Substation and Feeder Maximum Demand Forecasts

To ensure security and reliability of supply, capital investment is driven by growth in demand for electricity creating emerging limitations at substations and on feeders. Importantly, no distribution network investment is directly driven by the total Energex peak demand. Hence individual substation and feeder maximum demand forecasts are prepared to analyse and address limitations with prudent investment decisions. The forecasts produced post summer 2013/14 have provided a range of demand growth rates. Some substations supplying the outer regions of the major settlement areas such as south of Ipswich are growing strongly as areas like Ripley Valley are developed. Other growth areas include the northern Gold Coast, the southern Sunshine Coast, southern Logan including Yarrabilba and Flagstone, and the northern Brisbane gateway. Energex uses the forecasts to identify network limitations and then investigates the most cost effective solution which may include increased capacity, load transfers or Demand Management alternatives. The distribution of growth rate for zone substations is shown in Figure 38.

0 2,000 4,000 6,000 8,000 10,000 12,000 14,000 16,000

2008/09 2009/10 2010/11 2011/12 2012/13 2013/14 2014/15 2015/16 2016/17 2017/18 2018/19 2019/20 2020/21 2021/22 2022/23 2023/24

GWh

Residential Non-Residential

Forecast Period

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Figure 38 – Zone Substation Growth Distribution 2015-2025

While growth in demand has remained static at a system level, there can be significant growth at a localised substation level. Approximately 15 per cent of substations have an average compound growth rate greater than 2 per cent, with 7.2 per cent exceeding an average of 4 per cent. Due to this growth, augmentation will be required to meet the additional demand on the network in these areas.

Energex has incorporated demand management initiatives into the summer and winter substation forecasts. The initiatives include broad application of air-conditioning control, pool pump control and hot water control capability. Demand management is also being targeted at network limitation substations in an effort to defer capital expenditure. The approach used is to target commercial and industrial customers with incentives to reduce peak demand through efficiency and power factor improvements. The resulting reductions are captured in the Energex Substation Investment Forecasting tool (SIFT) and in the 10 year peak demand forecasts.

These forecasts underpin the detailed analysis provided in Volume 2 of the DAPR.

The 10 year substation peak demand forecasts are prepared at the end of summer and winter each year (for day and evening peaks), and are produced within a substation forecast modelling tool. To enable appropriate technical evaluation of network limitations, these forecasts are completed for both existing and proposed substations.

Output from solar PV is generally coincident with C&I peak demand. Although there are limited numbers installed at this time, increasing penetration of solar PV at C&I premises will provide benefits through reduced substation and feeder peak demands. Conversely, the

0

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impact of solar PV at residential premises is largely negligible due to the coincident peak demand on substations and feeders occurring at around 6.30pm or after the sun has set.

5.3.1 Substation Forecasting Methodology

Energex employs a bottom up approach to develop the 10 year zone substation peak demand forecasts using validated historical peak demands and expected load growth based on demographic and appliance information in small area grids. Larger block loads are included separately after validation for size and timing by Asset Managers. The zone substation peak demand forecasts are then aggregated up to the 10 year bulk supply point, and transmission connection point demand forecasts and take into account diversity of individual zone substation peak demands and network losses. This aggregated forecast is then reconciled with the independent system demand forecast and adjusted as required.

The process used to develop the 10 year substation demand forecast is briefly described as follows:

 Validated uncompensated substation peak demands are determined for summer 2013/14;

 Minimum and maximum temperature at five BOM weather stations are regressed against substation daily maximum demand to assess the impact of each set of weather data on substation demand (Amberley, Archerfield airport, Coolangatta airport, Brisbane airport and Maroochydore airport). The best fit relationship is used to determine the temperature adjustment;

 Commercial and industrial substations tend not to be sensitive to temperature and the 50PoE and 10PoE adjustments are based solely on demand variation;

 Previous substation peak demand forecasts are reviewed against temperature adjusted results and causes of forecast error are identified;

 Starting values for MVA, MW and MVAr are calculated for four periods - summer day, summer night, winter day and winter night;

 Demographic and population analysis is undertaken and customer load profiles are prepared for Energex;

 Year-on-year peak demand growth rates are determined from the customer load profiles prepared for Energex, historical growth trends and local knowledge from Asset Managers using a panel review (Delphi) process;

 Size and timing of new block loads are reviewed and validated with Asset Managers before inclusion in the forecast;

 Size and timing of load transfers are also reviewed with Asset Managers before inclusion in the forecast;

 Timing and scope of proposed transmission projects are reviewed with development planners before inclusion in the forecast;

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 The growth rates, block loads, transfers and transmission projects are applied to the starting values to determine the forecast demand for each of the 10 years starting from a coincident demand basis;

 Zone substation forecast peak demands are aggregated up to transmission connection point demands through the bulk supply substations using appropriate coincidence factors and losses; and

 Reconciliation of the total aggregated demand with the independently produced system demand forecast ensures consistency for the 10 year forecast period.

Substation peak demand forecasts are reviewed each season and compared with previous forecasts. The relative error between recorded demand and the forecast is investigated for the most recent season. Energex has developed a tool to undertake this comparison, and this is applied to every zone substation. The substation forecast modelling tool can differentiate between approved and proposed projects in the process. However, to comply with the NER, the forecasts provided in the DAPR include approved projects only.

5.3.2 Transmission Feeder Forecasting Methodology

Energex uses a simulation tool to model the 110 kV and 132 kV transmission network. The software was selected to align with tools used by Powerlink and the Australian Energy Market Operator (AEMO). Powerlink provides a base model to Energex on an annual basis.

This base model is then refined to incorporate Energex’s future project components using an application program interface, and is uploaded with peak forecast loads at each bulk supply and connection point zone substation from Energex’s corporate database for substation load forecast (SIFT).

Twenty models are created using this simulation tool, with each model representing the forecast for a particular season in a particular year. The models have five years of summer day 50PoE and 10PoE data and five years of winter night 50PoE and 10PoE data.

5.3.3 Sub-transmission Feeder Forecasting Methodology

Energex uses a simulation tool to model the 33 kV sub-transmission network. The simulation tool has built-in support for network development which provides a variable simulation timeline that allows the modelling of future load and projects into a single model.

Simulation models are created using the existing network data. Future projects are then modelled with timings and proposed network configurations based on future project proposals being included. Future projects are automatically activated depending on the network analysis dates selected. The forecast peak loads at each substation for all years within the planning period are uploaded into the model from SIFT. Eight models are produced, each containing forecast load for the different seasons. These include summer day, summer night, winter day and winter night, and with 10PoE or 50PoE peak load. This enables Energex to identify the worst case risk period for each season.

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5.3.4 Distribution Feeder Forecasting Methodology

Forecasting of 11 kV feeder loads is performed on a feeder by feeder basis. The forecast begins by establishing a feeder load starting point by undertaking bi-annual 50PoE temperature corrected load assessments (post summer and post winter). This involves the analysis of daily peak loads for day and night to identify the load expected at a 50PoE temperature after first identifying and removing any temporary (abnormal) loads and transfers.

Using a statistical distribution, the 10PoE load value is extrapolated by using 80% of the temperature sensitivity from the 50PoE load assessment. The summer assessment covers the period from 1 November to 31 March, and the winter assessment from 1 June to 31 August. Growth rates are applied and specific known block loads are added and events associated with approved projects are also incorporated (such as load transfers and increased ratings) to develop the feeder forecast.

In addition, the 10PoE load forecast is used for determining voltage limitations.