Modeling of photovoltaic power uncertainties for impact analysis on generation scheduling and cost of an urban micro grid

Abstract In electrical systems, the main objective is to satisfy the load demand at the least cost without having imbalance between generation and consumption. Thus, the uncertainty of photovoltaic (PV) power production must be considered in generation planning of a power system. In this paper, we develop a modeling method of this uncertainty to consider it into the generation scheduling. The optimal generation scheduling in an urban microgrid is made by taking in consideration the operating reserve provision under stochastic characteristics of PV power prediction. By considering a prescribed risk level of unbalancing, a dynamic programming algorithm sets the operational planning of conventional generators by solving a non-convex mixed-integer nonlinear programming model, so that the operational cost and available operating reserve can be calculated. Then, the effect of PV power uncertainty into the unit commitment is analyzed by considering PV forecast intervals with a 95 % confidence level. The unit commitment is then recalculated with new generator set points and the same criteria. Finally, variations of the targeted minimized costs and obtained OR is analyzed according to the uncertainty.

[1]  Pandelis N. Biskas,et al.  Multiple Time Resolution Unit Commitment for Short-Term Operations Scheduling Under High Renewable Penetration , 2014, IEEE Transactions on Power Systems.

[2]  Bruno Francois,et al.  Emission Reduction and Economical Optimization of an Urban Microgrid Operation Including Dispatched PV-Based Active Generators , 2014, IEEE Transactions on Sustainable Energy.

[3]  M A Matos,et al.  Setting the Operating Reserve Using Probabilistic Wind Power Forecasts , 2011, IEEE Transactions on Power Systems.

[4]  Martin Haberg,et al.  Fundamentals and recent developments in stochastic unit commitment , 2019, International Journal of Electrical Power & Energy Systems.

[5]  Gilles Malarange,et al.  Energy storage systems in distribution grids: New assets to upgrade distribution network abilities , 2009 .

[6]  R. Bellman Dynamic programming. , 1957, Science.

[7]  Bangyin Liu,et al.  Smart energy management system for optimal microgrid economic operation , 2011 .

[8]  P. Sauer,et al.  Uncertainty Management in the Unit Commitment Problem , 2009, IEEE Transactions on Power Systems.

[9]  D. P. Kothari,et al.  Optimal thermal generating unit commitment: a review , 1998 .

[10]  Chun-Lung Chen,et al.  Optimal Wind–Thermal Generating Unit Commitment , 2008, IEEE Transactions on Energy Conversion.

[11]  Jianhui Wang,et al.  Stochastic Optimization for Unit Commitment—A Review , 2015, IEEE Transactions on Power Systems.

[12]  Bruno Francois,et al.  Development of a tool for urban microgrid optimal energy planning and management , 2018, Simul. Model. Pract. Theory.

[13]  Javier Contreras,et al.  Stochastic Unit Commitment in Isolated Systems With Renewable Penetration Under CVaR Assessment , 2016, IEEE Transactions on Smart Grid.

[14]  Robin Broder Hytowitz,et al.  Managing solar uncertainty in microgrid systems with stochastic unit commitment , 2015 .

[15]  Jianhui Wang,et al.  Energy Management Systems in Microgrid Operations , 2012 .

[16]  S. P. Singh,et al.  Integration of Distributed Energy Resources , 2014 .

[17]  Joao P. S. Catalao,et al.  Overview of insular power systems under increasing penetration of renewable energy sources: Opportunities and challenges , 2015 .

[18]  Henrik Madsen,et al.  Integrating Renewables in Electricity Markets: Operational Problems , 2013 .

[19]  Ming Yang,et al.  Optimizing probabilistic spinning reserve by an umbrella contingencies constrained unit commitment , 2019 .

[20]  Allen J. Wood,et al.  Power Generation, Operation, and Control , 1984 .

[21]  Wencong Su,et al.  Stochastic Energy Scheduling in Microgrids With Intermittent Renewable Energy Resources , 2014, IEEE Transactions on Smart Grid.

[22]  M. Carrion,et al.  A computationally efficient mixed-integer linear formulation for the thermal unit commitment problem , 2006, IEEE Transactions on Power Systems.

[23]  Xingyu Yan,et al.  Uncertainty analysis for day ahead power reserve quantification in an urban microgrid including PV generators , 2017 .

[24]  Nikolaos V. Sahinidis,et al.  Optimization under uncertainty: state-of-the-art and opportunities , 2004, Comput. Chem. Eng..

[25]  Abdollah Kavousi-Fard,et al.  Considering uncertainty in the optimal energy management of renewable micro-grids including storage devices , 2013 .