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Proceedings ArticleDOI

Demand side management for residential areas using hybrid bacterial foraging and bat optimization algorithm: Demand side management using hybrid bacterial foraging and bat optimization algorithm

TL;DR: Results show that proposed technique has significantly reduced electricity cost and peak-to-average ratio and consumers have not only supposed to pay less electricity bill, however, utilities also have to bear less stress especially in on-peak hours.
Abstract: In this work, two meta-heuristic bio-inspired algorithms and our proposed hybrid technique (Bacterial foraging optimization algorithm (BFA) and BAT algorithm (BA) (HBB)) are proposed for optimizing and scheduling the appliances of residential consumers. BFA, BA and our proposed technique HBB are used for scheduling the appliances in order to find the optimal solution. Appliances have different power ratings and power consumption patterns. Three different operational time intervals of 5, 30 and 60 minutes are taken in this work and their comparison is carried out. Eighteen appliances are considered and they are classified into three categories: interruptible, non-interruptible and base load appliances. Single home scenario is considered in this work. Results show that proposed technique has significantly reduced electricity cost and peak-to-average ratio. Consumers have not only supposed to pay less electricity bill, however, utilities also have to bear less stress especially in on-peak hours.
Citations
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Journal ArticleDOI
TL;DR: This paper presents an efficient home energy management system (HEMS) for consumer appliance scheduling in the presence of an energy storage system and photovoltaic generation with the intention to reduce the energy consumption cost determined by the service provider.
Abstract: The transformation of a conventional power system to a smart grid has been underway over the last few decades. A smart grid provides opportunities to integrate smart homes with renewable energy resources (RERs). Moreover, it encourages the residential consumers to regulate their home energy consumption in an effective way that suits their lifestyle and it also helps to preserve the environment. Keeping in mind the techno-economic reasons for household energy management, active participation of consumers in grid operations is necessary for peak reduction, valley filling, strategic load conservation, and growth. In this context, this paper presents an efficient home energy management system (HEMS) for consumer appliance scheduling in the presence of an energy storage system and photovoltaic generation with the intention to reduce the energy consumption cost determined by the service provider. To study the benefits of a home-to-grid (H2G) energy exchange in HEMS, photovoltaic generation is stochastically modelled by considering an energy storage system. The prime consideration of this paper is to propose a hybrid optimization approach based on heuristic techniques, grey wolf optimization, and a genetic algorithm termed a hybrid grey wolf genetic algorithm to model HEMS for residential consumers with the objectives to reduce energy consumption cost and the peak-to-average ratio. The effectiveness of the proposed scheme is validated through simulations performed for a residential consumer with several domestic appliances and their scheduling preferences by considering real-time pricing and critical peak-pricing tariff signals. Results related to the reduction in the peak-to-average ratio and energy cost demonstrate that the proposed hybrid optimization technique performs well in comparison with different meta-heuristic techniques available in the literature. The findings of the proposed methodology can further be used to calculate the impact of different demand response signals on the operation and reliability of a power system.

34 citations


Cites methods from "Demand side management for resident..."

  • ...Models based on evolutionary algorithms were proposed in References [23,24] to solve an energy-based optimization problem in a residential area....

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  • ...Various applications of heuristic algorithms in green and sustainable energy systems are reviewed in References [15,16]....

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  • ...This study used an already developed probabilistic model based on a beta distribution for the modeling of solar irradiance and PV pattern generation, as reported in References [44,45]....

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  • ...John Holland was the first to develop the basic GA in 1975 [48], and more explanations are given in References [49–51]....

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  • ...DR programs play a significant role in a smart grid operation by scheduling household appliances from away from high-tariff time slots to low-tariff time slots according to time-based electricity tariffs, which are explained in References [9,12]....

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Proceedings ArticleDOI
01 Oct 2018
TL;DR: Some congestion management methods are reviewed dividing them into various sections Market based methods, Conventional Optimization methods, Artificial Intelligence Approaches, and various optimization techniques that are being used are briefed in the paper.
Abstract: With the increase in population and subsequently increasing demand of electricity the power sector industry is under deregulation. Restructuring in electricity sector has changed the definition of this market. With its development it has not only changed the way electricity was traded earlier but also given birth to issues like congestion. Congestion not only effect the flow of power but also give ways to various other issues like market power, market inefficiency and security. Congestion take place when transmission line exceeds any of their limits (voltage, thermal, stability). Congestion management is a technique that help us to solve the problem related to congestion. Several methods have been developed for managing congestion and different countries implement different method for their smooth operation of network. This paper review some congestion management methods dividing them into various sections Market based methods, Conventional Optimization methods, Artificial Intelligence Approaches. Various optimization techniques that are being used are briefed in the paper. The work of various publications are reviewed and Hybrid market significance is discussed.

7 citations


Cites background from "Demand side management for resident..."

  • ...The algorithm help in finding the optimal solution for scheduling the appliances [57]....

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Journal ArticleDOI
TL;DR: The proposed HGOA got better power scheduling arrangements and better performance than other comparative algorithms using the classical benchmark functions and according to the computational time, it runs in constant execution time as the population is increased.
Abstract: With the increasing number of electricity consumers, production, distribution, and consumption problems of produced energy have appeared. This paper proposed an optimization method to reduce the peak demand using smart grid capabilities. In the proposed method, a hybrid Grasshopper Optimization Algorithm (GOA) with the self-adaptive Differential Evolution (DE) is used, called HGOA. The proposed method takes advantage of the global and local search strategies from Differential Evolution and Grasshopper Optimization Algorithm. Experimental results are applied in two scenarios; the first scenario has universal inputs and several appliances. The second scenario has an expanded number of appliances. The results showed that the proposed method (HGOA) got better power scheduling arrangements and better performance than other comparative algorithms using the classical benchmark functions. Moreover, according to the computational time, it runs in constant execution time as the population is increased. The proposed method got 0.26 % enhancement compared to the other methods. Finally, we found that the proposed HGOA always got better results than the original method in the worst cases and the best cases.

6 citations

Proceedings ArticleDOI
01 Dec 2019
TL;DR: An optimization algorithm for HEM considering appliance scheduling flexibility is proposed with the aim of electricity bill cost minimization and results show the effectiveness of the algorithm in minimizing the Electricity bill cost.
Abstract: Home Energy Management (HEM) is considered a great potential for energy efficiency in smart grids. With the advent of advanced metering infrastructure (AMI), demand side management (DSM) become possible where households (HHs) change their consumption behavior in response to electricity time varying prices provided by the utility. An optimization algorithm for HEM considering appliance scheduling flexibility is proposed with the aim of electricity bill cost minimization. The appliance scheduling is done on weekly basis to be able to model a more realistic scenario which is able to shift the operation of some appliances that aren't required to operate daily throughout the week. The problem is formulated as a binary integer programming (BIP) problem. Single home scenario is considered in this work. Real time pricing (RTP) is considered to be the electricity pricing tariff that incentivize the users to adjust their energy consumption. The performance of the proposed algorithm is tested under different simulation scenarios. Results show the effectiveness of the algorithm in minimizing the electricity bill cost.

Cites methods from "Demand side management for resident..."

  • ...In [8], scheduling of HH appliances was done using bio-inspired metaheuristic techniques with the aim of peak-toaverage ratio (PAR) and electricity bill cost minimization....

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References
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Journal ArticleDOI
TL;DR: The main industry drivers of smart grid and the different facets of DER under the smart grid paradigm are explored and the existing and evolving programs at different ISOs/RTOs and the product markets they can participate in are summarized.
Abstract: Demand response (DR), distributed generation (DG), and distributed energy storage (DES) are important ingredients of the emerging smart grid paradigm. For ease of reference we refer to these resources collectively as distributed energy resources (DER). Although much of the DER emerging under smart grid are targeted at the distribution level, DER, and more specifically DR resources, are considered important elements for reliable and economic operation of the transmission system and the wholesale markets. In fact, viewed from transmission and wholesale operations, sometimes the term ?virtual power plant? is used to refer to these resources. In the context of energy and ancillary service markets facilitated by the independent system operators (ISOs)/regional transmission organizations (RTOs), the market products DER/DR can offer may include energy, ancillary services, and/or capacity, depending on the ISO/RTO market design and applicable operational standards. In this paper we first explore the main industry drivers of smart grid and the different facets of DER under the smart grid paradigm. We then concentrate on DR and summarize the existing and evolving programs at different ISOs/RTOs and the product markets they can participate in. We conclude by addressing some of the challenges and potential solutions for implementation of DR under smart grid and market paradigms.

846 citations


"Demand side management for resident..." refers background in this paper

  • ...Authors have designed a generic design for DSM which uses wide area network (WAN) to combine residential area and smart area domain....

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  • ...Demand response (DR) is a function of DSM [1]....

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  • ...DSM uses different strategies which motivates the consumers to shift their on-peak load to off-peak hours [2]....

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  • ...In this work they have used GA, enhanced differential evolution (EDE), TLBO and have introduced a hybrid technique called enhanced differential teaching learning algorithm (EDTLA) for DSM programs....

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  • ...To achieve both of these, multiple objective function is introduced for DSM....

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Journal ArticleDOI
TL;DR: In this article, a cost-based formulation to determine the optimal size of the battery energy storage (BES) in the operation management of the micro-grid is presented. And the performance of the approach is evaluated by one grid-connected low voltage MG where the optimal BES is determined professionally.

310 citations

Journal ArticleDOI
TL;DR: A generic architecture for demand side management (DSM) which integrates residential area domain with smart area domain via wide area network and performs more efficiently than BPSO based energy management controller and ACO basedEnergy management controller in terms of electricity bill reduction, peak to average ratio minimization and user comfort level maximization.

244 citations


"Demand side management for resident..." refers methods in this paper

  • ...In [10][13], authors have used different techniques, in [10], TLBO and SLF are used and in [13], GA, BPSO and ACO are used....

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  • ...In [12][13], GA is used with other algorithms, both papers have similar objectives....

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  • ...In [13], a home energy management controller is proposed using three heuristic algorithms: GA, BPSO and ant colony optimization (ACO)....

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  • ...In [10][13], authors have used multiple techniques to decrease PAR and electricity cost, however, waiting time has increased in these works....

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Proceedings ArticleDOI
18 Nov 2011
TL;DR: In this paper, the authors describe various smart grid concepts, architectures, and details of associated technological demonstrations implemented worldwide, and present drivers, visions and roadmaps to develop smart grids worldwide including China and India.
Abstract: This paper describes various smart grid concepts, architectures, and details of associated technological demonstrations implemented worldwide. The survey is based on initiatives taken by EU and IEA (e.g. ETP, EEGI, EERA and IEA DSM) and description of projects conducted in Europe and US (e.g. FENIX, ADDRESS, EU-DEEP, ADINE, GridWise and SEESGEN-ICT). The report presents drivers, visions and roadmaps to develop smart grids worldwide including China and India. The survey encompasses various smart grid concepts, i.e. development of virtual power plant, active demand in consumer networks, DER aggregation business, active distribution network, and ICT applications to develop intelligent future grids. The comparison is carried out on the basis of commercial, technological, and regulatory aspects. In addition, the existing features of smart grid technology and challenges faced to implement it in Finnish environment are addressed. As a matter of fact, the implementation of smart grid is consisting of more than any one technology, therefore, this transition will not be so easy. In the end, a fully realized smart grid will be beneficial to all the stakeholders. Smart grid will be an outcome of an evolutionary development of the existing electricity networks towards an optimized and sustainable energy system.

224 citations


"Demand side management for resident..." refers background in this paper

  • ...DSM uses different strategies which motivates the consumers to shift their on-peak load to off-peak hours [2]....

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Journal ArticleDOI
TL;DR: Simulation results demonstrate that the scheduling strategy can achieve a desired tradeoff between the payments and the discomfort.

214 citations


"Demand side management for resident..." refers background or methods in this paper

  • ...Power scheduling problem is considered as the optimization problem in [6]....

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  • ...In [4][6], authors have used different techniques MOEA and ILP for reducing the electricity cost and user discomfort....

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