Abstract

Photovoltaic (PV) energy generation in microgrids (MGs) is increasing. Battery energy storage systems (BESSs) reduce the fluctuations in PV outputs caused by the intermittent availability of solar energy. Although BESSs are advantageous for stable MG operation, they are still relatively expensive. By remaining within the operational limits during normal and contingency operation, optimal sizing of BESS is required to maintain security considering cost of MG system. This paper proposes a BESS sizing optimization approach for MGs by solving the security constrained optimal power flow (SCOPF), considering the stochastic errors in forecasting the PV outputs. The degree of compensation for the solar energy forecasting error is firstly configured. To address these errors, the combined PV and BESS operation system is modeled by applying a control strategy to smooth PV fluctuations and minimize battery life degradation. BESS sizing optimization, under a certain degree of compensation, minimizes the PV penalty cost and BESS operation cost. The optimal BESS capacity and schedule are then obtained for the MG. To enhance the convergence and computational efficiency, decomposed-probabilistic security constrained optimal power flow (D-PSCOPF) is proposed. It efficiently solves the problem by dividing it into a master problem and a slave problem. The base case solution is computed in the slave problem, which induces the partial optimal size of BESS. By adding the feasibility cut through the violation of the slave problem, the master problem derives the optimal BESS capacity. Different case studies were analyzed, confirming the superiority and computational efficiency of the proposed approach.

Highlights

  • J Set of indices of all scenarios k Index over post-contingency cases K Set of indices of contingencies considered in scenarios i Index over injections I t Set / maximum number of uncertainties available for dispatch in any contingency at time t n Number of samples in a scheduling cycle c Electricity price gtjk htjk

  • Our strategy increased the accuracy of the combined PV-Battery energy storage systems (BESSs) operation system through the BESS compensation strategy reflecting the rated output/capacity and life degradation model of the BESS

  • To optimize the BESS sizing under the constraint of a certain compensation degree, the compensation interval of the forecasting error should be first obtained in the combined PV-BESS

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Summary

PARAMETERS

A. INDICES and SETS t Index over time periods T Set of indices of time periods j Index over scenarios. J Set of indices of all scenarios k Index over post-contingency cases K Set of indices of contingencies considered in scenarios i Index over injections I t Set / maximum number of uncertainties available for dispatch in any contingency at time t n Number of samples in a scheduling cycle c Electricity price gtjk htjk. Power flow equations in post contingency state k of scenario j at time t Transmission, voltage and other limits in post-c ontingency state k of scenario j at time t. PG Combined output power of the system fα Confidence rate cost fα,penalty Penalty cost of the PV operation at α%

VARIABLES ptijk P+tijk
BACKGROUND
LITERATRUE REVIEW
CONTRIBUTIONS AND PAPER ORGANIZATIONS
PSCOPF MODEL
1) Objective function
COMBINED PV AND BESS OPERATION SYSTEM
BESS OPERATION FOR PV FORECASTING ERROR
BESS SIZING OPTIMIZATION APPROACH
1) Objective Function
PROPOSED D-PSCOPF MODEL
Slave Problem
Master Problem
Solution Procedure
CASE STUDY
CONCLUSION
Full Text
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