Residential demand response considering distributed PV consumption: A model based on China's PV policy

Lu, Qing; Yu, Hao; Zhao, Kangli; Li, Yajun; Hou, Jianchao; Xie, Pinjie

doi:10.1016/j.energy.2019.01.097

Cited by 40 publications

(15 citation statements)

References 41 publications

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“…Such approaches may include particle swarm optimization [26], genetic algorithms [27], differential evolution [28], cuckoo search [29], among others. From the circuit shown in Figure 1, it is possible to write an implicit equation that describes the relationship between the submodule's output voltage (V) and current (I), as shown in (1), where I sat and η are the inverse saturation current, and ideality factor of D, respectively, V t,d is the diode thermal voltage and I bd is the current through BD. The thermal voltage is defined as V t,d = k • T/q, where k is the Boltzmann constant, q is the electron charge and T is the cell's temperature in K. Moreover, I db is defined in (2), where I sat,bd and η bd are the inverse saturation current and ideality factor of BD.…”

Section: Submodule Modelmentioning

confidence: 99%

“…The continuous effects of climate change and environmental contamination have motivated a growing interest in the use of renewable energies to replace conventional energy sources based on fossil fuels. Within renewable energies, photovoltaic (PV) energy offers interesting advantages: long life cycle, lack of mobile parts, low maintenance costs, modularity, among others [1]; that is why the installed PV capacity has been growing in the last years [2]. In a PV system, one of the most important elements is the generator; therefore, it is important to have models of this element to reproduce its electrical behavior when they operate under homogeneous and non-homogeneous conditions [3].…”

Section: Introductionmentioning

confidence: 99%

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A Solution of Implicit Model of Series-Parallel Photovoltaic Arrays by Using Deterministic and Metaheuristic Global Optimization Algorithms

et al. 2020

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The implicit model of photovoltaic (PV) arrays in series-parallel (SP) configuration does not require the LambertW function, since it uses the single-diode model, to represent each submodule, and the implicit current-voltage relationship to construct systems of nonlinear equations that describe the electrical behavior of a PV generator. However, the implicit model does not analyze different solution methods to reduce computation time. This paper formulates the solution of the implicit model of SP arrays as an optimization problem with restrictions for all the variables, i.e., submodules voltages, blocking diode voltage, and strings currents. Such an optimization problem is solved by using two deterministic (Trust-Region Dogleg and Levenberg Marquard) and two metaheuristics (Weighted Differential Evolution and Symbiotic Organism Search) optimization algorithms to reproduce the current–voltage (I–V) curves of small, medium, and large generators operating under homogeneous and non-homogeneous conditions. The performance of all optimization algorithms is evaluated with simulations and experiments. Simulation results indicate that both deterministic optimization algorithms correctly reproduce I–V curves in all the cases; nevertheless, the two metaheuristic optimization methods only reproduce the I–V curves for small generators, but not for medium and large generators. Finally, experimental results confirm the simulation results for small arrays and validate the reference model used in the simulations.

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Section: Submodule Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A Solution of Implicit Model of Series-Parallel Photovoltaic Arrays by Using Deterministic and Metaheuristic Global Optimization Algorithms

et al. 2020

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“…On one hand, employment of classical algorithms consists of implementing linear programming [4], nonlinear programming, mixed-integer linear programming [5][6][7][8] or mixed-integer nonlinear programming. On the other hand, implementation of metaheuristic techniquessuch as particle swarm optimization, genetic algorithm (GA) [9], simulated annealing, and teaching learningbased optimizationdepends on the structure and coding of the problem under analysis. In a general sense, the technique to be used depends on the characteristics of a specific problem and its mathematical formulation.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Proper usage of DR resources available from users enrolled in the proposed DLC scheme is determined by solving the optimization problem shown in (5)(6)(7)(8)(9)(10)(11)(12)(13)(14)(15)(16)(17)(18), where the first two expressions represent the variable to be optimized and the rest of the equations are the constraints related to the ES's physical limitations.…”

Section: Optimal Allocation Of Dr Resources Under Total Certainty Of Wind Generationmentioning

confidence: 99%

Contract design of direct-load control programs and their optimal management by genetic algorithm

Lujano-Rojas

Zubi

Dufo-López

et al. 2019

Energy

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A computational model for designing direct-load control (DLC) demand response (DR) contracts is presented in this paper. The critical and controllable loads are identified in each node of the distribution system (DS). Critical loads have to be supplied as demanded by users, while the controllable loads can be connected during a determined time interval. The time interval at which each controllable load can be supplied is determined by means of a contract or compromise established between the utility operator and the corresponding consumers of each node of the DS. This approach allows us to reduce the negative impact of the DLC program on consumers' lifestyles. Using daily forecasting of wind speed and power, solar radiation and temperature, the optimal allocation of DR resources is determined by solving an optimization problem through a genetic algorithm where the energy content of conventional power generation and battery discharging energy are minimized. The proposed approach was illustrated by analyzing a system located in the Virgin Islands. Capabilities and characteristics of the proposed method in daily and annual terms are fully discussed, as well as the influence of forecasting errors.

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“…Lu vd. [16] fotovoltaik (PV) panellere sahip belirli bir sayıda evin tüketim değerlerini, üretim değerlerine göre ayarlayabilmek ve bu sayede bir enerji depolama sistemine olabilecek ihtiyacı ortadan kaldırabilmek amacıyla talep cevabı tabanlı bir enerji yönetimi algoritması önermişlerdir. Aynı amaçla Venizelou vd.…”

Section: Introductionunclassified

Paylaşımlı Elektrik Enerjisi Depolama Sisteminin Kullanımına Dayanan Bir Enerji Yönetimi Yaklaşımı

Taşçıkaraoğlu¹,

Erdinç²

2019

European Journal of Science and Technology

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Öz Bu çalışmada, bir paylaşımlı elektrik enerjisi depolama sistemi kullanan ve aynı bölge içerisinde yer alan belli bir sayıdaki evsel tüketicinin toplam enerji maliyetini en aza indirebilmek ve bu evlerin bağlı olduğu dağıtım şebekesindeki pik yük talebini azaltabilmek amacıyla bir tahmin algoritmasına dayanan bir enerji yönetimi yaklaşımı önerilmektedir. Önerilen yöntem, farklı güçlerde fotovoltaik (PV) panellere sahip olan evlere ait elektrik üretimi ve tüketimi miktarlarını, bu değerlere ait farklı zaman ölçeklerindeki tahminleri ve bir gerçek zamanlı fiyatlama elektrik tarifesine ait değişken fiyatları dikkate alarak, evler tarafından üretilen elektrik enerjisinden en yüksek seviyede faydalanmayı hedeflemektedir. Bu amaçla, her bir eve ait üretim, öncelikle evin kendisinin tüketimini karşılamak amacıyla kullanılmaktadır. İhtiyaç fazlası üretimin mevcut olması durumunda ise üretilen enerji belirtilen değişkenler dikkate alınarak bölge içerisindeki diğer evlerin tüketimi için kullanılmakta, paylaşımlı depolama sisteminde depolanmakta veya şebekeye satılmaktadır. Önerilen yaklaşımına göre evler, şebekeye veya bölgedeki diğer evlere sağladıkları enerji miktarı oranında enerji kredileri kazanmaktadırlar ve bu kredilere karşılık gelecek miktarda enerjiyi paylaşımlı enerji depolama sisteminden, özellikle elektrik satın alma fiyatının yüksek olduğu zaman dilimlerinde kullanarak önemli bir maddi kazanç elde etmektedirler. Belirli bir sayıda evsel tüketiciye ait gerçek yük talebi ve PV güç üretimi verileri kullanılarak yapılan benzetim çalışmalarında, paylaşımlı enerji depolama sisteminin var olmadığı durumda elde edilen sonuçlar ile ve depolama sisteminin var olduğu ancak ilgili tahmin değerlerinin göz önüne alınmadığı durumda elde edilen sonuçlar ile karşılaştırmalar yapılmıştır. Belirtilen karşılaştırmalar, önerilen paylaşımlı enerji depolama sistemi ve tahmin algoritması kullanımına dayanan enerji yönetimi yaklaşımının son kullanıcı açısından enerji maliyetini azaltmakta ve dağıtım sistemi işletmecisi açısından pik yük talebini sınırlamakta etkili olduğunu göstermiştir.

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Residential demand response considering distributed PV consumption: A model based on China's PV policy

Cited by 40 publications

References 41 publications

A Solution of Implicit Model of Series-Parallel Photovoltaic Arrays by Using Deterministic and Metaheuristic Global Optimization Algorithms

A Solution of Implicit Model of Series-Parallel Photovoltaic Arrays by Using Deterministic and Metaheuristic Global Optimization Algorithms

Contract design of direct-load control programs and their optimal management by genetic algorithm

Paylaşımlı Elektrik Enerjisi Depolama Sisteminin Kullanımına Dayanan Bir Enerji Yönetimi Yaklaşımı

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