Resource Complementarity as Criterion for Siting Renewable Energy Generation Assets

This paper tackles the topic of siting intermittent renewable energy assets, e.g., wind and solar PV. For this purpose, an integer programming formulation is devised to leverage spatiotemporal complementarity of dispersed renewable resources in selecting the most suitable locations for electricity generation. The applicability of the model, designed to make use of vast amounts of climatological data across large geographical scopes, is tested on a five-year horizon case study of Europe and North Africa, including 4,500 potential deployment sites. Results show that the method identifies deployment patterns drastically reducing the intermittent feed-in variability, as well as the probability of low-generation events. In addition, it is shown that, under a complementarity-based siting strategy, the length of periods with firm supply from intermittent sources increases up to three times compared to more conservative approaches relying on generation potential maximization.

[1]  A. Krenzinger,et al.  A dimensionless index evaluating the time complementarity between solar and hydraulic energies , 2008 .

[2]  Hazel E. Thornton,et al.  The climatological relationships between wind and solar energy supply in Britain , 2015, 1505.07071.

[3]  Jon Olauson,et al.  Correlation between wind power generation in the European countries , 2016 .

[4]  Antonio J. Conejo,et al.  Multistage Stochastic Investment Planning With Multiscale Representation of Uncertainties and Decisions , 2018, IEEE Transactions on Power Systems.

[5]  William Zappa,et al.  Analysing the potential of integrating wind and solar power in Europe using spatial optimisation under various scenarios , 2018, Renewable and Sustainable Energy Reviews.

[6]  Benjamin F. Hobbs,et al.  Adaptive Transmission Planning: Implementing a New Paradigm for Managing Economic Risks in Grid Expansion , 2016, IEEE Power and Energy Magazine.

[7]  R. Ramakumar,et al.  Modeling and Assessment of Wind and Insolation Resources with a Focus on Their Complementary Nature: A Case Study of Oklahoma , 2011 .

[8]  Daren Yu,et al.  Characterization of wind resource in China from a new perspective , 2019, Energy.

[9]  Iris Grossmann,et al.  Distributed solar electricity generation across large geographic areas, Part I: A method to optimize site selection, generation and storage , 2013 .

[10]  Yuanfu Xie,et al.  Future cost-competitive electricity systems and their impact on US CO2 emissions , 2016 .

[11]  Ian H. Rowlands,et al.  Solar and wind resource complementarity: Advancing options for renewable electricity integration in Ontario, Canada , 2011 .

[12]  Damien Ernst,et al.  Complementarity Assessment of South Greenland Katabatic Flows and West Europe Wind Regimes , 2018, Energy.

[13]  Marina Lavorato,et al.  Optimal siting and sizing of renewable energy sources, storage devices, and reactive support devices to obtain a sustainable electrical distribution systems , 2017, Energy Systems.

[14]  Fernando A. Kuipers,et al.  Optimal siting and sizing of wind farms , 2017 .

[15]  M. Borga,et al.  Space-time variability of climate variables and intermittent renewable electricity production – A review , 2017 .

[16]  Lei Wu,et al.  Spatial Power Network Expansion Planning Considering Generation Expansion , 2015, IEEE Transactions on Power Systems.

[17]  S. Liersch,et al.  A new approach for assessing synergies of solar and wind power: implications for West Africa , 2018, Environmental Research Letters.

[18]  Alberto Bemporad,et al.  Control of systems integrating logic, dynamics, and constraints , 1999, Autom..

[19]  Ana Martins,et al.  Optimizing the renewable generation mix in the Portuguese power system based on temporal and spatial diversity , 2014, 11th International Conference on the European Energy Market (EEM14).

[20]  Damien Ernst,et al.  Critical Time Windows for Renewable Resource Complementarity Assessment , 2018, Energy.

[21]  David Pozo-Vázquez,et al.  A methodology for evaluating the spatial variability of wind energy resources: Application to assess the potential contribution of wind energy to baseload power , 2014 .

[22]  Jay Apt,et al.  Geographic smoothing of solar PV: results from Gujarat , 2015 .

[23]  Jonathan L. Ho,et al.  An Engineering-Economic Approach to Transmission Planning Under Market and Regulatory Uncertainties: WECC Case Study , 2014, IEEE Transactions on Power Systems.

[24]  W. Short,et al.  Matching Western US electricity consumption with wind and solar resources , 2013 .

[25]  J. Edmonds,et al.  A Min-Max Relation for Submodular Functions on Graphs , 1977 .

[26]  Jay Apt,et al.  The variability of interconnected wind plants , 2010 .

[27]  Duncan S. Callaway,et al.  Strategic siting and regional grid interconnections key to low-carbon futures in African countries , 2017, Proceedings of the National Academy of Sciences.