Abstract
This paper explores real power generation planning, considering distributed generation resources and energy storage in a small standalone power system. On account of the Kyoto Protocol and Copenhagen Accord, wind and photovoltaic (PV) powers are considered as clean and renewable energies. In this study, a genetic algorithm (GA) was used to determine the optimal capacities of wind-turbine-generators, PV, diesel generators and energy storage in a small standalone power system. The investment costs (installation, unit and maintenance costs) of the distributed generation resources and energy storage and the cost of fuel for the diesel generators were minimized while the reliability requirement and CO2 emission limit were fulfilled. The renewable sources and loads were modeled by random variables because of their uncertainties. The equality and inequality constraints in the genetic algorithms were treated by cumulant effects and cumulative probability of random variables, respectively. The IEEE reliability data for an 8760 h load profile with a 150 kW peak load were used to demonstrate the applicability of the proposed method.
Highlights
Small standalone power systems are found on offshore islands and indigenous areas in mountains.This paper addresses the generation expansion planning involving wind-turbine generators (WTG), photovoltaic (PV), diesel generators, and energy storage (ES) for small standalone power systems to meet the restriction of fuel emissions [1,2]
Due to uncertainty in the power generated by WTG and PV, diesel generators or energy storage are needed to maintain reliability
This paper presents a new method, based on the genetic algorithms, for determining the optimal capacities of hybrid wind/PV/diesel generation units and energy storage in a small autonomous power system
Summary
This paper addresses the generation expansion planning involving wind-turbine generators (WTG), photovoltaic (PV), diesel generators, and energy storage (ES) for small standalone power systems to meet the restriction of fuel emissions [1,2]. Many works have addressed the generation expansion planning in small standalone power systems [3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19]. Existing methodologies fall into three categories: reliability, optimization-, and enumeration-based methods. With respect to reliability-based methods, Billinton presented a methodology for sizing the WTG and PV array, considering investment cost, loss of power supply probability (LPSP) and loss of load probability (LOLP) [3]. Diaf considered different types and capacities of renewable sources to yield the desired reliability indices using the smallest “levelized cost of energy” [6]
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