Optimal siting and sizing of renewable sources in distribution system planning based on life cycle cost and considering uncertainties

V. V. Thang; Thanhtung Ha; V. V. Thang; Thanhtung Ha

doi:10.3934/energy.2019.2.211

AIMS Energy

2019, Volume 7, Issue 2: 211-226. doi: 10.3934/energy.2019.2.211

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Research article

Optimal siting and sizing of renewable sources in distribution system planning based on life cycle cost and considering uncertainties

V. V. Thang ^{1
,
,},
Thanhtung Ha ²

1.
Thainguyen University of Technology (TNUT), Thai Nguyen, Vietnam
2.
School of Electric Power, South China University of Technology, Guangzhou, China

Received: 19 February 2019 Accepted: 11 April 2019 Published: 19 April 2019

The renewable sources have made an impact on economic benefits and the electrical quality of the distribution system. Therefore, a multi-scenario optimization model is proposed, targeting to optimize the investment of renewable sources considering uncertainties based on the minimum life cycle cost. The mathematic model allows selecting the siting, sizing and type of renewable sources in distribution system. The objective function is minimizing life-cycle cost of the project during the planning period, including the investment and operation cost of renewable sources, the cost of purchasing energy from the grid, the emission taxes and residual value of the equipment at the end of the planning period. The nonlinear power flow model alternating current is utilized to concurrently balance both active and reactive power at each state as well as the constraints for the limit capacity of feeders. Connectable substation and the constraints in selecting the renewable sources are also represented and thus improving the accuracy of the calculated results of the distribution system. The uncertainty parameters of renewable sources (photovoltaic and wind turbine), electricity price and load were modeled by the probability density functions and are considered in the optimization model. The clustering technique was utilized to divide each parameter into states then all states of parameters are integrated by the combined model. The general algebraic modeling system (GAMS) was applied to solve the optimization problem with the test system and demonstrated the advantages of the proposed model.
- Distribution system,
- GAMS,
- Life cycle cost,
- optimization,
- renewable sources,
- uncertainties
Citation: V. V. Thang, Thanhtung Ha. Optimal siting and sizing of renewable sources in distribution system planning based on life cycle cost and considering uncertainties[J]. AIMS Energy, 2019, 7(2): 211-226. doi: 10.3934/energy.2019.2.211

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Abstract

The renewable sources have made an impact on economic benefits and the electrical quality of the distribution system. Therefore, a multi-scenario optimization model is proposed, targeting to optimize the investment of renewable sources considering uncertainties based on the minimum life cycle cost. The mathematic model allows selecting the siting, sizing and type of renewable sources in distribution system. The objective function is minimizing life-cycle cost of the project during the planning period, including the investment and operation cost of renewable sources, the cost of purchasing energy from the grid, the emission taxes and residual value of the equipment at the end of the planning period. The nonlinear power flow model alternating current is utilized to concurrently balance both active and reactive power at each state as well as the constraints for the limit capacity of feeders. Connectable substation and the constraints in selecting the renewable sources are also represented and thus improving the accuracy of the calculated results of the distribution system. The uncertainty parameters of renewable sources (photovoltaic and wind turbine), electricity price and load were modeled by the probability density functions and are considered in the optimization model. The clustering technique was utilized to divide each parameter into states then all states of parameters are integrated by the combined model. The general algebraic modeling system (GAMS) was applied to solve the optimization problem with the test system and demonstrated the advantages of the proposed model.

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