Demand side management of photovoltaic-battery hybrid system

Wu, Zhou; Tazvinga, Henerica; Xia, Xiaohua

doi:10.1016/j.apenergy.2015.03.109

Cited by 241 publications

(89 citation statements)

References 48 publications

(74 reference statements)

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“…Now approximately 40% of global energy consumption is attributed to residential, office and commercial buildings. As there are a large number of old buildings equipped with out-of-date facilities, whose operations may be also inefficiently scheduled, it has great potential to decelerate the increasing rate of energy demand or possibly reduce total demand in the building sector [1]. For this purpose, an intuitive but costly way to improve existing buildings is to replace them with new green buildings.…”

Section: Introductionmentioning

confidence: 99%

Large-scale building energy efficiency retrofit: Concept, model and control

Wang

Xia

2016

Energy

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Building energy efficiency retrofit (BEER) projects are initiated in many nations and regions over the world. Existing studies of BEER focus on modeling and planning based on one building and one year period of retrofitting, which cannot be applied to certain large BEER projects with multiple buildings and multi-year retrofit. In this paper, the large-scale BEER problem is defined in a general time-building-technology (TBT) framework, which fits essential requirements of real-world projects. The large-scale BEER is newly studied in the control approach rather than the optimization approach commonly used before. Optimal control is proposed to design optimal retrofitting strategy in terms of maximal energy savings and maximal net present value (NPV). The designed strategy is dynamically changing on dimensions of time, building and technology. The TBT framework and the optimal control approach are verified in a large BEER project, and results indicate that promising performance of energy and cost savings can be achieved in the general TBT framework.

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Section: Introductionmentioning

confidence: 99%

Large-scale building energy efficiency retrofit: Concept, model and control

Wang

Xia

2016

Energy

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“…The time periods for operating these elastic loads can be determined by the time-of-use tariff, PV generation, a capacity contract, cost of the fuel of the micro-turbine generator and other operational constraints. The uncertainty of PV power output was addressed by many papers [21][22][23][24][25][26][27][28][29][30][31][32]. In this paper, the uncertainty of PV power is modeled using stochastic distributions.…”

Section: Introductionmentioning

confidence: 99%

Novel Genetic Algorithm-Based Energy Management in a Factory Power System Considering Uncertain Photovoltaic Energies

Hong

2017

Applied Sciences

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Abstract:The demand response and accommodation of different renewable energy resources are essential factors in a modern smart microgrid. This paper investigates the energy management related to the short-term (24 h) unit commitment and demand response in a factory power system with uncertain photovoltaic power generation. Elastic loads may be activated subject to their operation constraints in a manner determined by the electricity prices while inelastic loads are inflexibly fixed in each hour. The generation of power from photovoltaic arrays is modeled as a Gaussian distribution owing to its uncertainty. This problem is formulated as a stochastic mixed-integer optimization problem and solved using two levels of algorithms: the master level determines the optimal states of the units (e.g., micro-turbine generators) and elastic loads; and the slave level concerns optimal real power scheduling and power purchase/sale from/to the utility, subject to system operating constraints. This paper proposes two novel encoding schemes used in genetic algorithms on the master level; the point estimate method, incorporating the interior point algorithm, is used on the slave level. Various scenarios in a 30-bus factory power system are studied to reveal the applicability of the proposed method.

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“…However, domestic consumers are hardly aware of the direct and indirect benefits of the water-energy nexus savings at home [10], such as; energy savings for purifying water, utility pumping and corresponding CO 2 reduction [11], energy savings from the waste water purification and lower cost for potable water and waste water management [12]. Whilst most research in South Africa has concentrated on energy efficiency [13,14,15] and electrical demand side management [16,17,18], little attention has been given to water demand management and its effect on energy consumption [19,20].…”

Section: Introductionmentioning

confidence: 99%

Energy-water optimization model incorporating rooftop water harvesting for lawn irrigation

Wanjiru

Xia

2015

Applied Energy

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The management of energy and water is increasingly gaining attention among domestic end-users. In developing countries, potable water supply is unreliable leading to alternative strategies such as rooftop water harvesting (RWH), storage and pumping. Since urban garden irrigation is the highest outdoor water consumer, optimal scheduling is important to conserve energy and water over conventional lawn irrigation methods. A model to optimally control the lawn irrigation was developed with the simulation results showing 17.4% potential water savings when using water directly from municipal sources. With RWH of a 1-hr event with 1-mm rainfall from a 120-m 2 roof, the model can potentially save 23.4% of water and 73.8% in energy costs per day. Such savings are important in reducing the demand for existing water and energy sources as well as greenhouse emissions. Further, this paper looks into two strategies to maximize the pump's life through minimizing the maintenance cost.Keywords: buildings, energy, optimal scheduling, rooftop water harvesting, time-of-use tariff, water

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Demand side management of photovoltaic-battery hybrid system

Cited by 241 publications

References 48 publications

Large-scale building energy efficiency retrofit: Concept, model and control

Large-scale building energy efficiency retrofit: Concept, model and control

Novel Genetic Algorithm-Based Energy Management in a Factory Power System Considering Uncertain Photovoltaic Energies

Energy-water optimization model incorporating rooftop water harvesting for lawn irrigation

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