Review on the state‐of‐the‐art multi‐objective optimisation of hybrid standalone/grid‐connected energy systems

Khezri, Rahmat; Mahmoudi, Amin

doi:10.1049/iet-gtd.2020.0453

Cited by 81 publications

(32 citation statements)

References 177 publications

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“…By using the TOU mechanism, the electricity price changes two or three times during the day. Hence, the optimal capacity of PV and BESS needs to be selected according to the electricity rates for import/export costs of GCHs to obtain the highest economic profits [11]. There are also several important parameters such as the salvation value and degradation of PV and BESS, considering grid constraints, as well as incorporation of actual data that are required to achieve a practical optimal sizing of the system.…”

Section: Introduction 1background and Motivationmentioning

confidence: 99%

Optimal Sizing of Rooftop PV and Battery Storage for Grid-Connected Houses Considering Flat and Time-of-Use Electricity Rates

et al. 2021

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This paper investigates a comparative study for practical optimal sizing of rooftop solar photovoltaic (PV) and battery energy storage systems (BESSs) for grid-connected houses (GCHs) by considering flat and time-of-use (TOU) electricity rate options. Two system configurations, PV only and PV-BESS, were optimally sized by minimizing the net present cost of electricity for four options of electricity rates. A practical model was developed by considering grid constraints, daily supply of charge of electricity, salvation value and degradation of PV and BESS, actual annual data of load and solar, and current market price of components. A rule-based energy management system was examined for GCHs to control the power flow among PV, BESS, load, and grid. Various sensitivity analyses are presented to examine the impacts of grid constraint and electricity rates on the cost of electricity and the sizes of the components. Although the capacity optimization model is generally developed for any case study, a grid-connected house in Australia is considered as the case system in this paper. It is found that the TOU-Flat option for the PV-BESS configuration achieved the lowest NPC compared to other configuration and options. The optimal capacities of rooftop PV and BESS were obtained as 9 kW and 6 kWh, respectively, for the PV-BESS configuration with TOU-Flat according to two performance metrices: net present cost and cost of electricity.

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Section: Introduction 1background and Motivationmentioning

confidence: 99%

Optimal Sizing of Rooftop PV and Battery Storage for Grid-Connected Houses Considering Flat and Time-of-Use Electricity Rates

et al. 2021

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“…In [25, 26], two cooperative and non‐cooperative game theory techniques are explained, and the best one is proposed to find the payoff value based on different objective functions. Designing a networked microgrid based on a game‐theoretic technique can be a promising idea to optimize different conflicts based on multi‐objective function [27]. In [20], a grid‐connected hybrid power system is built through a technique of multi‐objective optimization including costs, reliability, and pollutant emissions as criteria to be met.…”

Section: Introductionmentioning

confidence: 99%

A multi‐objective optimization for planning of networked microgrid using a game theory for peer‐to‐peer energy trading scheme

Ali

Muyeen

Bizhani

et al. 2021

IET Generation Trans & Dist

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In this paper, a multi‐objective optimization technique is proposed for the planning of a networked microgrid based on peer‐to‐grid (P2G) and peer‐to‐peer (P2P) energy trading schemes. Two different criteria's including annual profit and energy index of reliability are taken into consideration to form a multi‐objective function. The networked microgrid consists of three individual microgrids containing their own combinations of generation resources, batteries and residential loads. All microgrids are connected together and also to the main grid to meet the energy exchange requirements of P2P energy trading. A cooperative game theory technique based on a particle swarm optimization algorithm is used to model the networked microgrid, and to find the suitable sizes of the players that simultaneously maximize the payoff values of both objective functions. Besides, a comparative analysis is carried out for both P2G and P2P energy trading schemes. The results show that the outcomes are maximum when both criteria are considered in the optimization and P2P energy trading is carried out. The sensitivity analysis is performed on the selected parameters and verified the right change 0.003% and 4.5% in discount rate and electricity prices, respectively.

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“…Different charging/discharging strategies of grid‐connected EVs were discussed in [12]. However, these studies did not investigate optimal sizing of SPV and BSS, which is an important stage of design procedure [13]. This is usually integrated with energy management of the system.…”

Section: Introductionmentioning

confidence: 99%

Optimal planning of solar photovoltaic and battery storage for electric vehicle owner households with time‐of‐use tariff

Merrington

Khezri

Mahmoudi

2021

IET Generation Trans & Dist

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This paper presents a practical optimal planning of solar photovoltaic (SPV) and battery storage system (BSS) for electric vehicle (EV) owner households with time of use (TOU) electricity pricing. The main aim of the optimisation problem is to minimize the Cost of Electricity (COE) while satisfying the design constraints over 20‐year project lifespan. Novel rule‐based home energy management systems are created to investigate the optimal sizing of two system configurations: (1) SPV‐EV, and (2) SPV‐BSS‐EV. The arrival and departure times of the EV's availability, as well as its initial state‐of‐charge are incorporated into the energy management system via stochastic functions. Sensitivity analyses of the feed in tariff, grid constraint, electricity demand, and available rooftop area are provided to investigate the variations of cost of electricity and capacities of SPV and BSS. From the study results, practical guidelines for grid‐connected households, based on TOU energy pricing, are provided to select the optimal capacity of SPV and BSS to accommodate the existing EV. The optimisation method is general and applicable to any household owning EV; however, in this study realistic data of solar insolation and temperature as well as household electricity demand and electricity prices are implemented for South Australia. Uncertainty analysis is investigated based on 10‐year real and stochastic data to prove the optimal results. It is found that the optimal configuration for a typical SA household utilising TOU pricing with an EV requires a 10‐kW SPV with a 10‐kWh capacity of BSS.

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Review on the state‐of‐the‐art multi‐objective optimisation of hybrid standalone/grid‐connected energy systems

Cited by 81 publications

References 177 publications

Optimal Sizing of Rooftop PV and Battery Storage for Grid-Connected Houses Considering Flat and Time-of-Use Electricity Rates

Optimal Sizing of Rooftop PV and Battery Storage for Grid-Connected Houses Considering Flat and Time-of-Use Electricity Rates

A multi‐objective optimization for planning of networked microgrid using a game theory for peer‐to‐peer energy trading scheme

Optimal planning of solar photovoltaic and battery storage for electric vehicle owner households with time‐of‐use tariff

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