Multi-objective optimal planning of the stand-alone microgrid system based on different benefit subjects

Guo, Li; Wang, Nan; Lu, Hai; Li, Xialin; Wang, Chengshan

doi:10.1016/j.energy.2016.09.123

Cited by 44 publications

(30 citation statements)

References 37 publications

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“…The main aim of the main optimization is to find a potential set of solutions for concerned planning problems. The prominent meta-heuristic techniques addressed in the literature (Table 3) include: genetic algorithm (GA) and associated evolutionary algorithms with various variants as in [122,128,131,137,139,143,147,152,155,157,162,165,166]. Also, PSO with various variants have addressed SDN planning problems as in [125,127,130,132,138,158,163].…”

Section: B Numerical Methodsmentioning

confidence: 99%

Smart Distribution Networks: A Review of Modern Distribution Concepts from a Planning Perspective

et al. 2017

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Smart grids (SGs), as an emerging grid modernization concept, is spreading across diverse research areas for revolutionizing power systems. SGs realize new key concepts with intelligent technologies, maximizing achieved objectives and addressing critical issues that are limited in conventional grids. The SG modernization is more noticeable at the distribution grid level. Thus, the transformation of the traditional distribution network (DN) into an intelligent one, is a vital dimension of SG research. Since future DNs are expected to be interconnected in nature and operation, hence traditional planning methods and tools may no longer be applicable. In this paper, the smart distribution network (SDN) concept under the SG paradigm, has presented and reviewed from the planning perspective. Also, developments in the SDN planning process have been surveyed on the basis of SG package (SGP). The package presents a SDN planning foundation via major SG-enabling technologies (SGTF), anticipated functionalities (SGAF), new consumption models (MDC) as potential SDN candidates, associated policies and pilot projects and multi-objective planning (MOP) as a real-world optimization problem. In addition, the need for an aggregated SDN planning model has also been highlighted. The paper discusses recent notable related works, implementation activities, various issues/challenges and potential future research directions; all aiming at SDN planning.

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Section: B Numerical Methodsmentioning

confidence: 99%

Smart Distribution Networks: A Review of Modern Distribution Concepts from a Planning Perspective

et al. 2017

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“…At present, the study of optimization of the microgrid operation mainly considers its economy and environmental protection including initial investment cost, operation and maintenance cost, sales income of power, government subsidy, and environment benefit. Guo et al [2] proposed a multiobjective optimization model for isolated microgrid system, which aimed at the confliction of interests between the distribution company and the distributed generation owners in the isolated microgrid system. The economic scheduling objective function in [3,4] considered the operation costs, environmental pollution of the power system, and the equipment type, while Chen et al [5] also considered the extra cost of battery.…”

Section: Introductionmentioning

confidence: 99%

Dual-Layer Optimal Dispatching Strategy for Microgrid Energy Management Systems considering Demand Response

Pan

Liu

et al. 2018

Mathematical Problems in Engineering

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The continuous development of microgrid’s technology creates favorable conditions for the access of distributed energy. Firstly, in order to consider the interests of the demand side and the power side, this paper presents a dual-layer optimal dispatching model of microgrid based on demand response. The objective of the first-layer optimization is to obtain the maximum load satisfaction and to optimize the load curve. The objective of the second-layer optimization is to make the microgrid system economical and environmentally friendly and to optimize the power utilization ratio. And a microsource control strategy based on the isolated microgrid is proposed, which can optimize the operation state of battery and improve the economy of the system. Finally, the Nondominated Sorting Genetic Algorithm-II (NSGA-II) is adopted to solve the optimal scheduling problem of the isolated microgrid. The simulation results indicate that the microsource scheduling strategy proposed in this paper can improve the operation economy and environmental conservation of the system. It can improve the reliability of microgrid power supply and reduce energy waste.

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“…where N max is the maximum induced speed, α local,i and α target,i are neighbor's local effect and best krill's target direction effect, ω n is the inertia weight of the motion induced in range [0,1] and N old,i is the old motion induced for i th krill individual. The foraging motion can be written as: where ∆t is derived from the difference between the upper and lower limits of the design variables.…”

Section: Main Concepts Of Krill Herd and Ant Lion Algorithmsmentioning

confidence: 99%

“…Guo et al [1] determined the optimal sites and sizes of RESs installed in typical micro-grid via formulating multiobjective function comprising the contract price between distribution company (Disco) and distributed generation owner (DGO). Non-dominated sorting genetic algorithm (NSGA-II) has been used for solving the presented problem.…”

Section: Introductionmentioning

confidence: 99%

Single and multi-objective operation management of micro-grid using krill herd optimization and ant lion optimizer algorithms

Fathy

Abdelaziz

2018

Int J Energy Environ Eng

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In this paper, two recent heuristic optimization algorithms are presented to optimally manage the operation of the microgrid (MG) with installed renewable energy sources (RESs); krill herd (KH) optimization and ant lion optimizer (ALO) algorithms. The first algorithm is used for solving single-objective function represents either total operation cost or total pollutant emission injected from the installed generating units while ALO is applied to solve the multi-objective function of both total operating cost and emission. The problem is formulated as nonlinear constrained objective function with equality and inequality constraints. In this work; the devices installed in MGs are photovoltaic panel (PV), wind turbine (WT), microturbine (MT), fuel cell (FC), battery and grid. Two scenarios are studied; the first one is optimizing MG with installing all RESs within specified limits in addition to grid, while the second scenario is operating both PV and WT at their rated powers. The obtained results are compared with different reported algorithms like genetic algorithm (GA), Fuzzy self-adaptive PSO (FSAPSO) and others programmed like particle swarm optimization (PSO), grey-wolf optimizer (GWO) and whale optimization algorithm (WOA). For first scenario; the proposed KH gives the best optimal cost of 105.94 €ct while the best emission is 420.57 kg, the best optimal cost and emission of 592.86 €ct 339.71 kg are obtained via KH in the second scenario.

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Multi-objective optimal planning of the stand-alone microgrid system based on different benefit subjects

Cited by 44 publications

References 37 publications

Smart Distribution Networks: A Review of Modern Distribution Concepts from a Planning Perspective

Smart Distribution Networks: A Review of Modern Distribution Concepts from a Planning Perspective

Dual-Layer Optimal Dispatching Strategy for Microgrid Energy Management Systems considering Demand Response

Single and multi-objective operation management of micro-grid using krill herd optimization and ant lion optimizer algorithms

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