Optimal Dispatch Model for Demand Response Aggregators
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The necessity to seamlessly integrate emerging smart grid (SG) technologies to the electric distribution system has encouraged the development of demand-side management (DSM) and Demand Response (DR) programs. In particular, DR aggregators will play an important role in the new operational paradigm of SG.
To propose a new three-phase optimal dispatch model for multiple DR aggregators. The model can consider several DR service providers by means of the explicit inclusion of their characteristics, in the form of cost functions and capacity, in an optimal dispatch model for DR support at the distribution system level. Hence, this proposal helps to eliminate any possible uncertainty about the provision of DR services by improving the traditional hierarchical scheme adopted based on prices issued by the independent system operator.
By means of the unbalanced distribution system modeling, DR involvement of single- and three-phase consumers is considered avoiding aggravating the asymmetric balancing between phases, as opposed to traditional positive-sequence DR approaches. The model is implemented and solved combining the two state-of-the-art computational tools, Matlab® and OpenDSS. The former is used to solve the optimization problem, whereas the latter is used to perform numerical simulations of three-phase unbalanced power flow; both tools allow a straightforward model implementation resulting in a tool easily modified and updated.
The effectiveness of the proposed approach is numerically demonstrated using the IEEE 13- and 123-node test feeders, in which undesirable operating scenarios are corrected by the implementation of the optimal dispatch of DR resources in very short computational times.
Based on the results, it is shown how the ISO is capable to request DR considering several aggregators competing at the distribution system level. Finally, the loss reduction has been included in the objective function, showing that the proposal optimally dispatches the DR aggregators to conveniently minimize the ISO’s operational costs.
KeywordsSmart grids Demand side management Demand response Optimal dispatch Aggregators
Publication charges were supported by the University of Guanajuato PFCE 2018.
- 1.Energy Independence and Security Act of 2007 (EISA 2007). https://www.congress.gov/bill/110thcongress/house-bill/6. Accessed 18 Dec 2018
- 2.Brown HE, Suryanarayanan S (2009) A survey seeking a definition of a smart distribution system. In: Proceedings of North American Power Symp., Starkville, MS, USA Oct 2009Google Scholar
- 3.Hamidi V, Smith KS, Wilson RC (2010) Smart grid technology review within the transmission and distribution sector. In: Proceedings of IEEE PES innovative smart grid technologies Conf. Europe, Gothenburg, SE, Oct 2010Google Scholar
- 4.Geidl M, Koeppel G, Favre-Perrod P, Klockl B, Andersson G, Frohlich K (2007) Energy hubs for the future. In: IEEE Power and energy mag., vol. 5, no. 1, pp. 24–30, Jan–Feb 2007Google Scholar
- 5.Broehl JH et al (1984) Demand side management vol. 1–3. Electric Power Research Institute, final project report EPRI EA/EM-3597, Aug 1984Google Scholar
- 6.Palensky P, Dietrich D (2011) Demand side management: demand response, intelligent energy systems, and smart loads. In: IEEE Trans. ind. informat, vol. 7, no. 3, Aug 2011Google Scholar
- 7.U.S. Dept. Energy (2006) Benefits of demand response in electricity markets and recommendations for achieving them, report to the United States Congress, Washington, D.C.Google Scholar
- 8.Han J, Piette M (2008) Solutions for summer electric power shortages: demand response and its applications in air conditioning and refrigerating systems. Refrig Air Cond Electr Power Mach 29(1):1–4Google Scholar
- 9.Vardakas JS, Zorba N, Verikoukis CV (2015) A survey on demand response programs in smart grids: pricing methods and optimization algorithms. In: IEEE commun. surveys tutorials, vol. 17, no. 1, pp 152–178, first quarter 2015Google Scholar
- 11.U. S. Dept. Energy. Demand response measurement and verification. https://www.smartgrid.gov/files/demand-response.pdf. Accessed 18 Dec 2018
- 13.Saebi J, Javidi MH (2012) Implementation of demand response in different control strategies of smart grids. In: Proceedings of 2nd Iranian conf. smart grids, Tehran, IRN, May 2012Google Scholar
- 14.Lee WJ, Quilumba FL, Shi J, Huang SH (2012) Demand response—an assessment of load participation in the ERCOT nodal market. In: Proceedings of IEEE Power and Energy Society-general meeting, San Diego, CA, USA, July 2012Google Scholar
- 15.IESO (2016) Demand response auction. http://www.ieso.ca/Pages/Ontario’s-Power-System/Reliability-Through-Markets/Demand-Response.aspx. Accessed Jul 2016
- 16.FERC (2008) Wholesale competition in regions with organized electric markets. https://www.ferc.gov/whats-new/comm-meet/2008/101608/E-1.pdf. Accessed Oct 2008
- 20.Fu W (2000) Risk assessment and optimization for electric power systems. Ph.D. dissertation, Iowa State Univ., Ames, IAGoogle Scholar
- 21.Lami B (2012) Operational risk assessment of power systems with distributed energy resources using minimal cut sets. M.S. thesis, Univ. of Waterloo, Waterloo, ON, CAGoogle Scholar
- 22.The Mathworks Inc. (2016) Optimization toolbox (R2014a). https://www.mathworks.com. Accessed 18 Dec 2018
- 23.OpenDSS program (2016). https://sourceforge.net/projects/electricdss/. Accessed 18 Dec 2018
- 24.Strbac G, Farmer ED, Cory BJ (1996) Framework for the incorporation of demand-side in a competitive electricity market. In: Proceedings IEE generation, transmission and distribution, vol. 143, no. 3, pp 232–237, May 1996Google Scholar
- 25.Zhu Q, Sauer P, Baar T (2013) Value of demand response in the smart grid. In: Proceedings of IEEE power and energy conf. at Illinois, Champaign, IL, USA, Feb 2013Google Scholar
- 26.Oh H, Thomas RJ (2008) Demand-side bidding agents: modeling and simulation. IEEE Trans Power Syst 23(3):1050–1056Google Scholar
- 28.Chen C, Kishore S, Wang Z, Alizadeh M, Scaglione A (2012) How will demand response aggregators affect electricity markets?—a Cournot game analysis. In: Proceedings of 5th int. symp. on commun. control and signal processing, Rome, IT, May 2012, pp 1–6Google Scholar
- 32.Montenegro D, Hernandez M, Ramos GA (2012) Real time OpenDSS framework for distribution systems simulation and analysis. In: Proceedings of IEEE PES transmission and distribution: Latin America Conf., Montevideo, UY, Sep 2012, pp 1–5Google Scholar