Stochastic optimization for power system configuration with renewable energy in remote areas

Kuznia, Ludwig; Zeng, Bo; Centeno, Grisselle; Miao, Zhixin

doi:10.1007/s10479-012-1110-9

Cited by 49 publications

(26 citation statements)

References 20 publications

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“…When P avai (t) < P L (t), the reliability analysis is significant. There are various methods for carrying out the reliability analysis: the LPSP, defined as Equation (19), is one of the widely-used methodologies for this purpose.…”

Section: Reliabilitymentioning

confidence: 99%

“…(c) Solving algorithm: Many authors have investigated some classical algorithms for sizing stand-alone hybrid systems based on renewable sources and storage devices [8,[18][19][20]. In [18], a nonlinear programming has been used to find the optimal sizing and location of grid-connected wind turbines based on the simulation of various scenarios.…”

Section: Introductionmentioning

confidence: 99%

“…In [18], a nonlinear programming has been used to find the optimal sizing and location of grid-connected wind turbines based on the simulation of various scenarios. Akella [9], Kellogg and Nehrir [7] and Kuznia et al [19] have adopted different linear programming models to optimize the design of a hybrid system. In [20], Malheiro and Castro have addressed the sizing and scheduling of hybrid isolated systems via a mixed-integer linear programming.…”

Section: Introductionmentioning

confidence: 99%

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Optimal Sizing of a Stand-Alone Hybrid Power System Based on Battery/Hydrogen with an Improved Ant Colony Optimization

Dong

Xiang

2016

Energies

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A distributed power system with renewable energy sources is very popular in recent years due to the rapid depletion of conventional sources of energy. Reasonable sizing for such power systems could improve the power supply reliability and reduce the annual system cost. The goal of this work is to optimize the size of a stand-alone hybrid photovoltaic (PV)/wind turbine (WT)/battery (B)/hydrogen system (a hybrid system based on battery and hydrogen (HS-BH)) for reliable and economic supply. Two objectives that take the minimum annual system cost and maximum system reliability described as the loss of power supply probability (LPSP) have been addressed for sizing HS-BH from a more comprehensive perspective, considering the basic demand of load, the profit from hydrogen, which is produced by HS-BH, and an effective energy storage strategy. An improved ant colony optimization (ACO) algorithm has been presented to solve the sizing problem of HS-BH. Finally, a simulation experiment has been done to demonstrate the developed results, in which some comparisons have been done to emphasize the advantage of HS-BH with the aid of data from an island of Zhejiang, China.Keywords: hybrid system based on battery and hydrogen (HS-BH); hydrogen storage subsystem; ant colony optimization (ACO); annual system cost; loss of power supply probability (LPSP)

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Section: Reliabilitymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Optimal Sizing of a Stand-Alone Hybrid Power System Based on Battery/Hydrogen with an Improved Ant Colony Optimization

Dong

Xiang

2016

Energies

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“…On the other hand dynamic programming (usually involving quantization) and mixed integer algorithms can help to find the expected cost benefit of charging at specific times [19]. Finally there are a number of industry specific approaches coming from operations research, that deal with the question of optimal load shifting and scheduling using a limited capacity [20][21]. However, the complexity is significant, and while such approaches may be worthwhile for the management of large storage elements such as pumped-storage hydroelectric machines, they are not suitable for domestic applications at this point.…”

Section: Stochastic Pricesmentioning

confidence: 99%

Optimal Charging of EVs in a Real Time Pricing Electricity Market

Mody¹,

Steffen²

2013

SAE Int. J. Alt. Power.

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The idea of grid friendly charging is to use electricity from the grid to charge batteries when electricity is available in surplus and cheap. There are several ways of achieving this, for example using droop control, using night time electricity tariffs, or using smart metering. The goal is twofold: to avoid putting additional load on the electricity grid and power generation, and to reduce the cost to the consumer. This paper looks at the saving potential when charging an electric car using real time tariffs provided by a smart meter, using the Ameren tariffs in Illinois as an example. If prices are known in advance (day-ahead pricing), the optimization only requires picking the cheapest time slots for charging the battery. Further savings can be made by using real time prices that are not known in advance, but the optimization problem then depends on price prediction models, and it becomes much more difficult to solve. This paper presents a simple suboptimal approach, and it quantifies the potential improvements that could be made using more sophisticated price predictions.The result is that cost savings in the order of about 50 USD (1/3 of the electricity costs) are feasible if a fast charger is used using real time pricing. The scale of the savings is such that complex optimization strategies are not worthwhile, and for the foreseeable future simple solutions are expected to be more cost effective.

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“…Extending the main utility grids to these remote locations is possible, but not cost effective [1][2]. Hence, electricity is usually provided to these remote areas through stand-alone power systems.…”

Section: Introductionmentioning

confidence: 99%

Fuzzy Energy Management for Photovoltaic Water Pumping System

Yahyaoui¹,

Chaabene²,

Tadeo³

2015

IJCA

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A Fuzzy energy management algorithm for a photovoltaic water pumping installation is presented and validated experimentally, using a plant composed of photovoltaic panels, battery banks, DC/AC converters, relays and a water pump. Considering many criteria related to the battery safe operation, fulfilling the water volume needed by the crops and ensuring a continuous function of the pump, the algorithm decides the switching of the relays, which link the installation' components. The algorithm is evaluated for a specific case study: tomato irrigation in Tunisia. Obtained results confirm that the irrigation water demand is covered during the season with a minimum use of the battery. General TermsFuzzy logic, Photovoltaic Energy management.

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Stochastic optimization for power system configuration with renewable energy in remote areas

Cited by 49 publications

References 20 publications

Optimal Sizing of a Stand-Alone Hybrid Power System Based on Battery/Hydrogen with an Improved Ant Colony Optimization

Optimal Sizing of a Stand-Alone Hybrid Power System Based on Battery/Hydrogen with an Improved Ant Colony Optimization

Optimal Charging of EVs in a Real Time Pricing Electricity Market

Fuzzy Energy Management for Photovoltaic Water Pumping System

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