Evaluation and modelling of demand and generation at distribution level for Smart grid implementation Dr.Haile-Selassie Rajamani Senior Lecturer Energy and Smart Grid Research Group University of Bradford, UK
Group Expertise / Areas Modelling and simulation of power systems Artificial intelligence and heuristic optimization techniques Smart grid distribution technology Embedded Renewable Energy generation & embedded storage Electric vehicles integration into grid Wireless communication networks for smart grids Security in Smart grids Pricing strategies in deregulated energy markets Demand side management and demand response Energy policy
Structure Background Development of models Targeted interventions Pricing issue Development of a criteria Local demand under pricing schemes Key points
The Smart Grid
Why is there interest in distribution side? Deregulation of the industry move away from single central planning unit Energy Security spreading supply Approaches for CO2 emissions reduction targets Rising cost of fossil fuels makes some of the other options feasible renewables Technology developments SMART Grid, affordable local generation options, advanced control electronics, market mechanisms Private investment
UK Energy consumption over time (DECC)
Distribution side aspects Embedding renewable energy more common Embedding storage to some extent Improving efficiency much effort in insulation Purchasing market leverage, green energy deals, etc Demand side response (DSR) Some effort
Demand Side Response (DSR) Change in load characteristics on a daily basis behaviour change Change in load due to sudden changes in supply e.g due to embedded generation
Drivers for Demand side response in UK Electric vehicles Driverless cars being introduced in UK Increased embedded generation dependent on weather Maximising existing infrastructure Heat pumps, air-conditioning on the increase globally Storage options developing Involvement of private investment Reduction in investment in supply provision.
Load shifting initiatives Peak and off peak pricing: issues of how to change behaviour, length of time, pricing, etc Critical peaks: short term, not regular. Can be effective. Automated shifting of load: air-conditioning (USA) etc. Enabling technology is helpful. Override facility issues, food safety in fridges etc. No real-time Time of Use pricing.
Some aspects of Demand side response Consumers more likely to change behaviour in response to financial incentives (Economy 7 tariff lower price 12-6am) Consumers also change behaviour with better information Most impact where there are flexible energy units such as electric heating, air-conditioning. (Economy 7 tariff)
Distribution side Energy research Simulations Historical, Demographical Business case around government initiatives Case studies Trails in different countries USA, UK, Germany, Nordic countries etc Investigating particular aspects Financial incentives Information / educational Technology Technology and business development Tariff schemes, capital grants etc
Modelling of a local load National projections exist based on historical consumption Good for supply planning purposes Lack detail Case studies Detailed measurements of sample households Metering data Too detailed / not detailed enough Simulation models Appliance characteristics Behaviour patterns
Community Demand Profile Generator Demographic information: The information on the type of households such as the number of adults, working people, and number of children. Annual electricity consumption patterns: Includes ownership level of appliances, and total energy consumption of certain appliances. Daily Occupancy information: This is the behaviour of occupants in households with respect to their usage of appliances and lighting on a daily basis.
Framework
Type of Households in UK Type of Household Percentage Share (%) Single adult without children 15 Single adult with children 6 Single retired adult 15 Two adults without children 24 Two adults with children 19 Two retired 9 Two adults or more without children 8 Two adults or more with children 4 Total (%) 100
UK Appliance demand decc
Projection of a Community (Number of households) 120 100 80 60 40 20 0 1 working adult 1retired adult 1 adult with children 2 working adults 2 adults with children 2 retireds 3 adults or more 3 adults or more with children
00:00 00:30 01:00 01:30 02:00 02:30 03:00 03:30 04:00 04:30 05:00 05:30 06:00 06:30 07:00 07:30 08:00 08:30 09:00 09:30 10:00 10:30 11:00 11:30 12:00 12:30 13:00 13:30 14:00 14:30 15:00 15:30 16:00 16:30 17:00 17:30 18:00 18:30 19:00 19:30 20:00 20:30 21:00 21:30 22:00 22:30 23:00 23:30 Elec. Cons. (kwh) Daily consumption for 2 Adults, weekday 90 75 Minimum Maximum 60 Average 45 30 15 0 Time
Local Community Energy usage who contributes most?
Interventions Renewable Energy Storage options Load shifting Energy efficiency measures Behaviour modification / education We need to understand these.
How do we evaluate? Standard business practice methodology. Short term based on current prices Economic models Often too lumped for a small community Not able to account easily for technological changes Market prices vary significantly in a free market
Oil price changes 1981 2007 (oil)
UK Electricity Market Wholesale Market Generation Contracts between companies Spot difference market Retail Market Domestic customer bills Commercial customer bills
UK System buy prices for one week
00:00 00:30 01:00 01:30 02:00 02:30 03:00 03:30 04:00 04:30 05:00 05:30 06:00 06:30 07:00 07:30 08:00 08:30 09:00 09:30 10:00 10:30 11:00 11:30 12:00 12:30 13:00 13:30 14:00 14:30 15:00 15:30 16:00 16:30 17:00 17:30 18:00 18:30 19:00 19:30 20:00 20:30 21:00 21:30 22:00 22:30 23:00 23:30 Demand (MW) UK System demand over 24 hrs two days 60000 52000 Monday Friday 44000 36000 28000 20000 Time
System Buy Price ( /MWh) System Buy Price ( /MWh) System Buy Price ( /MWh) System Buy Price ( /MWh) 400 System Buy Price (SBP), Monday 400 System Buy Price (SBP), Tuesday 350 350 300 250 200 150 100 50 0 30 35 40 45 50 55 60 Demand (GW) 300 250 200 150 100 50 0 30 35 40 45 50 55 60 Demand (GW) System Buy Price vs. demand On different days 400 350 300 250 System Buy Price (SBP), Wednesday 400 350 300 250 System Buy Price (SBP), Thursday 200 200 150 150 100 100 50 50 0 30 35 40 45 50 55 60 Demand (GW) 0 30 35 40 45 50 55 60 Demand (GW)
SBP ( /MWh) System buy price vs demand combined 400 350 300 250 200 150 100 50 0 20 25 30 35 40 45 50 55 60 Demand (GW)
Simple model of system buy price vs demand PU
Pricing aspects Range of prices indicates that peak price costs the supplier almost 2 p.u. Generally the most efficient generators are switched on first, then the more inefficient ones. Also indicative of the capital costs for meeting peak demand.
Community Electricity Cost under the three pricing ranges
Key points Actual maximum cost does not occur at maximum load Only gives indication of cost of electricity supply Provides a basis for evaluating an intervention behaviour and also cost.
How does this fit in with Smart Grid?
New requirements Need to have some way of establishing the relative cost of demand and supply over a day, over weeks, and over months. Need for service provider to identify consumer behaviour, and opportunities in order to develop market instruments. Need to manage loads remotely, and also to monitor them. Consumer needs to be able to participate ultimately in a financial manner.
Some relevant areas What are the electrically energy intense chemical engineering processes that can participate in Smart Grid in such a way as to give mutual benefit? What kind of intelligent elements are needed to enable such processes to be integrated into the Smart Grid or into local microgrids? Smart buildings for smart grid integration Development of reward mechanisms etc. Driverless cars virtually linked to get home quickly!
Thank you
Electricity Cost under three price model options and actual data
23:00 00:00 2.2 01:00 21:00 22:00 2 1.8 1.6 1.4 02:00 03:00 National demand and price (medium) 20:00 1.2 1 04:00 0.8 19:00 0.6 05:00 0.4 Measure of System cost pu 18:00 0.2 0 06:00 Electricity Cost pu 17:00 07:00 National Demand pu 16:00 08:00 15:00 09:00 14:00 National Demand (pu) Measure of System Cost (pu) 13:00 Electricity Costl (pu) 12:00 11:00 10:00
Average energy consumption of electrical appliances in the UK Appliance Average annual consumption per household (kwh/day) Average annual consumption per capita (kwh/day) Electric hob 1.33 0.39 Electric oven 0.74 0.22 Microwave Oven 0.23 0.07 Refrigerator 0.82 0.33 Freezer 1.9 0.55 Television 0.91 0.27 Video recorder 0.3 0.09 Dishwasher 1.72 0.48 Washing Machine 0.8 0.2 Tumble Driers 0.78 0.28 Electric Kettle 0.78 0.28 Iron 0.3 0.09 Vacuum Cleaner 0.15 0.04 Miscellaneous 1.1 0.33 Computers 0.5 0.3
UK Energy end use (2012 DECC)