Energy resources management in three distinct time horizons considering a large variation in wind power

The intensive use of distributed generation based on renewable resources increases the complexity of power systems management, particularly the short-term scheduling. Demand response, storage units and electric and plug-in hybrid vehicles also pose new challenges to the short-term scheduling. However, these distributed energy resources can contribute significantly to turn the shortterm scheduling more efficient and effective improving the power system reliability. This paper proposes a short-term scheduling methodology based on two distinct time horizons: hour-ahead scheduling, and real-time scheduling considering the point of view of one aggregator agent. In each scheduling process, it is necessary to update the generation and consumption operation, and the storage and electric vehicles status. Besides the new operation condition, more accurate forecast values of wind generation and consumption are available, for the resulting of short-term and very short-term methods. In this paper, the aggregator has the main goal of maximizing his profits while, fulfilling the established contracts with the aggregated and external players. Nomenclature t  Elementary period (h) ( ) c ST  Storage charge efficiency ( ) c V  Grid-to-vehicle efficiency ( ) d ST  Storage discharge efficiency ( ) d V  Vehicle-to-grid efficiency ( ) i t  Voltage angle at bus i in period t (rad) max i  Maximum voltage angle at bus i (rad) min i  Minimum voltage angle at bus i (rad) ( ) j t  Voltage angle at bus j in period t (rad)  Phase angle of the load L ij B Imaginary part of the element in admittance matrix corresponding to the row i and column j (S) C VPP operation costs (m.u.) f Objective function (m.u.) ij G Real part of the element in admittance matrix corresponding to row i and column j (S) In VPP income (m.u.) i L Set of line connected to bus i ( , ) Cut L t c Demand response curtailment cost of load L in period t (m.u./Wh) ( , ) Dch ST t c Discharge cost of storage ST in period t (m.u./Wh) ( , ) Dch V t c Discharge cost of electric vehicle V in period t (m.u./Wh) ( , ) DG DG t c Generation cost of DG unit in period t (m.u./Wh) ( , ) GCP DG t c Generation curtailment power cost of DG unit in period t (m.u./Wh) ( , ) NSD L t c Non-supplied demand cost of load L in period t (m.u./Wh) ( , ) Red L t c Demand response reduction cost of load L in period t (m.u./Wh) ( , ) SP SP t c Energy price of the external supplier SP in period t (m.u./Wh) ( ) BatCap ST E Battery energy capacity of storage unit ST (Wh) ( ) BatCap V E Battery energy capacity of electric vehicle V (Wh) ( , ) MinCh ST t E Minimum stored energy of storage unit ST (Wh) ( , ) MinCh V t E Minimum stored energy to be guaranteed at the end of period t, for electric vehicle V (Wh) ( , ) Stored ST t E Energy stored in storage unit ST at the end of period t (Wh) ( , ) Stored V t E Energy stored in electric vehicle V at the end of period t (Wh) ( , ) Trip V t E Energy consumption during a trip of the electric vehicle V in period t (Wh) ( , ) Ch ST t MP Market price for the charge process of storage ST in period t (m.u./Wh) ( , ) Ch V t MP Market price for the charge process of vehicle V in period t (m.u./Wh) ( , ) Load L t MP Market price of load L in period t (m.u./Wh) ( ) Sell t MP Market price of selling energy to the market unit in period t (m.u./Wh) B N Total number of buses DG N Total number of distributed generators i DG N Total number of units DG for bus i L N Total number of loads i L N Total number of loads L for bus i K N Total number of lines ST N Total number of storage units i ST N Total number of storage units ST for bus i SP N Total number of external suppliers i SP N Total number of external suppliers SP for bus i V N Total number of electric vehicles i V N Total number of electric vehicles V for bus i ( , ) Ch ST t P Active power charge of storage ST in period t (W) ( , ) i Ch ST t P Active power charge of storage units ST at bus i in period t (W) ( , ) Ch V t P Active power charge of electric vehicle V in period t (W) ( , ) i Ch V t P Active power charge of electric vehicle V at bus i in period t (W) ( , ) ChLimit ST t P Maximum active power charge of storage unit ST in period t (W) ( , ) ChLimit V t P Maximum active power charge of electric vehicle V in period t (W) ( , ) Cut L t P Active power of demand response curtailment of load L in period t (W) ( , ) i Cut L t P Active power of demand response curtailment of load L at bus i in period t (W) ( , ) Dch ST t P Active power discharge of storage ST in period t (W) ( , ) i Dch ST t P Active power discharge of storage unit ST at bus i in period t (W) ( , ) Dch V t P Active power discharge of electric vehicle V in period t (W) ( , ) i Dch V t P Active power discharge of electric vehicle V at bus i in period t (W) ( , ) DchLimit ST t P Maximum active power discharge of storage unit ST in period t (W) ( , ) DchLimit V t P Maximum active power discharge of electric vehicle V in period t (W) ( , ) DchMin ST t P Minimum active power discharge of storage unit ST in period t (W) ( , ) DchMin V t P Minimum active power discharge of electric vehicle V in period t (W) ( , ) DG DG t P Active power generation of DG unit in period t (W) ( , ) i DG DG t P Active power generation of DG unit at bus i in period t (W) ( ) Di t P Active power demand at bus i in period t (W) ( , ) DGMax DG t P Maximum active power generation of DG unit in period t (W) ( , ) DGMin DG t P Minimum active power generation of DG unit in period t (W) ( , ) GCP DG t P Generation curtailment power by DG unit in period t (W) ( , ) i GCP DG t P Generation curtailment power by DG unit at bus i in period t (W) ( ) Gi t P Active power generation at bus i in period t (W) ( , ) Load L t P Active power demand of load L in period t (W) ( , ) i Load L t P Active power demand of load L at bus i in period t (W) ( , ) MaxCut L t P Maximum DR curtailment of load L in period t (W) ( , ) MaxRed L t P Maximum DR reduction of load L in period t (W) ( , ) MinCut L t P Minimum DR curtailment of load L in period t (W) ( , ) MinRed L t P Minimum DR reduction of load L in period t (W) ( , ) NSD L t P Active non-supplied demand for load L in period t (W) ( , ) i NSD L t P Active non-supplied demand for load L at bus i in period t (W) ( , ) Red L t P Active power of demand response reduction of load L in period t (W) ( , ) i Red L t P Active power of demand response reduction of load L at bus i in period t (W) ( ) Sell t P Active power sell to market of VPP in period t (W) ( ) i Sell t P Active power sell to market of VPP at bus i in period t (W) ( , ) SP SP t P Active power generation of the external supplier SP in period t (W) ( , ) i SP SP t P Active power generation of the external supplier SP at bus i in period t (W) ( , ) SPMax SP t P Maximum active power of the external supplier SP in period t (W) ( , ) SPMin SP t P Minimum active power of the external supplier SP in period t (W) ( , ) i DG DG t Q Reactive power generation of DG unit at bus i in period t (VAr) ( ) Di t Q Reactive power demand at bus i in period t (VAr) ( , ) DGMax DG t Q Maximum reactive power generation of DG unit in period t (VAr) ( , ) DGMin DG t Q Minimum reactive power generation of DG unit in period t (VAr) ( ) Gi t Q Reactive power generation at bus i in period t (VAr) ( , ) i Load L t Q Reactive power demand of load L at bus i in period t (VAr) ( , ) i NSD L t Q Reactive non-supplied demand for load L at bus i in period t (VAr) ( , ) i SP SP t Q Reactive power generation of the external supplier SP at bus i in period t (VAr) ( , ) SPMax SP t Q Maximum reactive power of the external supplier SP in period t (VAr) max Lk S Maximum apparent power flow established in line k that connect buses i and j (VA) T Total number of periods ( ) i t U Voltage at bus i in polar form in period t (V) ( ) j t U Voltage at bus j in polar form in period t (V) ( ) i t V Voltage magnitude at bus i in period t (V) max i V Maximum voltage magnitude at bus i (V) min i V Minimum voltage magnitude at bus i (V) ( ) j t V Voltage magnitude at bus j in period t (V) ( , ) Ch ST t X Binary variable of storage unit ST related to power charge ( , ) Ch V t X Binary variable of electric vehicle V related to power charge ( , ) Cut L t X Binary variable of DR curtailment of load L in period t ( , ) Dch ST t X Binary variable of storage unit ST related to power discharge ( , ) Dch V t X Binary variable of electric vehicle V related to power discharge ( , ) DG DG t X Binary variable of DG unit in period t (connected or disconnected) ij y Series admittance of line that connect the buses i and j in polar form (S) _ sh i y Shunt admittance of line connected in bus i in polar form (S) _ sh j y Shunt admittance of line connected in bus j in polar form (S)

[1]  Ganesh Kumar Venayagamoorthy,et al.  One Step Ahead: Short-Term Wind Power Forecasting and Intelligent Predictive Control Based on Data Analytics , 2012, IEEE Power and Energy Magazine.

[2]  Z. Vale,et al.  Demand response in electrical energy supply: An optimal real time pricing approach , 2011 .

[3]  Zita Vale,et al.  Real-time energy resources scheduling considering intensive wind penetration , 2012 .

[4]  Federico Silvestro,et al.  Short-Term Scheduling and Control of Active Distribution Systems With High Penetration of Renewable Resources , 2010, IEEE Systems Journal.

[5]  Zita Vale,et al.  Optimal scheduling of a renewable micro-grid in an isolated load area using mixed-integer linear programming , 2010 .

[6]  Danny Pudjianto,et al.  Virtual power plant and system integration of distributed energy resources , 2007 .

[7]  Pedro Faria,et al.  Demsi — A demand response simulator in the context of intensive use of distributed generation , 2010, 2010 IEEE International Conference on Systems, Man and Cybernetics.

[8]  Zita Vale,et al.  A probabilistic methodology for distributed generation location in isolated electrical service area , 2010 .

[9]  H. Morais,et al.  Technical and economic resources management in smart grids using heuristic optimization methods , 2010, IEEE PES General Meeting.

[10]  H. Morais,et al.  Distributed energy resources management with cyber-physical SCADA in the context of future smart grids , 2010, Melecon 2010 - 2010 15th IEEE Mediterranean Electrotechnical Conference.

[11]  Nouredine Hadjsaid,et al.  On the concept and the interest of virtual power plant: Some results from the European project Fenix , 2009, 2009 IEEE Power & Energy Society General Meeting.

[12]  M. Ragwitz,et al.  Status and perspectives of renewable energy policy and deployment in the European Union—What is needed to reach the 2020 targets? , 2011 .

[13]  Qiong Wu,et al.  Multi-objective optimization for the operation of distributed energy systems considering economic and environmental aspects , 2010 .

[14]  H. Morais,et al.  Distribution network short term scheduling in Smart Grid context , 2011, 2011 IEEE Power and Energy Society General Meeting.