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辅导案例-ECON 2209

By May 15, 2020No Comments

1 Major Course Assignment ECON 2209- Business Forecasting Term 1, 2020 The Australian Energy Market Operator (AEMO) is the national energy market operator and is responsible for delivering integrated, secure and cost effective energy supply in New South Wales, Victoria, South Australia, Queensland and Tasmania. AEMO operates the electricity and gas markets systems and also provides planning advice to energy generation, transmission and distribution businesses in these five States. One of the key responsibilities of AEMO is to maintain supply and demand balance in the electricity sector of the National Energy Market (NEM) particularly in the generation and bulk transmission sectors and prepares annual electricity and gas statement of opportunities- ESOO and GSOO in order to attract investments in these sectors. AEMO publishes historical power demand and spot price (daily and half hourly) data for each jurisdictions, that is, all NEM States. See AEMO’s website For the major course project for ECON 2209 you are required to: I. Construct an Excel spreadsheet with historical data for the 10 year period – from 1 January 2010 to 31 December 2019 in respect of the jurisdiction of New South Wales: 1. Daily energy (MWh); 2. Daily peak demand (MW); 3. Daily average spot price 4. Daily maximum and minimum temperatures for each weather station 5. Daily 9 am and 3pm relative humidity for each nominated weather stations. II. Undertake a temperature correction analysis for summer peak demand in each year (1 Nov to 31 March excluding week-end days and public holidays) on the basis of a 10 percent probability of exceedence maximum temperature and long term weighted average relative humidity. III. Construct a historical annual temperature corrected summer peak demand series and an annual energy demand series. 2 IV. Formulate a reliable temperature corrected summer peak demand model using multiple regression technique. Potential predictor variables are annual NSW real Gross State Product (GSP), real household disposable income, interest rates, retail/spot prices of electricity, air conditioner penetration (25% of the households in 1995, 50% in 2000, 65% in 2005, 70% in 2010 and 80%% in 2018). V. Formulate a reliable annual energy demand model using multiple regression technique. Potential predictor variables are Real NSW GSP, real household disposable income, interest rates and annual total cooling degree days (CDD) and annual total heating degree days(HDD) threshold temperature being 21 degree centigrade and 12 degree centigrade respectively. Note: Historical data for macro-variables are available from the Australian Bureau of Statistics (ABS) website: Historical weather data should be available from the Bureau of Meteorology (BoM) website: . VI Acquire macro projections from NSW State Treasury or other sources for at least three economic and demographic scenarios (High, Most Likely and Low). Using long term average values for weather variables (real average retail electricity price projections will be provided) produce summer peak demand and annual energy demand in NSW ten years out for each of these scenarios, incorporating post modelling adjustments for roof top PV solar penetrations and energy efficiency improvements. VII. Provide comments on demand and supply balance for the NSW power system particularly in relation to generation and bulk transmission sectors. For the current capacity information refer to AEMO and NSW Transgrid ( websites. Maximum marks:17 Marking Scheme: a) Use and documentation of appropriate demand modelling and forecasting methods using appropriate data (4 marks); b) Quality of desk research (5 marks); 3 c) Quality of coloured graphs and tables (including scatter plots) (2 marks); d) Appropriate style of business report, quality and correctness of English business language (2 marks); e) Level of understanding and interpretation of the topic, argument used and conclusion drawn (2 marks); and f) Peer assessment (2 marks). Note: 1. This assignment can be undertaken in a group of up to four students. 2. Provide a cover page- type the names of students and student IDs. Signatures of students are required as well. 3. Peer assessment report must be attached with the assignment. (see the course outline) 4. Use appropriate referencing format. 5. The maximum length of the assignment is strictly 12 pages including bibliography and appendices. 6. The time deadline for submission of both electronic and paper versions of the assignment is 6 pm 23 April 2020. The paper version and the electronic version must be identical.


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