Abstract
In this paper, optimal economic management of a grid-connected microgrid (MG) with distributed energy resource (DER) and its interaction with incentive-based demand response programs (DRPs) is studied. The use of DR makes energy management system (EMS) of the MG an efficient tool in balancing the demand and supply, and therefore ensuring the network reliability. In this work, the cost function of customers is developed in the incentive-based DRP with the aim of receiving a more realistic incentive and then it is combined with EMS. Accordingly, the consumers offer hourly power reduction bids based on which they are sorted and then incentive-based payment model is implemented. At times, due to full utilization of grid and MG resources, the supply–demand balance cannot be maintained by respecting the consumer offers. Specific energy policies and contracts are required in this case for mandatory power curtailment in exchange for higher incentive payments by MG operator (MGO). The objective function attempts to minimize operation costs of the MG units such as Diesel Generator fuels costs, cost of power exchange with the main grid, battery energy storage system (BESS) costs and in the mean time, maximize MGO DR benefit. On the other hand, simultaneous EMS and DR management leads to a complex non-linear problem, which can be solved using whale optimization algorithm (WOA) in MATLAB software. To assess the performance of the proposed new approach, a grid-connected MG with DERs and reducible power of consumers is studied within a 24-h time cycle. Also, to verify the scalability of the implemented system, an MG with aggregators and a large scale battery is considered. Simulation results show that incorporating a developed DR into EMS is an efficient way in optimal performance of both demand and supply sides in conjunction with the goals of economic operation of MGs.
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Abbreviations
- I:
-
Number of diesel generators
- J:
-
Total number of consumers
- T:
-
Number of dispatch intervals
- \(CT_{t}\) :
-
MGO cost for trading transferable power at time t
- \(BO_{t}\) :
-
Benefit function of the MGO at time t
- \(P_{{{\text{utility}}}}^{max}\) :
-
Maximum power transferable between the main grid and MG
- \(\gamma_{b,t}\) :
-
Price of power bought from the main grid at time t
- \(\gamma_{s,t}\) :
-
The price of the power sold to the main grid at time t
- \(P_{wind}^{Max}\) :
-
Upper power output limit of wind turbine
- \(v_{hub,t}\) :
-
Hourly wind speed at the desired height at time t
- \(h_{hub}\) :
-
Desired height for wind turbine
- \(h_{ref}\) :
-
Reference height for wind turbine
- \(v_{ref,t}\) :
-
Hourly wind speed at the reference height at time t
- \(\beta\) :
-
The power law exponent that ranges from \(\frac{1}{7}\,to\,\frac{1}{4}\)
- \(v_{hub,t}\) :
-
The wind velocity at height \(h_{hub}\) at time t
- \(\rho_{air}\) :
-
Air density
- \(C_{p}\) :
-
Power coefficient of the wind turbine (dependent on wind turbine design)
- \(A_{wind}\) :
-
Area of the wind turbine rotor swept area
- \(\eta_{wind}\) :
-
Efficiency of the wind generator
- \(P_{pv}^{Max}\) :
-
Upper power output limit of the photovoltaic panel
- \(\eta_{pv}\) :
-
Efficiency of the PV system
- \(A_{pv}\) :
-
Area of the PV array
- \(I_{pv,t}\) :
-
Hourly solar irradiation incident on the solar PV array at time t
- \(CF_{i,t}\) :
-
Fuel cost of diesel generator i at time t
- \(P_{i}^{min}\) :
-
The minimum capacity of diesel generator i
- \(P_{i}^{max}\) :
-
The maximum capacity of diesel generator i
- \(DR_{i}\) :
-
The maximum ramp down rates of diesel generator i
- \(UR_{i}\) :
-
Maximum ramp up rates of diesel generator i
- \(a_{i}\) \(b_{i}\) :
-
Fuel cost coefficients of diesel generator i
- \(BC_{j,t}\) :
-
Benefit function of customer j at time t
- \(CIn_{j,t}\) :
-
Incurred cost of reducing PC (kW) by customer of type \(\theta\)
- \(CPe_{j,t}\) :
-
Penalty cost imposed for reducing more Power from declared value of customer j at time t
- \(k_{1,j}\) :
-
\(k_{2,j}\), Outage cost function coefficients of participant customer j
- \(\theta_{j,t}\) :
-
Customer type from 0 to 1
- \(PC_{j,t}^{pro}\) :
-
Proposed amount of power curtailment limit by customer j at time t
- \(CB_{t}\) :
-
Cost of charging/discharging the battery unit at time t
- \(\sigma\) :
-
Price of battery operation
- \(\xi\) :
-
Self-discharge coefficients of the battery unit
- \(\eta_{ch} , \eta_{dis}\) :
-
Charge/ discharge efficiencies of the battery unit
- \(C_{batt}\) :
-
Capacity of the battery unit
- \({\text{SOC}}^{0}\) :
-
Initial state of charge
- \({\text{SOC}}^{min}\) :
-
Minimum capacity of the battery unit
- \({\text{SOC}}^{max}\) :
-
Maximum capacity of the battery unit
- \(SOC_{t}\) :
-
State Of Charge for battery unit at time t
- \(P_{batt}^{max}\) :
-
Maximum charge and discharge power rate of the battery unit at time t
- \(P_{batt}^{min}\) :
-
Minimum charge and discharge power rate of the battery unit at time t
- \(\vec{A}\) :
-
Coefficient vectors of the whale algorithm; Random value in interval [-a, a]
- \(\vec{C}\) :
-
Coefficient vectors of the whale algorithm
- \(\overrightarrow {{X^{*} }}\) :
-
Position vector of the best solution obtained so far
- \(\vec{X}\) :
-
Position vector of the whale logarithm
- \(\overrightarrow {{X_{rand} }}\) :
-
A random whale position vector
- a:
-
A value linearly decreased from 2 to 0 over the course of iterations (in both exploration and exploitation phases)
- r:
-
A random vector in [0,1]
- \(\delta\) :
-
A random number in [0,1]
- \(\overrightarrow {{D{^{\prime}}}}\) :
-
Distance of the ith whale to the prey (best solution obtained so far)
- b:
-
A constant for defining the shape of the logarithmic spiral
- L:
-
A random number in [− 1,1]
- \(PD_{t}\) :
-
Total system demand at time t
- OB:
-
MGO's total budget
- \(\lambda_{j,t}\) :
-
Value of interrupted power calculated via OPF (LMP)
- W:
-
Objective function weight
- \(P_{batt,t}\) :
-
Hourly power output from the battery unit at time t
- \(P_{ch,t}\) :
-
Amount of power charge from the battery unit at time t
- \(P_{dis,t}\) :
-
Amount of power discharge from the battery unit at time t
- \(P_{utility,t}\) :
-
Transferable power between the main grid and MG at time t
- \(P_{b,t}\) :
-
Amount of power bought from the main grid at time t
- \(P_{s,t}\) :
-
Amount of power sold to the main grid at time t
- \(P_{wind,t}\) :
-
Hourly energy output from the wind generator at time t
- \(P_{pv,t}\) :
-
Power generated from the Photovoltaic generator at time t
- \(P_{i,t}\) :
-
Power generated from diesel generator i at time t
- \(PC_{j,t}^{opt}\) :
-
Quantity of optimum power curtailment by a participant customer j at time t
- \(PC_{j,t}^{norm}\) :
-
Quantity of normal power curtailment by customer j at time t
- \(PC_{j,t}^{mand}\) :
-
Quantity of mandatory power curtailment by customer j at time t
- \(y_{j,t}\) :
-
Value of monetary compensation received by customer j at time t
- \(b_{t}^{batt}\) :
-
Binary variable for discharging (0)/charging (1) mode of the battery unit at time t
- \(b_{t}^{u}\) :
-
Binary variable for exporting (0) and importing (1) mode to/from the main grid at time t
- BESS:
-
Battery energy storage system
- DER:
-
Distributed energy resource
- DG:
-
Distributed generation
- DOD:
-
Depth of discharge
- DR:
-
Demand response
- DRP:
-
Demand response program
- EMS:
-
Energy management system
- ESS:
-
Energy storage system
- GA:
-
Genetic algorithm
- MG:
-
Microgrid
- MGO:
-
Microgrid operator
- MILP:
-
Mixed integer linear programming
- MINLP:
-
Mixed integer nonlinear programming
- OPF:
-
Optimal power flow
- PSO:
-
Particle Swarm Optimization
- PV:
-
Photovoltaic
- RES:
-
Renewables energy source
- SOC:
-
State of charge
- WOA:
-
Whale Optimization Algorithm
- WT:
-
Wind turbine
- | |:
-
Absolute value
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Mohammadjafari, M., Ebrahimi, R. & Parvin Darabad, V. Optimal Energy Management of a Microgrid Incorporating a Novel Efficient Demand Response and Battery Storage System. J. Electr. Eng. Technol. 15, 571–590 (2020). https://doi.org/10.1007/s42835-020-00345-5
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DOI: https://doi.org/10.1007/s42835-020-00345-5