Design of installation capacity evaluation mechanism for hybrid energy generation system

Abstract

This study presents a simple evaluation mechanism for the installation capacity of a hybrid energy generation system. The mechanism is mainly applicable to hybrid energy sources, including wind power, photovoltaic (PV), and fuel cells (FC). Demand power is mainly supplied by the PV and wind power, and backup power in case of an emergency is provided by the FC generation system. The aim of the hybrid energy generation system is to suppress the penalty bill caused by exceeding the contract power capacity with the power company and to supply the backup power when needed. According to different installation locations of the hybrid energy generation system, a simple evaluation mechanism for the installation capacity is designed by considering the concept of capacity factor and cost recovery to obtain the ratio of installation capacity. The performance of the proposed evaluation mechanism is verified by numerical simulations of a real campus in Taiwan. The comparison of the proposed evaluation mechanism with two dispatch methods via the rate of capacity factor and the rate of power generation cost is done on the equal basis of 104 kW power requirement provided by the PV and wind power generation systems to avoid the penalty for exceeding its contractual power capacity, and the capacity factors (10.7 and 34.33%) for the PV and wind power generation systems. Numerical results show that the proposed evaluation mechanism has about (45.5%/13.3%) and (18.2%/20%) self-use/selling payback year improvements than two conventional dispatch methods, respectively.

Installed capacity selection of hybrid energy generation system via improved particle‐swarm‐optimisation

“…Thus, the corresponding demand charge saving, energy charge saving and CO 2 reduction cost are relatively lower and are not considered here [17].…”

“…2, 3 and 4). Mechanism for evaluating installation capacity of HEGS in [17] www.ietdl.org 750 This study has successfully developed an IPSO algorithm to enhance the optimal performance of the installed capacity selection of a HEGS with a shorter execution time and a higher convergence speed. By considering the installation cost and the recovery cost of the HEGS, an optimisation objective function, which equals the installation cost divided by the recovery cost, is formulated, and then the optimal ratio for the HEGS can be obtained via minimising of the objective function in the sense of the proposed IPSO algorithm.…”

Installed capacity optimization of hybrid energy generation system

“…Because the FC is expensive and its useful life is shortest so that FC mainly supplies the backup emergent power, the corresponding demand charge, energy charge, and 2 CO reduction cost are not considered [13].…”

“…The capacity factor for each renewable energy source in the installation can be obtained via a dynamic mathematical model under different weather conditions for the location and its information is beneficial to assess the power generation efficiency and ensure providing higher quality and more reliable power to customer [13].…”

“…The objective of providing reliable power for load and shortest payback period can then be achieved. Different from the method described in the literature [13], the installed capacity selection of the proposed HEGS is formulated as an optimization problem with equality and inequality constraints, and an improved particle swarm optimization (IPSO) algorithm is applied to achieve the optimal ratio of the installed capacity.…”