No abstract

This paper presents the optimal scheduling of a diesel generator and an energy storage system (ESS) while using a detailed battery ESS energy efficiency model. Optimal scheduling has been hampered to date by the nonlinearity and complexity of the battery ESS. This is due to the battery ESS efficiency being a multiplication of inverter and battery efficiency and the dependency of an inverter and any associated battery efficiencies on load and charging and discharging. We propose a combined mixed-integer linear programming and particle swarm optimization (MILP-PSO) algorithm as a novel means of addressing these considerations. In the algorithm, MILP is used to find some initial points of PSO, so that it can find better solution. Moreover, some additional algorithms are added into PSO to modify and, hence, improve its ability of dealing with constraint conditions and the local minimum problem. The simulation results show that the proposed algorithm performs better than MILP and PSO alone for the practical microgrid. The results also indicated that simplification or neglect of ESS efficiency when applying MILP to scheduling may cause a constraint violation.

Recently, isolated microgrids have been operated using renewable energy sources (RESs), diesel generators, and battery energy storage systems (BESSs) for an economical and reliable power supply to loads. The concept of the complementary control, in which power imbalances are managed by diesel generators in the long time scale and BESSs in the short time scale, is widely adopted in isolated microgrids for efficient and stable operation. This paper proposes a new complementary control strategy for regulating the frequency and state of charge (SOC) when the system has multiple diesel generators and BESSs. In contrast to conventional complementary control, the proposed control strategy enables the parallel operation of diesel generators and BESSs, as well as SOC management. Furthermore, diesel generators regulate the equivalent SOC of BESSs with hierarchical control. Additionally, BESSs regulate the frequency of the system with hierarchical control and manage their individual SOCs. We conducted a case study by using Simulink/MATLAB to verify the effectiveness of the proposed control strategy in comparison with conventional complementary control.

No abstract

Department of Energy (DOE) reports produced after 1991 and a growing number of pre-1991 documents are available free via www.OSTI.gov.