Search Improvement Process-Chaotic Optimization-Particle Swarm Optimization-Elite Retention Strategy and Improved Combined Cooling-Heating-Power Strategy Based Two-Time Scale Multi-Objective Optimization Model for Stand-Alone Microgrid Operation

Fei Wang, Lidong Zhou, Hui Ren and Xiaoli Liu
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Fei Wang: State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University, Baoding 071003, China
Lidong Zhou: State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University, Baoding 071003, China
Hui Ren: State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University, Baoding 071003, China
Xiaoli Liu: Shuozhou Power Company of State Grid Shanxi Electric Power Company, Shuozhou 036000, China

Energies, 2017, vol. 10, issue 12, 1-23

Abstract: The optimal dispatching model for a stand-alone microgrid (MG) is of great importance to its operation reliability and economy. This paper aims at addressing the difficulties in improving the operational economy and maintaining the power balance under uncertain load demand and renewable generation, which could be even worse in such abnormal conditions as storms or abnormally low or high temperatures. A new two-time scale multi-objective optimization model, including day-ahead cursory scheduling and real-time scheduling for finer adjustments, is proposed to optimize the operational cost, load shedding compensation and environmental benefit of stand-alone MG through controllable load (CL) and multi-distributed generations (DGs). The main novelty of the proposed model is that the synergetic response of CL and energy storage system (ESS) in real-time scheduling offset the operation uncertainty quickly. And the improved dispatch strategy for combined cooling-heating-power (CCHP) enhanced the system economy while the comfort is guaranteed. An improved algorithm, Search Improvement Process-Chaotic Optimization-Particle Swarm Optimization-Elite Retention Strategy (SIP-CO-PSO-ERS) algorithm with strong searching capability and fast convergence speed, was presented to deal with the problem brought by the increased errors between actual renewable generation and load and prior predictions. Four typical scenarios are designed according to the combinations of day types (work day or weekend) and weather categories (sunny or rainy) to verify the performance of the presented dispatch strategy. The simulation results show that the proposed two-time scale model and SIP-CO-PSO-ERS algorithm exhibit better performance in adaptability, convergence speed and search ability than conventional methods for the stand-alone MG’s operation.

Keywords: stand-alone MG; SIP-CO-PSO-ERS; two-time scale optimized model; improved CCHP dispatch strategy; multi-scenario; economic dispatch (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (8)

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