Optimal Subhourly Electricity Resource Dispatch Under Multiple Price Signals With High Renewable Generation Availability

This paper proposes a system-wide optimal resource dispatch strategy that enables a shift from a primarily energy cost-based approach, to a strategy using simultaneous price signals for energy, power and ramping behavior. A formal method to compute the optimal sub-hourly power trajectory is derived for a system when the price of energy and ramping are both significant. Optimal control functions are obtained in both time and frequency domains, and a discrete-time solution suitable for periodic feedback control systems is presented. The method is applied to North America Western Interconnection for the planning year 2024, and it is shown that an optimal dispatch strategy that simultaneously considers both the cost of energy and the cost of ramping leads to significant cost savings in systems with high levels of renewable generation: the savings exceed 25% of the total system operating cost for a 50% renewables scenario.

[1]  Joseph H. Yan,et al.  What objective function should be used for optimal auctions in the ISO/RTO electricity market? , 2006, 2006 IEEE Power Engineering Society General Meeting.

[2]  Thomas E. Carroll,et al.  Generalized aggregation and coordination of residential loads in a smart community , 2015, 2015 IEEE International Conference on Smart Grid Communications (SmartGridComm).

[3]  Ned Djilali,et al.  Transactive control of fast-acting demand response based on thermostatic loads in real-time retail electricity markets , 2018 .

[4]  M. Markoff,et al.  Impact of climate change on Pacific Northwest hydropower , 2008 .

[5]  Benjamin A Carreras,et al.  Complex systems analysis of series of blackouts: cascading failure, critical points, and self-organization. , 2007, Chaos.

[6]  G. Shrestha,et al.  Strategic self-dispatch considering ramping costs in deregulated power markets , 2004 .

[7]  K. M. Muttaqi,et al.  Mitigation of Rooftop Solar PV Impacts and Evening Peak Support by Managing Available Capacity of Distributed Energy Storage Systems , 2013, IEEE Transactions on Power Systems.

[8]  A. Bagchi,et al.  Economic dispatch with network and ramping constraints via interior point methods , 1998 .

[9]  Varun Rai,et al.  Solar Valuation and the Modern Utility's Expansion into Distributed Generation , 2014 .

[10]  Makoto Tanaka.  Real-time pricing with ramping costs: A new approach to managing a steep change in electricity demand , 2006 .

[11]  Aleksandra Roos,et al.  Modeling Consumer Flexibility of an Aggregator Participating in the Wholesale Power Market and the Regulation Capacity Market , 2014 .

[12]  Nivad Navid,et al.  Market Solutions for Managing Ramp Flexibility With High Penetration of Renewable Resource , 2012, IEEE Transactions on Sustainable Energy.

[13]  E. Ela,et al.  Effective ancillary services market designs on high wind power penetration systems , 2012, 2012 IEEE Power and Energy Society General Meeting.

[14]  Ruisheng Diao,et al.  Planning for variable generation integration through balancing authorities consolidation , 2012, 2012 IEEE Power and Energy Society General Meeting.

[15]  Ned Djilali,et al.  Robust response to hydro-climatic change in electricity generation planning , 2015, Climatic Change.

[16]  Yannick Perez,et al.  Aggregation of demand side flexibility in a smart grid: A review for European market design , 2015, 2015 12th International Conference on the European Energy Market (EEM).

[17]  Ned Djilali,et al.  Interconnection-wide hour-ahead scheduling in the presence of intermittent renewables and demand response: A surplus maximizing approach , 2017 .

[18]  Daniel S. Kirschen,et al.  Estimating the Spinning Reserve Requirements in Systems With Significant Wind Power Generation Penetration , 2009, IEEE Transactions on Power Systems.

[19]  Godfrey Boyle,et al.  Renewable Electricity and the Grid : The Challenge of Variability , 2007 .

[20]  Paul Denholm,et al.  Overgeneration from Solar Energy in California - A Field Guide to the Duck Chart , 2015 .

[21]  Miao He,et al.  Multiple timescale dispatch and scheduling for stochastic reliability in smart grids with wind generation integration , 2011, 2011 Proceedings IEEE INFOCOM.

[22]  Madeleine Gibescu,et al.  Local market framework for exploiting flexibility from the end users , 2016, 2016 13th International Conference on the European Energy Market (EEM).

[23]  Munish K. Chandel,et al.  The potential impacts of climate-change policy on freshwater use in thermoelectric power generation , 2011 .

[24]  F. Alvarado,et al.  Management of multiple congested conditions in unbundled operation of a power system , 1997 .

[25]  H. Buttin,et al.  Scheduling demand response and Smart Battery flexibility in a market environment: Results from the Reflexe demonstrator project , 2015, 2015 IEEE Eindhoven PowerTech.

[26]  Jian Ma,et al.  Operational Impacts of Wind Generation on California Power Systems , 2009, IEEE Transactions on Power Systems.

[27]  Yun Tiam Tan,et al.  Co-optimization of Energy and Reserve in Electricity Markets with Demand-side Participation in Reserve Services , 2006, 2006 IEEE PES Power Systems Conference and Exposition.

[28]  Yang Shi,et al.  H2-optimal transactive control of electric power regulation from fast-acting demand response in the presence of high renewables , 2017 .