Abstract
In the economic dispatch problem, the objective is to supply the demand at least cost. It is a well known fact that the solution to this problem corresponds to the generation settings that lead to equal marginal/incremental costs for all generators and for which the total generation output is equal to the total load. This provides a way to determine the solution to the economic dispatch problem by simply considering the marginal cost curves of the generators and the demand curve. In this paper, we integrate the effect of storage into this marginal cost analysis. This requires the consideration of conversion losses occurring in the storage converter, the extension to a multi-step optimization problem and the limitations imposed by the limited energy storage capacity. A method is provided by which the optimal generation and storage settings can be determined by only using marginal cost curves and the intersections thereof. Simulation results provide insights into how the theory translates into solving a multi-step optimization problem including storage.
Similar content being viewed by others
References
Awad, A., Fuller, J., EL-Fouly, T., Salama, M.: Impact of energy storage systems on electricity market equilibrium. IEEE Trans. Sustain. Energy 5(3), 875–885 (2014). doi:10.1109/TSTE.2014.2309661
Baone, C., DeMarco, C.: Distributed control design to regulate grid frequency and reduce drivetrain stress in wind systems using battery storage. In: American Control Conference (ACC), pp. 1368–1375 (2012). doi:10.1109/ACC.2012.6315217
Bergen, A., Vittal, V.: Power Systems Analysis. Prentice Hall, USA (1999)
Delille, G., Francois, B., Malarange, G.: Dynamic frequency control support by energy storage to reduce the impact of wind and solar generation on isolated power system’s inertia. IEEE Trans. Sustain. Energy 3(4), 931–939 (2012). doi:10.1109/TSTE.2012.2205025
Dutta, S., Sharma, R.: Optimal storage sizing for integrating wind and load forecast uncertainties. In: Innovative Smart Grid Technologies (ISGT) (2012). doi:10.1109/ISGT.2012.6175721
Hopkins, M., Pahwa, A., Easton, T.: Intelligent dispatch for distributed renewable resources. IEEE Trans. Smart Grid 3(2), 1047–1054 (2012). doi:10.1109/TSG.2012.2190946
Hug-Glanzmann, G.: Coordination of intermittent generation with storage, demand control and conventional energy sources. In: VIII Bulk Power System Dynamics and Control (iREP) Symposium (2010). doi:10.1109/IREP.2010.5563304
Khalid, M., Savkin, A.: Model predictive control based efficient operation of battery energy storage system for primary frequency control. In: 11th International Conference on Control Automation Robotics Vision (ICARCV), pp. 2248–2252 (2010). doi:10.1109/ICARCV.2010.5707855
Kirschen, D., Strbac, G.: Fundamentals of Power System Economics. Wiley, New York (2004)
Li, N., Hedman, K.: Economic assessment of energy storage in systems with high levels of renewable resources. IEEE Trans. Sustain. Energy PP(99), 1–9 (2014). doi:10.1109/TSTE.2014.2329881
Mayhorn, E., Kalsi, K., Elizondo, M., Zhang, W., Lu, S., Samaan, N.,Butler-Purry, K.: Optimal control of distributed energy resources using model predictive control. In: IEEE Power and Energy Society General Meeting (2012). doi:10.1109/PESGM.2012.6345596
Megel, O., Mathieu, J., Andersson, G.: Maximizing the potential of energy storage to provide fast frequency control. In: Innovative Smart Grid Technologies Europe (ISGT) (2013). doi:10.1109/ISGTEurope.2013.6695380
Miao, L., Wen, J., Xie, H., Yue, C., Lee, W.: Coordinated control strategy of wind turbine generator and energy storage equipment for frequency support. In: IEEE Industry Applications Society Annual Meeting (2014). doi:10.1109/IAS.2014.6978370
Parvania, M., Fotuhi-Firuzabad, M., Shahidehpour, M.: Comparative hourly scheduling of centralized and distributed storage in day-ahead markets. IEEE Trans. Sustain. Energy 5(3), 729–737 (2014). doi:10.1109/TSTE.2014.2300864
Silva-Monroy, C., Watson, J.P.: Integrating energy storage devices into market management systems. Proc. IEEE 102(7), 1084–1093 (2014). doi:10.1109/JPROC.2014.2327378
Teleke, S., Baran, M., Bhattacharya, S., Huang, A.: Rule-based control of battery energy storage for dispatching intermittent renewable sources. IEEE Trans. Sustain. Energy 1(3), 117–124 (2010). doi:10.1109/TSTE.2010.2061880
Torres, M., Lopes, L., Moran, T., Espinoza J.: Self-tuning virtual synchronous machine: a control strategy for energy storage systems to support dynamic frequency control. IEEE Trans. Energy Convers. 29(4), 833–840 (2014). doi:10.1109/TEC.2014.2362577
Zhu, D., Hug, G.: Robust control design for integration of energy storage into requency regulation. In: Innovative Smart Grid Technologies Europe (ISGT) (2012)
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Hug, G. Integration of optimal storage operation into marginal cost curve representation. Energy Syst 7, 391–409 (2016). https://doi.org/10.1007/s12667-015-0163-7
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s12667-015-0163-7