Multi-Objective Optimisation of an Active Distribution System using Normalised Normal Constraint Method

Saffari, Mohammadali; Misaghian, M. Saeed; Flynn, Damian; Kia, Mohsen; Vahidinasab, Vahid; Lotfi, Mohamed; Catalào, João P. S.; Shafie‐khah, Miadreza

doi:10.1109/ptc.2019.8810778

Cited by 4 publications

(5 citation statements)

References 26 publications

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“…Equation (10), which represents the battery power during discharging when the SoC exceeds the RESs, may be derived from the previously mentioned facts.…”

Section: Battery Mathematical Modelingmentioning

confidence: 99%

“…A multi-objective optimization approach utilizing the Normalized Normal Constraint (NNC) was utilized to evaluate two competing objectives: minimizing the operating costs of the Active Distribution System (ADS) and minimizing the power losses in the ADS [10]. In the interim, variable wind patterns, solar systems, and electric car arrival and departure timings are considered.…”

Section: Introductionmentioning

confidence: 99%

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Optimal Design of Grid-Connected Hybrid Renewable Energy System Considering Electric Vehicle Station Using Improved Multi-Objective Optimization: Techno-Economic Perspectives

Al-Sahlawi,

Ayob,

Tan

et al. 2024

Sustainability

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Electric vehicle charging stations (EVCSs) and renewable energy sources (RESs) have been widely integrated into distribution systems. Electric vehicles (EVs) offer advantages for distribution systems, such as increasing reliability and efficiency, reducing pollutant emissions, and decreasing dependence on non-endogenous resources. In addition, vehicle-to-grid (V2G) technology has made EVs a potential form of portable energy storage, alleviating the random fluctuation of renewable energy power. This paper simulates the optimal design of a photovoltaic/wind/battery hybrid energy system as a power system combined with an electric vehicle charging station (EVCS) using V2G technology in a grid-connected system. The rule-based energy management strategy (RB-EMS) is used to control and observe the proposed system power flow. A multi-objective improved arithmetic optimization algorithm (MOIAOA) concept is proposed to analyze the optimal sizing of the proposed system components by calculating the optimal values of the three conflicting objectives: grid contribution factor (GCF), levelled cost of electricity (LCOE), and energy sold to the grid (ESOLD). This research uses a collection of meteorological data such as solar radiation, temperature, and wind speed captured every ten minutes for one year for a government building in Al-Najaf Governorate, Iraq. The results indicated that the optimal configuration of the proposed system using the MOIAOA method consists of eight photovoltaic modules, two wind turbines, and thirty-three storage batteries, while the fitness value is equal to 0.1522, the LCOE is equal to 2.66 × 10−2 USD/kWh, the GCF is equal to 7.34 × 10−5 kWh, and the ESOLD is equal to 0.8409 kWh. The integration of RESs with an EV-based grid-connected system is considered the best choice for real applications, owing to their remarkable performance and techno-economic development.

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“…Equation (10), which represents the battery power during discharging when the SoC exceeds the RESs, may be derived from the previously mentioned facts.…”

Section: Battery Mathematical Modelingmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Optimal Design of Grid-Connected Hybrid Renewable Energy System Considering Electric Vehicle Station Using Improved Multi-Objective Optimization: Techno-Economic Perspectives

Al-Sahlawi,

Ayob,

Tan

et al. 2024

Sustainability

View full text Add to dashboard Cite

show abstract

“…Additionally, we show the cost of EVs active power in the second line of (23) [32] EVs charging/discharging constrains for both active and reactive powers are illustrated in (24) and (25). Equation (26) indicates EV storage power balance. We show the capacity limit of EV storage and the EV energy at the departure time in (27).…”

Section: Electric Vehiclesmentioning

confidence: 99%

“…In [25], the authors suggest a multiobjective optimisation method to solve the transmission congestion problem, where the NNC method is applied to discover the optimal solutions. Saffari et al [26] propose a multi-objective framework based on NNC method to optimise an ADN. They consider the biobjective operation of an ADN in their proposed model.…”

mentioning

confidence: 99%

“…This normalised space has the desirable property that the method's performance is entirely independent of the objectives' scales [14]. (III) The NNC produces a Pareto optimal with a regularly distributed set of points, even distribution of Pareto solutions is an indication that the solution space is well represented in the Pareto points [26]. (IV) NNC method is able to generate a well-distributed set of Pareto points even in numerically demanding (ill-conditioned) situations.…”

mentioning

confidence: 99%

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Integrated active/reactive power scheduling of interdependent microgrid and EV fleets based on stochastic multi‐objective normalised normal constraint

Saffari

Kia

Vahidinasab

et al. 2020

IET Generation, Transmission & Distribution

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This study proposes an integrated framework for coordinated optimisation of the interdependent microgrid (MG) and electric vehicle (EV) fleet entities using the normalised normal constraint approach. By considering the active/reactive power management option of the bidirectional charger enabled EVs in the proposed model, the authors investigate the effectiveness of EV's integration in the presence of the techno-economical objective functions. This work concentrates on the trade-off analysis of two conflicting objectives, including the economic objective of the MG's operation cost minimisation and the technical objective of the MG's voltage deviation. Besides, they consider several uncertainty sources, e.g. wind, EV and solar panel (PV) power provision, as well as market price fluctuations in the proposed model affecting the aforementioned techno-economic trade-off solution. The proposed model is a stochastic multi-objective mixed-integer non-linear programming problem where the authors apply the designed integrated framework on a modified IEEE 18-bus test case in GAMS software. Through numerical results, they demonstrate MG optimal operation changes due to different MGO priorities and study the positive effects of EVs integrated energy management on the bi-objective operation. Nomenclature Sets RL cost function of responsive loads Superscript max/min and C/D with any of the above notations indicate the maximum/minimum value and charge/discharge status. Set • runs from 1 to N •

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A Linear Stochastic Formulation for Distribution Energy Management Systems Considering Lifetime Extension of Battery Storage Devices

2022

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Recently, the number of Battery Energy Systems (BESs) connected to the grid has grown significantly. These assets can alleviate some operational issues such as demand surges and occasional power fluctuations associated with the Renewable Energy Sources (RESs) connected to the grid. Nonetheless, both overcharging and frequent usage severely affect their health status and shorten their life expectancy. In this paper, an Energy Management System (EMS) framework with a linearised algorithm and in-depth analysis on BES life extension is presented, which optimises the techno-economic aspects of an Active Distribution Network (ADN) connected to RESs. By applying a mathematical linearisation formulation, a Mixed-Integer Linear Programming (MILP) model is proposed for linearising the Optimal Power Flow (OPF) problem. This technique, which has the merit of fair accuracy while having high speed, is used for scheduling BESs to increase their durability and decrease grid costs. To consider the inherent uncertainty associated with demand and RES generation, a two-stage Stochastic Programming (SP) method is implemented in the proposed model. In terms of battery Loss of Health (LoH) assessment, a linearised battery lifetime method is introduced. Ultimately, a modified 33-bus radial distribution test system with a day-ahead Real-Time Pricing (RTP) program was chosen to apply the proposed algorithm and assess its efficiency.INDEX TERMS Energy management system (EMS), optimal power flow (OPF), linearised AC-OPF, battery scheduling, battery degradation, rain-flow cycle counting, day-ahead pricing. NOMENCLATURE A. INDICES & SETS C BES bat Purchasing cost of bat energy storage system [$]. λ Piecewise linearisation segments for linearising AC-OPF model [-]. p ω Probability of scenario ω [-].C. BINARY VARIABLES q ij,t,ω Line power exchange between bus i and j [-].

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Multi-Objective Optimisation of an Active Distribution System using Normalised Normal Constraint Method

Cited by 4 publications

References 26 publications

Optimal Design of Grid-Connected Hybrid Renewable Energy System Considering Electric Vehicle Station Using Improved Multi-Objective Optimization: Techno-Economic Perspectives

Optimal Design of Grid-Connected Hybrid Renewable Energy System Considering Electric Vehicle Station Using Improved Multi-Objective Optimization: Techno-Economic Perspectives

Integrated active/reactive power scheduling of interdependent microgrid and EV fleets based on stochastic multi‐objective normalised normal constraint

A Linear Stochastic Formulation for Distribution Energy Management Systems Considering Lifetime Extension of Battery Storage Devices

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