Mid North Coast electricity demand forecasts

Transcription

1 Mid North Coast electricity demand forecasts A review of forecast electricity demand prepared by Essential Energy for the Greater Taree region Prepared for the Australian Energy Market Operator May 2013

2 Reliance and Disclaimer The professional analysis and advice in this report has been prepared by ACIL Tasman for the exclusive use of the party or parties to whom it is addressed (the addressee) and for the purposes specified in it. This report is supplied in good faith and reflects the knowledge, expertise and experience of the consultants involved. The report must not be published, quoted or disseminated to any other party without ACIL Tasman s prior written consent. ACIL Tasman accepts no responsibility whatsoever for any loss occasioned by any person acting or refraining from action as a result of reliance on the report, other than the addressee. In conducting the analysis in this report ACIL Tasman has endeavoured to use what it considers is the best information available at the date of publication, including information supplied by the addressee. Unless stated otherwise, ACIL Tasman does not warrant the accuracy of any forecast or prediction in the report. Although ACIL Tasman exercises reasonable care when making forecasts or predictions, factors in the process, such as future market behaviour, are inherently uncertain and cannot be forecast or predicted reliably. ACIL Tasman shall not be liable in respect of any claim arising out of the failure of a client investment to perform to the advantage of the client or to the advantage of the client to the degree suggested or assumed in any advice or forecast given by ACIL Tasman. ACIL Tasman Pty Ltd ABN Internet Melbourne (Head Office) Level 4, 114 William Street Melbourne VIC 3000 Telephone (+61 3) Facsimile (+61 3) melbourne@aciltasman.com.au Brisbane Level 15, 127 Creek Street Brisbane QLD 4000 GPO Box 32 Brisbane QLD 4001 Telephone (+61 7) Facsimile (+61 7) brisbane@aciltasman.com.au Canberra Level 2, 33 Ainslie Place Canberra City ACT 2600 GPO Box 1322 Canberra ACT 2601 Telephone (+61 2) Facsimile (+61 2) canberra@aciltasman.com.au Perth Centa Building C2, 118 Railway Street West Perth WA 6005 Telephone (+61 8) Facsimile (+61 8) perth@aciltasman.com.au Sydney Level 20, Tower 2 Darling Park 201 Sussex Street Sydney NSW 2000 GPO Box 4670 Sydney NSW 2001 Telephone (+61 2) Facsimile (+61 2) sydney@aciltasman.com.au For information on this report Please contact: Jeremy Tustin Telephone (03) Mobile (0421) j.tustin@aciltasman.com.au Contributing team members Jim Diamantopoulos

3 Contents Executive summary vi 1 Introduction Essential Energy Structure and objectives of this report 1 2 Drivers of electricity demand Population Weather Economic activity New South Wales economic growth The tourism sector Policy factors and appliance use Impact of PV systems on electricity demand The price of electricity 16 3 Historical behaviour of maximum demand at Taree Historical maximum demands Growth in observed demand Weather normalised historical maximum demands Approach to weather normalisation Historical weather normalised (50 POE) maximum demands - levels Historical weather normalised (50 POE) maximum demands growth rates Essential Energy Forecasts for Taree Summer maximum demand Winter maximum demand Consistency between summer and winter forecasts Comparison with NIEIR growth rates for the North Coast 33 4 Adjusted forecasts Starting points Growth rates Growth in the number of customers Growth in maximum demand of the average customer Relative growth in summer and winter Summary growth rates Summer maximum demand Winter maximum demand 42 ii

4 4.5 Disaggregated connection point forecasts 45 Appendix A Connection point forecasts A-1 Appendix B Drivers of electricity demand B-1 Appendix C Weather normalisation C-1 List of figures Figure 1 Mid North Coast estimated resident population - history 5 Figure 2 Mid North Coast population - projections 6 Figure 3 Weather conditions at Taree Airport during Taree Connection point peak to Figure 4 New South Wales Gross State Product (chain volume measures) annual % change 11 Figure 5 Electricity Demand and Solar Radiation 15 Figure 6 Taree 33 and 66kV historical summer maximum demands, to Figure 7 Taree 33 and 66kV historical winter maximum demands, 1996 to Figure 8 Combined Taree 33kV and 66kV historical growth rates over 5, 10 and 15 years 21 Figure 9 Combined Taree actual summer maximum demand versus 5, 10 and 15 year trend lines 22 Figure 10 Combined Taree actual winter maximum demand versus 5, 10 and 15 year trend lines 22 Figure 11 Taree historical growth rates over 5, 10 and 15 years based on start and end points from linear trend 23 Figure 12 Taree ratio of summer to winter peak, 1997 to Figure 13 Combined Taree summer weather normalised maximum demands 26 Figure 14 Combined Taree weather normalised winter maximum demands 27 Figure 15 Annualised growth rate of weather normalised maximum demands 2003 to 2012, summer and winter 29 Figure 16 Essential Energy s forecast summer maximum demand for Taree (50 POE) 30 Figure 17 Essential Energy s forecast winter maximum demand for Taree (50 POE) 31 Figure 18 Ratio of summer to winter maximum demands, historical and forecast 32 Figure 19 NIEIR Summer and winter growth rates, North Coast 33 Figure POE summer maximum demand forecasts 40 Figure POE summer maximum demand forecast 41 Figure POE winter maximum demand forecasts 43 Figure POE Winter maximum demand forecast 45 Figure A1 Connection point 50 POE summer maximum demand forecasts, to A-4 Figure A2 Connection point 10 POE summer maximum demand forecasts, to A-8 Figure A3 Connection point 50 POE winter maximum demand forecasts, 2013 to 2023 A-12 iii

5 Figure A4 Connection point 10 POE winter maximum demand forecasts, 2013 to 2023 A-16 Figure B1 Room nights in North Coast quarterly data B-3 Figure B2 Room nights in North Coast three month rolling average B-3 Figure C1 Winter daily maximum demand and average temperature 2003 to 2012 C-1 Figure C2 Summer daily maximum demand and average temperature to C-2 List of tables Table 1 Summer season MDs and weather conditions prevailing at the peak 26 Table 2 Winter season MDs and weather conditions prevailing at the peak 28 Table 3 Alternative starting points 35 Table 4 Assumed growth rates 39 Table 5 50 POE summer maximum demand forecast 39 Table 6 10 POE summer maximum demand forecast 41 Table 7 50 POE Winter maximum demand forecast 42 Table 8 10 POE Winter maximum demand forecast 44 Table A1 Taree 33 kv 50 POE Summer maximum demand forecasts, to A-1 Table A2 Taree 66 kv 50 POE Summer maximum demand forecasts, to A-1 Table A3 Herons Creek 50 POE Summer maximum demand forecasts, to A-2 Table A4 Halliday s Point 50 POE Summer maximum demand forecasts, to A-2 Table A5 Hawk s Nest 50 POE Summer maximum demand forecasts, to A-3 Table A6 Taree 33 kv 10 POE Summer maximum demand forecasts, to A-5 Table A7 Taree 66 kv 10 POE Summer maximum demand forecasts, to A-5 Table A8 Heron s Creek 10 POE Summer maximum demand forecasts, to A-6 Table A9 Halliday s Point 10 POE Summer maximum demand forecasts, to A-6 Table A10 Hawk s Nest 10 POE Summer maximum demand forecasts, to A-7 Table A11 Taree 33 kv 50 POE Winter maximum demand forecasts, 2013 to 2023 A-9 Table A12 Taree 66 kv 50 POE Winter maximum demand forecasts, 2013 to 2023 A-9 Table A13 Herons Creek 50 POE Winter maximum demand forecasts, 2013 to 2023 A-10 Table A14 Halliday s Point 50 POE Winter maximum demand forecasts, 2013 to 2023 A-10 Table A15 Hawk s Nest 50 POE Winter maximum demand forecasts, 2013 to 2023 A-11 Table A16 Taree 33 kv 10 POE Winter maximum demand forecasts, 2013 to 2023 A-13 iv

6 Table A17 Taree 66 kv 10 POE Winter maximum demand forecasts, 2013 to 2023 A-13 Table A18 Herons Creek 10 POE Winter maximum demand forecasts, 2013 to 2023 A-14 Table A19 Halliday s Point 10 POE maximum demand Winter forecasts, 2013 to 2023 A-14 Table 20 Hawk s Nest 10 POE Winter maximum demand forecasts, 2013 to 2023 A-15 Table B1 Employment by industry sector B-2 Table B2 Price elasticity of energy demand across jurisdictions B-6 Table C1 Estimated temperature sensitivities from seasonal regressions, MW per degree C-3 v

7 Executive summary The purpose of this report is to review the most recent connection point forecasts developed by the Distribution Network Service Providers (DNSPs) that operate the following connection points and adjust them if required: Hawk s Nest (new connection point) Halliday s point (also referred to as Nabiac - future connection point) Taree 66 kv Taree 33 kv Herons Creek (split from Taree 66 kv) The DNSP for these connection points is Essential Energy. This review was informed by ACIL Tasman s views regarding best practice load forecasting and information provided by Essential Energy regarding their forecasting methodology. The time available for the review means that it was primarily a qualitative review. In our view the electricity load forecasts should reflect the key drivers of electricity demand. In this case we consider that the two most important drivers are: 1. weather, particularly temperature 2. population growth. Load forecasts can be summarised by reference to the starting point and growth rate. This review is framed accordingly. In our view, the starting points and growth rates proposed by Essential Energy should both be revised. The main issue with the starting points is that they were not based on weather normalised data. At the aggregate level (sum of Taree 33kV and 66kV connection points) the starting points would be 80.2 MW for summer 2012/13 and 81.2 MW for winter Adopting these starting points would cause Essential Energy s summer forecasts to be increased and its winter forecasts to be reduced. In our view growth in electricity demand in the Greater Taree region is likely to be in line with population growth there. The available projections of population growth in for the region were prepared in 2006 and now appear optimistic (that is, high growth). In the absence of a persuasive reason to do otherwise our preference is to proceed on the assumption that future population growth will be similar to the historical trend, which has been 0.70 Executive summary vi

8 per cent per annum. We recommend adopting this as the assumed rate of growth for winter electricity demand. It is clear from the historical data that growth in summer electricity demand has outstripped growth in winter. Essential Energy has estimated the ratio between these two as 1.78 to 1, which we recommend is preserved. Therefore, we recommend that the forecasts summarised in Figure ES 1 be adopted (at the aggregate level for what is currently Taree 33kV and 66kV and, in time, will include Halliday s Point and Heron s Creek). Table ES 1 Adjusted forecasts Greater Taree Year (summer ending) Summer 50 POE Summer Actual Winter 50 POE Winter Actual Actual MW MW MW MW N/A N/A Forecast Summer 50 POE Summer 10 POE Winter 50 POE Winter 10 POE 2013 N/A N/A Source: ACIL Tasman Executive summary vii

9 MW Mid North Coast electricity demand forecasts Figure ES 1 Adjusted forecasts summer Greater Taree Low High Actual MD Medium Essential (original) 50 POE weather normalised MD Source: ACIL Tasman Executive summary viii

10 MW Mid North Coast electricity demand forecasts Figure ES 2 Adjusted forecasts winter Greater Taree Low High Actual MD Medium Essential (original) 50 POE weather normalised MD Source: ACIL Tasman At Hawk s Nest, Essential Energy will receive a transfer of load from Ausgrid in winter Our adjusted forecasts for Hawk s Nest are shown in Table ES 2. Executive summary ix

11 MW Mid North Coast electricity demand forecasts Table ES 2 Adjusted forecasts Hawk s Nest Winter 50 POE Winter 10 POE Summer 50 POE Summer 10 POE Forecast MW MW Forecast MW MW Source: ACIL Tasman Figure ES 3 Adjusted forecasts Hawk s Nest Summer 50 POE Winter 50 POE Summer 10 POE Winter 10 POE Source: ACIL Tasman Executive summary x

12 1 Introduction 1.1 Essential Energy Essential Energy is an electricity distribution network service provider. It is owned by the New South Wales Government and operates a network that covers approximately three quarters of New South Wales, making it the largest single electricity distribution network in Australia. The Mid North Coast of New South Wales is bounded by Hawk s Nest in the South and Iluka in the North. It extends from the sea to Dorrigo and Stroud inland. The Mid North Coast region includes such well known areas as Coffs Harbour, Bellingen, Dorrigo and Nambucca Heads. The Mid North Coast region incorporates Taree and its surrounds. Electricity is supplied to Taree through two existing connection points, one each at the 33 and 66kV levels. Where this report refers to demand at Taree, it refers to the total (sum) demand at these two connection points. Broadly, Essential Energy proposes to disaggregate this aggregate demand and supply it using several connection points. In addition, it will receive a transfer of certain customers located near Hawk s Nest who are currently supplied by Ausgrid. The electricity demand of these customers is currently not reflected in Essential Energy s historical data, so that connection point is treated independently. 1.2 Structure and objectives of this report In ACIL Tasman s view, electricity demand forecasts should satisfy the following criteria. 1. They should be accurate This property is highly important given that errors can result in economically costly or wasteful outcomes, either through the construction of excess capacity in the system which is a wasteful deployment of capital or through insufficient capacity which could result in chronic power blackouts and poor performance of the network. 2. They should be unbiased This means that the forecasting methodology should not consistently over or under estimate. The statistical and econometric techniques that we employ allow testing for bias and adjustment to remove the bias. Introduction 1

13 3. The forecasting methodology should be transparent and repeatable. incorporate the key drivers of demand and energy. incorporate a suitable method of weather normalisation. be parsimonious (simple as possible) without significantly sacrificing performance In fact there may be a trade-off between forecasting performance and model complexity, with a point being reached where any improvements in forecast accuracy could be outweighed by the increased complexity of the methodology. take into account any limitations in data availability or constraints in information system technologies employed. be subjected to statistical model validation and testing. The purpose of this report is to review the most recent connection point forecasts developed by the Distribution Network Service Providers (DNSPs) that operate the following connection points and adjust them if required: Taree 66 kv Taree 33 kv Halliday s Point (also referred to as - Nabiac future connection point) Herons Creek (split from Taree 66 kv) Hawk s Nest (new connection point) The DNSP for these connection points is Essential Energy. Our review has been informed by the above criteria and brief information provided by Essential Energy regarding the methodology by which the forecasts were prepared. However, the time available for the review means that it was primarily a qualitative review. The first two criteria, accuracy and unbiasedness, are difficult, if not impossible, to test before the event. That is, one cannot be sure whether forecasts are accurate, or whether a methodology has a tendency to over or under forecast until afterwards. This highlights the importance of the other criteria. Forecasts that satisfy these criteria are more likely to be accurate and unbiased. Introduction 2

14 A key characteristic of any robust forecasting methodology, therefore, is that it takes account of the drivers of electricity demand. Therefore, a key focus of our review has been to consider whether: 1. the forecasting methodology takes account of key drivers of electricity demand 2. the forecasts are consistent with projections of those drivers. The remainder of this report is structured as follows. Chapter 2 provides an overview of key drivers of electricity demand as background for the review. It includes an overview of drivers and their recent history in New South Wales and the Mid North Coast region (where appropriate data are available). The discussion in the chapter is brief, with further detail regarding certain drivers provided in Appendix B. Chapter 3 contains the substance of our review. It provides an overview of Essential Energy s forecasts of maximum demand for the Greater Taree region (the sum of the two Taree connection points and, in time, the Halliday s Point and Heron s Creek connection points). It also provides a brief description of the methodology by which we understand that they were prepared. It summarises the forecasts by reference to their starting point and growth rate applied and then considers the appropriateness of the forecasts in terms of those two parameters. Chapter 4 applies the conclusions reached in chapter 2.6 to produce alternative forecasts. These are provided at the Greater Taree level. Forecasts for the individual connection points, including Hawk s Nest, are presented in Appendix A. Introduction 3

15 2 Drivers of electricity demand The following sections provide an overview of the recent history of these factors in turn: Economic activity in the area in question Population and household size The price of electricity Policy factors such as policies to encourage the use of distributed generation Appliance use, in particular uptake of heating and cooling appliances. 2.1 Population Another likely driver of electricity demand is population. Simply put, the more people in an area, the more electricity they will use. 1 The estimated resident population of each Local Government area in the North Coast region as reported by the Australian Bureau of Statistics is shown in Figure 1. Both the level of population (i.e. number of resident persons) and annual growth are presented. The figure shows that each of the Local Government areas in the wider Mid North Coast region experienced population growth in excess of one per cent per annum until approximately Their population growth then declined and has been below one per cent per annum since approximately 2005 (later for Port Macquarie). 1 Note that parts of the Mid North Coast have large tourist populations during summer. This is discussed in section 2.1. People need not live in an area to contribute to electricity demand there. Drivers of electricity demand 4

16 % growth Persons Mid North Coast electricity demand forecasts Figure 1 Mid North Coast estimated resident population - history Population level Total Great Lakes Total Port Macquarie Total Kempsey - Nambucca Total Taree - Gloucester Population growth 3.00% 2.50% 2.00% 1.50% 1.00% 0.50% 0.00% Total Great Lakes Total Kempsey - Nambucca Total Port Macquarie Total Taree - Gloucester Note: Growth is calculated on a year on year basis TOTAL MID NORTH COAST (excl Lord Howe Island) Data source: Australian Bureau of Statistics, Catalogue No Regional Population Growth, Australia, Table 1, available from Drivers of electricity demand 5

17 The New South Wales Department of Planning published population projections in Those projections take 2006 Census data and are then projections from 2007 to The projections for the Mid North Coast region are shown in Figure 2. For comparison with Figure 1, the growth rate for the Mid North Coast (dashed blue line) is reproduced. Figure 2 Mid North Coast population - projections 2.00% 1.80% 1.60% 1.40% 1.20% 1.00% 0.80% 0.60% 0.40% 0.20% 0.00% Mid North Coast (ABS) NSW Dept Planning (MNC) Average of Greater Taree (ABS) Mid North Coast (forecast Id) Greater Taree (ABS) Data sources: Australian Bureau of Statistics, Catalogue No Regional Population Growth, Australia, Table 1, available from and New South Wales Department of Planning State and regional population projections: 2008 release, available from AU/Default.aspx New South Wales Department of Planning, New South Wales State and regional population projections, available from Forecast id online publications are available from each of the relevant local Governments. The figures presented here are the annual percentage change in the sum of the three. Note: The ABS data are estimates of the resident population of Statistical Areas Level 2-4 (SA2s - SA4s) for June 30 of each year from 2001 to 2011, according to the 2011 edition of the Australian Statistical Geography Standard. Estimates for 2001 to 2006 are final and estimates for 2007 to 2011 are preliminary rebased. There are three local Governments including, or near, parts of the Mid North Coast, namely Port Macquarie Hastings, Greater Taree and Great Lakes. Each of these publishes population projections provided by Forecast id. The growth rate of the projections published by the Greater Taree City Council is also shown in Figure 2. As we understand the projections presented in Figure 2 they were all based on data up to the 2006 census, and thus the growth rates presented after 2006 to Drivers of electricity demand 6

18 the present are forecasts prepared earlier. For this reason, they are likely to be more optimistic (i.e. faster growth) than is supported by current conditions. Collectively, the projections suggest an acceleration in population growth relative to the historical trend. On the one hand, the Greater Taree City Council suggests that population will grow strongly in future, with a significant acceleration expected above existing growth rates. Greater Taree City Council projects population growth of almost 1.5 per cent per annum from 2014 to On the other hand, the New South Wales Department of Planning projects relatively stable population growth of approximately one per cent per annum with a slight deceleration over time. In the absence of a persuasive reason to do otherwise our preference is to proceed on the assumption that future population growth will be similar to trend. Further, population growth and economic performance are typically linked closely to one another. Given the relatively flat economic outlook, it is difficult to see a basis for forecasting rapid population growth. This may not have been the case in 2006 when economic activity was stronger. For these reasons we consider that assuming future population growth will be consistent with the ten year historical (compound) growth rate as reported by the ABS is the preferred option. This leads us to assume that future population growth in the Greater Taree region will be approximately 0.70 per cent per annum. 2.2 Weather Weather is another key driver of electricity demand due to electricity s use as a fuel for heating and cooling. For regulatory purposes electricity demand forecasts are not actually intended to forecast what electricity demand will be in any given year. Rather, they are intended to forecast what it would be if the weather is normal or, more particularly, what demand would be under 50 per cent probability of exceedence (POE) conditions. The metric we use to measure weather in this case is the daily temperature, specifically a weighted average of daily maximum and minimum temperature (see Appendix C for details). It would be possible to use more complex weather variables incorporating features such as lag structures and other variables such as wind speed (for winter) and humidity (for summer), However, our experience in this area Drivers of electricity demand 7

19 suggests that the vast majority of weather related variation can be captured by the temperature conditions on the actual day of the peak. Given that the electricity demand with which we are concerned is in the Greater Taree region, it is important to use a weather station in that region. In this case we used data from the Taree Airport weather station, which has been in operation since Figure 3 summarises the weather data by showing the maximum and minimum temperatures that were observed on the peak day at the Taree connection point in summer and winter between 2003 and The figure shows that the more recent years in the sample were characterised by milder conditions than the earlier years. This has implications for interpreting the demand data, which are discussed in Chapter 2.6. Drivers of electricity demand 8

20 Max and Min temperature on peak demand day ( C) Max and Min temperature on peak demand day ( C) Mid North Coast electricity demand forecasts Figure 3 Weather conditions at Taree Airport during Taree Connection point peak to 2012 Summer Year (Winter) and year ending (Summer) Max Min Linear (Max) Linear (Min) Winter Year (Winter) and year ending (Summer) Max Min Linear (Max) Linear (Min) Data source: Bureau of Meteorology 2.3 Economic activity At the State and national level, it is reasonably straightforward to forecast electricity demand based on projections of economic activity (and other factors). It is reasonable to analyse and project economic product at the State Drivers of electricity demand 9

21 (regional) level, as well established methods exist for measuring this parameter and historical time series are readily available. However, at more granular levels, such as intra state and connection point levels, there are challenges with this approach. Economic product is not an entirely meaningful concept at granular levels. For example, there will be many businesses that operate in an area supplied by one connection point, but employ people whose homes are supplied by another. Those businesses would report their economic activity in the area where they operate, but also contribute to activity where their employees reside. Therefore, economic activity in an area supplied by one connection point can drive electricity demand in another area. We are not aware of detailed economic projections for either the Mid North Coast or Greater Taree regions. However, in our view, economic projections for New South Wales more broadly are likely to be adequate for present purposes. We reach this conclusion based on the fact that the structure of employment in Greater Taree, the Mid North Coast and New South Wales is similar. The employment structure of the two regions is shown in Appendix B New South Wales economic growth In recent years economic growth in New South Wales has not been strong. In January 2013 the New South Wales Parliamentary library published its view that economic growth is now New South Wales key weakness. The key message from a demand forecasting perspective is that New South Wales has recently been experiencing lacklustre economic growth. This is illustrated in Figure 4, showing year on year growth in New South Wales Gross State Product from 1 July 1991 to 30 June 2012 (latest available data). Drivers of electricity demand 10

22 Annual growth (%) Mid North Coast electricity demand forecasts Figure 4 New South Wales Gross State Product (chain volume measures) annual % change 6% 5% 4% 3% 2% 1% 0% year ending 30 June Historical NSW Government projection Data source: Australian Bureau of Statistics, Catalogue 1350, Table 9.3 and Department of Treasury and Finance New South Wales, Half Yearly Review, December 2012, available from both accessed 5 March Figure 4 shows that the New South Wales economy experienced strong growth in the late 1990s into However, it has grown more slowly since then. The historic trend in the growth rate over the period shown here is negative. That is, the New South Wales economy has been growing more and more slowly as time has passed (i.e. decelerating). Looking forward there are signs that growth in the New South Wales economy will improve. In the 2012/13 Budget the Government projected rising economic growth, though those projections were revised downwards in the Mid Year economic review in December However, in the February 2013 Economic Update the Treasurer referred to brighter rays of optimism for the New South Wales. 2 The New South Wales Government s current growth projections are shown in Figure 4, with historical figures reproduced for comparison. Those projections show that the Government expects that economic growth in the next few years will be stronger than it has been in recent years, though it is not expected to return to the levels of the late 1990s. 2 Growth projections were not published at this time. Drivers of electricity demand 11

23 2.3.2 The tourism sector Essential Energy has suggested that electricity demand in the Mid North Coast region is related to the number of room nights sold in tourist accommodation in the region. There are at least two reasons why this relationship might be expected. The first reason is indirect, but may be important. In a region with a substantial tourism sector, the number of room nights sold may provide a better indication of economic activity than broader economic projections. That is, tourists who visit will contribute to the local economy and, in this indirect way, contribute to the demand for electricity. In other words, the number of room nights occupied may provide a better proxy for economic activity in the region than GSP, which is inherently a whole of state value. This would be especially true if the region was more dependent on the tourism industry than the State. That is, if the Mid North Coast or Greater Taree were more dependent on tourism than New South Wales. However, as shown in Appendix B.1, the data do not support this interpretation in the Greater Taree region. 3 Eight per cent of the workforce of the Greater Taree region are employed in the accommodation and food services industry. This is only one percentage point higher than the corresponding statistic for New South Wales, suggesting that economic performance in the Greater Taree region is not significantly more dependent on this particular industry than the State of New South Wales. The second reason is more direct. When accommodation is occupied electricity is used. When it is not, less electricity is used. This is potentially a very important driver in regions with strong tourism industries. However, for the same reasons, it may not have a significantly stronger relationship with electricity demand than State economic activity. In any event, our analysis of the data (presented in Appendix B.2) suggests that the tourism industry is unlikely to drive substantial changes in electricity demand in future in either the Mid North Coast or Greater Taree regions. 2.4 Policy factors and appliance use Reducing energy use has been a key focus of Australian energy policy for approximately the last decade and appears likely to remain a key focus into the 3 This does not mean that the suggestion is not valid in other parts of Essential Energy s distribution area. The data suggest that the broader Mid North Coast region, is more dependent on the accommodation and food services industry, It is quite plausible that there are parts of this region that are highly dependent on this sector. Drivers of electricity demand 12

24 future. 4 It stands to reason that this would be reflected in demand for electricity. Broadly, there are two categories of policy to consider: 1. the carbon price 2. policies to increase energy efficiency of either appliances, homes and businesses These categories are discussed in Appendix B.4. A discussion of the implications for forecasting maximum demand is presented here. The policy impacts discussed above are relevant to Essential Energy s demand forecasts as follows: the carbon price will influence the price of electricity and therefore demand through elasticity. In practice, the carbon price is likely to have a fairly small impact on retail prices, bearing in mind that the wholesale cost of electricity is itself only one component of these. Given this and the likely small elasticity, the impact of the carbon price on demand is likely to also besmall. In any case, the appropriate way to incorporate the carbon price into demand forecasts is through the projected (wholesale) price of electricity. It would be double counting to make an additional adjustment to account for the carbon price itself energy efficiency and appliance policies are relevant to the demand for electricity through their effect on average use per household. However, they have been in place for some time and we do not expect that there will be substantial further changes in household demand in the medium term. 2.5 Impact of PV systems on electricity demand The use of distributed generation is also likely to have an impact on electricity demand. The most commonly used form of distributed generation in Australia at the moment is solar photovoltaic (PV) systems and in the remainder of this report we refer only to PV systems. The widespread use of PV systems in Australia is a relatively recent phenomenon. In recent years it has been driven substantially by Government feed-in tariff policies, declines in the capital cost of PV systems and anticipation of high electricity prices in future. Until approximately 2010, AEMO regarded the installed capacity of PV systems to be too small to have a 4 It is always difficult to say when a particular objective became the focus of policy because there are rarely bright lines. We note, for example, that the National Framework on Energy Efficiency was first adopted by the (then) Ministerial Council on Energy in 2004, nearly ten years ago. Of course work had been going on before then. Drivers of electricity demand 13

25 material impact on overall electricity demand. However, this is no longer AEMO s view. 5 Strictly speaking, PV systems have no impact on demand for electricity. Rather, they provide an alternative source from which a customer can take electricity. Whether a customer uses electricity from a PV system or from the grid their demand for electricity is the same. However, from a DNSP s perspective, the key question is the demand that will be placed on the network. Measured in this way, demand is reduced by PV systems. The amount that demand on the network is reduced is related to the total output of the PV system, not only the portion of that output that is exported. That is, it matters less whether the output of a PV system is used by the customer that owns that system or their neighbour. More important is the fact that less electricity needs to be transferred from the connection point. 6 The total output of a PV system at the time of system peak is uncertain. It can be altered by factors such as temperature and cloud cover as well as the time of day when the peak occurs. Peak electricity demand often occurs late in the day when the sun is low in the sky, which means that PV output is less than its peak capacity. AEMO has estimated that in New South Wales the typical PV system will be operating at 29 per cent of rated capacity at 4:00 pm, which is the time at which peak demand is typically observed. This is supported by Figure 5, which compares small customer consumption in Essential Energy s distribution region on a randomly selected day in November 2012 with solar radiation. It shows that when peak electricity demand occurred. Solar radiation was at approximately 32 per cent of its maximum. 5 AEMO, Rooftop PV information Paper, National Electricity Forecasting, May 2012, available from 6 This is something of a simplification as the exported electricity is still transferred by the network. Drivers of electricity demand 14

26 kw Mid North Coast electricity demand forecasts Figure 5 Electricity Demand and Solar Radiation :00 6:00 12:00 18:00 0:00 w/m 2 Consumption Solar radiation Note: Consumption reflects the Net System Load Profile, including the Controlled Load Profile, for Essential Energy s distribution region on 11 November The solar insolation data plotted here are were taken from Renewables SA ( They are modelled estimates of solar radiation (global horizontal irradiance) at Pimba in South Australia s Central North West. These data are presented here as indicative of the solar radiation data thatcould be expected at Taree because the two places are at similar latitudes (both approximately 31 degrees south) Therefore, while we understand from Essential Energy that the installed capacity of PV systems in the Greater Taree region is approximately 8 MW. 7. It does not follow from this that, without those PV systems, maximum demand would be 8 MW higher. Regardless of the relationship between rated capacity and the reduction in peak, the maximum demands that have been observed in recent years reflect the existence of the 8MW of PC systems in the Greater Taree region and, over time, the rate at which they have been installed. From the perspective of projecting demand, the question to consider is the rate at which PV systems will be taken up in future and, more importantly, whether the rate will change significantly from the rate that has been observed in the recent data. If a substantial change was expected an adjustment to the projection may be warranted. There are factors that would suggest a reduction in uptake, in particular as the reduction of support for PV systems through cross subsidies such as feed in tariffs and small scale technology certificates. However, these appear to have been offset by other factors, such as the decline in system capital costs. On balance, we anticipate that growth in uptake of PV systems will continue to be 7 This is approximately 10 per cent of the maximum demand in that area. Drivers of electricity demand 15

27 strong and broadly consistent with recent history. This suggests that no additional adjustment is required for demand forecasts to account for changes in the rate of PV uptake. 2.6 The price of electricity It is well understood that the price of a product influences demand for that product. It is also well known that the price of electricity has increased significantly in recent years. The price that end use customers pay for electricity is the sum of several components including a contribution to the cost of providing network services (transmission and distribution) and the wholesale price of electricity. In this report we refer to the sum of these and other components as the retail price. 8 In New South Wales, electricity retail prices increased rapidly in approximately the second half of the last decade. However, any effect this will have on electricity demand is already in train. For demand forecasting purposes, the more important question is what electricity (retail) price will do in future. Projecting electricity price in this context is problematic because, to some extent, it depends partly on future network expansions which depend, in turn, on demand projections. There is also significant Government policy activity in relation to electricity prices which makes it difficult to make a firm projection of forward electricity retail prices. 9 There are a range of factors including greenhouse gas emissions reduction policy and network expansions that are likely to place upward pressure on price in future, so it is unlikely that prices will remain flat or fall. At the same time, prices have grown rapidly recently, so it may be reasonable to expect that the rate of growth will slow. 10 In any event, as discussed in Appendix B.3, the magnitude of the relationship between price and maximum demand is not likely to be large. For this reason, 8 Note that most small customers pay a single price negotiated with their retailer. A few business and other large customers may pay separate prices for each component. 9 That policy is focussed particularly on network prices and could potentially lead to a reallocation between customers. This could potentially have a substantial impact on prices, though the impact would be different for different classes of customer. 10 See, for example, Australian Energy Market Commission, Electricity Price Trends Final Report: Possible future retail electricity price movements: 1 July 2012 to 30 June 2015, 22 March 2013, available from Drivers of electricity demand 16

28 the forward price of electricity is not likely to be a highly important factor in forecasting maximum demand This would not be the case for forecasting energy consumption but, as discussed in Appendix B.3, this is a different concept. Drivers of electricity demand 17

29 3 Historical behaviour of maximum demand at Taree This chapter provides an overview of historical maximum demand at the Taree connection point. 12 The overview begins, in section 3.1, with a discussion of the maximum demand as it was observed at the Taree connection point each year between 1997 and These data are not weather corrected, leaving them susceptible to bias given the trend to milder conditions that has been observed. They are presented in spite of this for two reasons: 1. there is still value in comparing the two seasons to one another, in particular to give insight into their relative growth rates 2. these data form the basis of Essential Energy s projections. The chapter then provides a discussion of the weather normalised historical demands in section 3.2. This discussion is limited to demand since 2003, which is the earliest that high the frequency data necessary for weather normalisation was available. This discussion is in three parts. First, section provides a description of the approach used for weather normalisation. Then, section and compare levels and growth in weather normalised demand with growth in demand as observed. 3.1 Historical maximum demands An examination of the historical maximum demand at Taree shows that it grew strongly in the first ten years for which data are available. That is, from 1997 to approximately As Figure 6 shows, summer maximum demand in Taree increased from 59 MW in to 94 MW in It has trended down since then, with each observed demand being below this level except where maximum demand reached 96 MW. 12 There are two connection points at Taree, one each at the 33kV and 66kV levels. In the discussion in this section they are treated as one. The demands referred to are the sum of the demand at the two connection points. Historical behaviour of maximum demand at Taree 18

30 MW MW Mid North Coast electricity demand forecasts Figure 6 Taree 33 and 66kV historical summer maximum demands, to Data source: Essential Energy The same general pattern is evident in winter demand, which rose from 76 MW in 1996 to 108 MW in 2008, as shown in Figure 7. After this the decline in maximum demand starts to gather momentum. Figure 7 Taree 33 and 66kV historical winter maximum demands, 1996 to Data source: Essential Energy As mentioned above, these data have not been adjusted to standard weather conditions, which were milder in the last five years of the sample than they were before then. This accounts for some of the decline in demand shown in Historical behaviour of maximum demand at Taree 19

31 this figure (see section for details). However, the decline in observed demand appears large enough to suggest that the impact of the difficult conditions after the global financial crisis as well as policy factors have placed downward pressure on maximum demand in both summer and winter since approximately Growth in observed demand The previous sections focussed on the level of maximum demand. However, for forecasting purposes it is important to consider historical growth, which is discussed in this section. In addition to calculating the annualised growth over the entire period for which data are available we also calculate growth rates from a trend. This approach is preferable, though it remains susceptible to bias because weather factors are not properly accounted for. However, it is informative in this case given that Essential Energy s forecasts are based on the raw demand data. It is important to note though that the available data date back to This mitigates the bias. The longer the time series that is available, the more likely it is that the pattern in the data reflects the true underlying growth rate. Figure 8 below presents the growth in historical maximum demand growth at Taree over a number of historical periods, ranging from 5, 10 and 15 years for both summer and winter using the start and end point approach. 13 All growth rates refer to annualised growth rates (i.e. compound growth over the relevant period). Figure 9 and Figure 10 show that maximum demand declined between 2007 and 2012 (the most recent five years for which data are available). The decline was observed in both summer and winter. Over the last ten years (from 2002 to 2012) maximum demand in summer showed some slow growth (0.40% per annum) while winter declined at 0.47% per annum. Over the longer 15 year period (from 1997 to 2012), maximum demand in winter grew at 0.24% per annum, while summer maximum demand grew at 1.69% per annum. 13 Time periods are: 5 years winter 2007 to 2012 or summer 2006/07 to 2011/12 10 years - winter, 2002 to 2012, summer 2001/02 to 2011/12 15 years - winter 1997 to 2012, summer 1996/97 to 2011/12 Historical behaviour of maximum demand at Taree 20

32 % per annum Mid North Coast electricity demand forecasts Figure 8 Combined Taree 33kV and 66kV historical growth rates over 5, 10 and 15 years 2.0% 1.69% 1.0% 0.0% 0.24% 0.40% -1.0% -0.47% -2.0% -3.0% -4.0% -5.0% -1.98% -3.85% Last 15 years Last 10 years Last 5 years Summer Winter Data source: Essential Energy and ACIL Tasman calculations Compound growth rates based on trend lines 14 are presented in Figure 11, with the trend lines themselves presented in Figure 9 and Figure 10. There has been a clear declining trend in winter maximum demand over the last 5 and 10 years, with growth in the first five years for which data are available (i.e. from 1997 to 2002) as well as a clear tendency for summer maximum demand to grow more strongly than winter. 14 That is, the compound growth rate from the beginning and end of the trend line itself. Historical behaviour of maximum demand at Taree 21

33 MW MW Mid North Coast electricity demand forecasts Figure 9 Combined Taree actual summer maximum demand versus 5, 10 and 15 year trend lines TG Actual Summer MW 15 year trend line 10 year trend line 5 year trend line Data source: Essential Energy and ACIL Tasman calculations Figure 10 Combined Taree actual winter maximum demand versus 5, 10 and 15 year trend lines Data source: Essential Energy and ACIL Tasman calculations Actual Winter MW 15 year trend line 10 year trend line 5 year trend line Historical behaviour of maximum demand at Taree 22

34 % per annum Mid North Coast electricity demand forecasts The calculated annualised growth rates based on these trend lines are presented in Figure 11. There has been a clear declining trend in winter maximum demand over the last 5 and 10 years, with growth in the first five years for which data are available (i.e. from 1997 to 2002) as well as a clear tendency for summer maximum demand to grow more strongly than its winter counterpart. Figure 11 Taree historical growth rates over 5, 10 and 15 years based on start and end points from linear trend 4.0% 3.0% 2.0% 1.0% 0.0% -1.0% -2.0% -3.0% -4.0% -5.0% 2.86% 1.01% 1.15% 1.12% -0.41% -4.33% Last 15 years Last 10 years Last 5 years Summer Winter Data source: Essential Energy and ACIL Tasman calculations The fact that demand growth in summer has outstripped demand growth in winter is also illustrated in Figure 12, which shows the ratio of the two (where the ratio is above the dashed line, the peak was observed in summer. Where it is below the line the peak was in winter). While the series does exhibit a significant degree of volatility (as summer demand is more sensitive to extreme weather conditions than winter), a clear upward trend can be observed. That trend is present throughout the period for which data are available. While the data shown here are not weather corrected, and thus susceptible to being distorted by changing weather conditions, this is not likely to affect the ratios strongly because the trend to milder years in recent years has been observed in both summer and winter. While the Taree connection points are currently a winter peaking, the implication of the faster growth in summer is that they will shift to become summer peaking if current trends continue. Historical behaviour of maximum demand at Taree 23