid in feasible geographic areas. The results derived from this study enable the planning engineer and/or developer to better plan the optimal location of a PV project wrt the chosen geographic area of KZN. This study case may be extended to other technologies leading to a more concise framework of network planning for renewable project integration.