RESOURCE ADEQUACY AND RELIABILITY IMPACT OF DEMAND RESPONSE IN A SMART GRID ENVIRONMENT
Rahmatallah Poudineh Department of Economics, Heriot-Watt University, UK
Phone:0044(0)1314513273, Email:
Tooraj Jamasb Department of Economics, Heriot-Watt University, UK
Phone:+44 (0) 131 451 3482, Email:
- Introduction
Demand response can be seen as one of the many resources to satisfy the increasing demand for electricity. In addition to providing capacity for resource adequacy and planning purposes, capacity and ancillary services provided by demand response helps ensure resource adequacy while providing operators with additional flexibility in maintaining operating reliability. However, demand Response is still a relatively new resource thus; it is necessary to measure its performance in order to better understand its benefits and impacts on reliability. Better performance measures will also help develop industry confidence in demand response use. In practice; demand response is defined as the change in electricity consumption pattern by the end user consumer in response to the changes in the price of electricity or other financial incentives. Under the current grid condition, most electricity customers see electricity rates that are based on average electricity costs and bear little relation to the true production costs of electricity as they vary over time. In a smart grid environment however; it is expected that demand response improves resource-efficiency of electricity production due to closer alignment between customers’ electricity prices and the value they place on electricity.
On pursuing this path, this study focuses primarily on estimating the direct impact of reductions in peak loads and improvement of reliability and resource adequacy standard.
- Methodology
Our approach is based on the stochastic programming techniquethatcan be used to formulate and solve problems with uncertain parameters. The objective of the model is to maximize the utility of three different types of consumers (i.e. a household user, a commercial user and an industrial user), that are exposed to real time pricing,subject to a minimum daily energy-consumption level, maximum and minimum hourly load levels, and ramping limits on such load levels. Price uncertainty is modelled through robust optimization techniques. Those three typical consumers are expected to represent the current electricity consumption spectrum.
- Results and Conclusion
Power system stability can be enhanced by the appropriate use of the responsive loads. The results show,although demand response is not the only reliability resource, but in most cases it is better than generation. This is because some loads can respond muchfaster toreliability events than most generators which make them more valuable than generation.On the other hand, reducing the peak demand has the added benefit that the reserve margin is reduced as well.Encouraging responsive loadsto provide reliability services, including spinning reserve, can free up generating capacityto provide energy.
The results also show that reliability enhancement of demand response can only be extracted up to the level of flexible users over the consumers’ spectrum.Thus, there is an optimum level of demand response. This means beyond a certain level the cost of improving reliability through demand response outweigh its benefits.
- References
Sioshansi, R (2010) “Evaluating the impacts of real-time pricing on the cost and value of wind generation,” IEEE Trans. Power Syst., vol. 25, pp. 741–748.
Mohsenian-Rad, A.H and Leon-Garcia, A (2010) “Optimal residential load control with priceprediction in real-time electricity pricing environments,” IEEE Trans. Smart Grid, vol. 1, no. 2, pp. 120–133
Conejo,A.J, Morales, J.M, and Baringo,L. (2010) “Real-time demand response model,” IEEE Trans. Smart Grid, vol. 1, no. 3, pp. 236– 242
J. Kim, S. and Giannakis,G.B, (2011) “Efficient and scalable demand response for the smart power grid,” in Proc. 4th Int. Workshop Computational Advances in Multi-Sensor Adaptive Processing, San Juan, Puerto Rico.