Demand Side Management Documentation

This documentation explains the Demand Side Management feature of urbs. With it, one can model time variant Demand Side Management Up/Downshift in a concrete energy system, for example, smart grid of a city.

Introduction

The DSM up/downshifts are closely related to commodities, which are given by default in the urbs with their energy content (MWh). The size of the modelled market has to be considered small relative to the surrounding market. To use this feature, the excel input file needs an additional Demand Side Management sheet with the five parameters containing the columns delay, eff, recov, cap-max-do and cap-max-up, which are used in DSM constraints as technical parameters. For a more detailed description of the implementation have a look at the mathematical definitions in the Mathematical Documentation, section Demand Side Management Constraints.

Exemplification

This section contains prototypical scenarios illustrating the system behaviour with time variant DSM up/downshifts. In this part there is an island as an example named Greenland, which composed of three sites Mid, North, and South. Between the three sites most of the electricity from South has to be transported to supply Mid. The electricity of North is relatively independent of the other two sites.

When do the electricity DSM downshifts appear in the process?

• it is necessary to constraint the whole system with DSM downshifts, if the demand is greater than the total output capacity.
• it is profitable to constraint the whole system with DSM downshifts, if the commodity begin to show upward trend till the peak value.

When appears the electricity DSM upshifts in the process?

• it is possible and profitable to constraint the whole system with DSM upshifts, if the demand is lesser than the total output capacity and the commodity begin to show downward trend till the valley value.

High Maximal Up/Downshift Capacity

All process, transmission and storage capacities are predetermined and constant.

The following scenario illustrates the energy balance of the South of greenland. It has a demand of 50-100 GW that is supplied by a 50 GW photovoltaics plant and a 50 GW wind plant. In addition a 50 GW transmission cable exports electricity, which connects the Mid of island with the grid of South. Both capacities and prices are fix. Because of the meteorological effects on Photovoltaics plants, the timesteps began at the 3000th hour of the year, which was also the beginning of the summer.

Scenario All Together: Elec in South

Process	eff	inst-cap	inst-cap-out	fuel-cost	var-cost	total-var-cost
Photovoltaics	1.00	0	50000	0	0	0
Wind plant	1.00	0	100000	0	0	0
Purchase	1.00	0	1500	15/45/75	0	15/45/75
Feed-in	1.00	0	1500	15/45/75	0	15/45/75

DSM in South

Site	Commodity	delay	eff	recov	cap-max-do	cap-max-up
South	Elec	16	0.90	1	2000	2000

The modelled timesplan lasts 7 days with five parameters from DSM sheet in greenland-south.xlsx. In the first ten hours of day 1 the electricity power is at a high level, because the supply is much less than the demand. So the DSM begins with downshifts. But the situation will change into opposite direction over time. After the supply exceeds, the demand the DSM upshifts appears to take place of downshifts. How much electricity can the photovoltaics plants and awind plants generate all depending on the weather conditions. The wind plants works the whole day 24 hours, as long as the wind blows strongly enough. But photovoltaics plants generates electricity only in the daytime, that is why the parameter delay is set to 16 hours. It just coincides the time in one day, that is covered by the sunshine. Before the second day the wind blows strongly enough, so that the surplus of wind plant generated electricity is converted into storage. From the 3rd day the wind production decreases, and the electricity of storage has to be taken out to meet the demand. At the midnight of the 5th day electricity capacity come to the lowest point of all, and the output and input keep nearly in balance. Not only the frequency of scenario_base up/downshifts, but also the amount of times of up/downshifts will decrease correspondingly. There is relative more volatility of electricity capacity in the seven days simulation than it without DSM.

If the commodity stock prices, global CO2 limit and maximum installable capacity in runme.py are not changed, and just only consider the scenario_base, it will be more clearly to show how the DSM affects the electricity commodities.

Note

For trial e.g. of the result of higher Demand Side Management this greenland-south.xlsx is the input file used for this scenario.

Low Maximal Up/Downshift Capacity

All process, transmission and storage capacities are predetermined and constant.

For the second scenario, the North of greenland will replaced the South. Compared to the South, the electricity supply of North is relatively simple and independent. It has a demand of 10000-15000 MW, and the supply is dominated by wind plants. Additionally there is about 2500 MW needed to be provided by Purchase.

Scenario All Together: Elec in North

Process	eff	inst-cap	inst-cap-out	fuel-cost	var-cost	total-var-cost
Photovoltaics	1.00	0	3000	0	0	0
Wind plant	1.00	0	15000	0	0	0
Gas plant	0.60	0	0	27	1.60	28.60
Purchase	1.00	1500	1500	15/45/75	0	15/45/75
Feed-in	1.00	2500	2500	15/45/75	0	15/45/75

DSM in North

Site	Commodity	delay	eff	recov	cap-max-do	cap-max-up
North	Elec	8	1.00	1	500	500

The modelled timesplan lasts also 7 days with five parameters from DSM sheet in greenland-north.xlsx. The electricity supply of North is dominated by wind plants. The wind plants works for 24 hours in one whole day, and the wind power strong or weak has nothing to do with the change of time. So the parameter delay is set to 8 hours. Because the peak value of the output of North is just close to 15 GW, the cap-max-do and cap-max-up are set to 500 MW, which is a quarter of South’s. The electricity in the first four days, which is generated by wind plants, keeps at a higher level. That is why the up/downshifts appear frequently, regularly, and alternately during this time. But in the last three days the wind power gets lower, and the electricity of storage has to be taken out to meet the demand. Then during the three days downshifts dominate in most case. With DSM up/downshifts intelligent allocation of electricity resources is required to avoid the shortage of electricity supply during peak hours and the overcapacity in the usual time.

Note

For trial e.g. of the result of lower Demand Side Management this greenland-north.xlsx is the input file used for this scenario.

No Maximal Up/Downshift Capacity

All process, transmission and storage capacities are predetermined and constant.

The last scenario illustrates the energy balance of the Mid of greenland. It has a demand of 50-70 GW that is mostly supplied by a 50 GW transmission, which come from South. In addition, a 13 GW wind plant and 16 GW Photovoltaics plant has made a contribution to the whole electricity system of Mid.

Scenario All Together: Elec in Mid

Process	eff	inst-cap	inst-cap-out	fuel-cost	var-cost	total-var-cost
Photovoltaics	1.00	15000	16000	0	0	0.00
Wind plant	1.00	0	13000	0	0	0.00
Gas plant	0.60	0	8000	27	1.60	28.60
Hydro plant	1.00	0	1400	6	1.40	7.40
Lignite plant	0.40	0	60000	0	0.60	0.60
Biomass plant	0.35	0	5000	6	1.40	7.40

DSM in Mid

Site	Commodity	delay	eff	recov	cap-max-do	cap-max-up
Mid	Elec	0	1.00	1	0	0

The Mid gets so adequate electricity import from the South, that commodity of the Mid per unit time is far greater than maximal up/downshifts capacity. That means it is meaningless for the setting of DSM faced with so enormous commodity, which is far beyond the controllable range. Supposed that the Mid is the city center, the largest energy customer, not the energy producer, and then there is huge infrastructure inside, such as public traffic, hospital, and communication system, which have to be supplied for 24 hours one day. That’s why the parameters delay, cap-max-do and cap-max-up are set to 0. It means that there was no more DSM in the electricity system of Mid to constraint the commodities.

Note

For trial e.g. of the result of no Demand Side Management this greenland-mid.xlsx is the input file used for this scenario.