An Artificial Immune Network for Distributed Demand-Side Management in Smart Grids

Lizondo, Diego F.; Rodríguez, Sebastián; Will, Adrián; Jimenez, Victor Adrian; Gotay, Jorge

doi:10.1016/j.ins.2018.01.039

Cited by 12 publications

(11 citation statements)

References 22 publications

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“…It was used to explain the basic characteristics of adaptive immune response to antigen stimulation. e ICSA has been widely used in solving problems such as combinatorial optimization, intelligent optimization, and production scheduling due to its powerful data search capabilities [42][43][44]. However, the convergence rate of original ICSA is slower, immune probability and cloning probability are relatively fixed, and the degree of change is relatively low when solving complex problems.…”

Section: Solution Methodsmentioning

confidence: 99%

Network Planning Method for Capacitated Metro‐Based Underground Logistics System

Dong

Shen

Ren

et al. 2018

Advances in Civil Engineering

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Underground logistics system (ULS) tends to alleviate traffic congestion, increase city logistics efficiency, mitigate the negative effects of traditional logistics processes, and improve the sustainability of urban areas. However, the relatively high cost and risk of underground construction are serious obstacles to implementing ULS. Integrating ULS into modern metro system (M-ULS) is considered to be feasible and efficient to solve this problem. is paper aims at developing a metro system-based ULS network planning method. First, an evaluation model of underground freight volume was proposed considering service capacity, freight flow, and regional accessibility. Second, a set of mixed integer programming model was developed to solve the problem of optimal nodes' location-allocation (LAP) in the network. en, a hybrid algorithm was designed with a combination of E-TOPSIS, exact algorithm, and heuristic algorithm. Finally, two lines of Nanjing Metro were selected as a case to validate the proposed planning method. e results showed that the new system can significantly reduce the construction costs of ULS and alleviate traffic congestion. Moreover, the potential of metro stations and underground tunnels can be fully exploited to achieve higher logistics benefits.

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Section: Solution Methodsmentioning

confidence: 99%

Network Planning Method for Capacitated Metro‐Based Underground Logistics System

Dong

Shen

Ren

et al. 2018

Advances in Civil Engineering

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“…We converted the objective represented by Equation (14) from a maximization problem to a minimization problem by multiplying it with (−1). This transformation is represented in Equation (19).…”

Section: Multi-objective Formulationmentioning

confidence: 99%

“…The two objectives represented by Equations (2) and (19) are scalarized by pre-multiplying each of them with a weighing factor "w" and "(1 − w)" such as the total weight: w + (1 − w) = The overall single-objective optimization problem is represented by Equation (20):…”

Section: Multi-objective Formulationmentioning

confidence: 99%

“…Adaptive schemes like genetic algorithm-and artificial intelligence-based optimization have Energies 2019, 12, 370 3 of 25 been tried upon to obtain the best possible solution in such adverse mathematical environment. A DSM program based on the artificial immune network has been proposed for the peak load problem [19]. Results show that the adaptive technique enabled the DSM program to keep the peak load within one percent of the desired limit.…”

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confidence: 99%

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Object-Oriented Usability Indices for Multi-Objective Demand Side Management Using Teaching-Learning Based Optimization

Singh

Jha

2019

Energies

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This paper proposes Object-Oriented Usability Indices (OOUI) for multi-objective Demand Side Management (DSM). These indices quantify the achievements of multi-objective DSM in a power network. DSM can be considered as a method adopted by utilities to shed some load during peak load hours. Usually, there are service contracts, and the curtailments or dimming of load are automatically done by service providers based on contract provisions. This paper formulates three indices, namely peak power shaving, renewable energy integration, and an overall usability index. The first two indices indicate the amount of peak load shaving and integration of renewable energy, while the third one combines the impact of both indices and quantifies the overall benefit achieved through DSM. The application of the proposed indices is presented through simulation performed in a grid-tied microgrid environment for a multi-objective DSM formulation. The adopted microgrid structure consists of three units of diesel generators and two renewable energy sources. Simulation has been done using MATLAB software. Teaching-Learning-Based Optimization (TLBO) is adopted as the optimization tool due to its simplicity and independency of algorithm-specific control parameters. Five different cases of renewable energy availability with results validate the efficiency of the proposed approach. The results indicate the usefulness in determining the suitable condition regarding DSM application.Energies 2019, 12, 370 2 of 25 problems is the main area of research for system operators. DSM has appeared as a potential solution for many of these problems.Any scheme that involves alteration in operation of a complex system should be reliable to a certain level. A reliability study of a power system with DSM is presented in [1]. Since a plan for load curtailment can only be prepared when load forecasting is reliable, stochastic optimization and Gray Wolf Optimization (GWO)-based load forecasting and subsequent DSM programs are presented in [2,3]. Load shifting is also an alternative method of performing DSM. In this aspect, a corrective load shifting program is found to be a better option to conventional preventive load shifting [4,5]. In another work, loads are categorized in rigid and flexible types, and DSM is performed keeping in mind the adaptability of the flexible loads [6]. A novel application of DSM to smoothing the peaks of load curve in a small demand area in the Sultanate of Oman is described in [7]. The key contribution was load profile prediction based upon which the DSM program was prepared. The DSM program developed here handles the issue of variable power generation from solar energy-based generation. In a work, the uncertainty due to wind power generation and its impact on the DSM scheme has been discussed [8]. The methodology discusses the fulfillment of two key objectives of DSM, i.e., minimization of emission and cost. Battery storage and diesel-based energy sources are also employed with solar or wind generators to improve the reliability ...

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“…An SG introduces a new vision of energy and information flow to create automated energy control and management network with DSM programs [63,64]. The current research in SG majorly focuses on the DSM, DR, and scheduling techniques to enhance the energy efficiency, stability, and power system capacity [65,66].…”

Section: System Modelmentioning

confidence: 99%

Smart Energy Optimization Using Heuristic Algorithm in Smart Grid with Integration of Solar Energy Sources

et al. 2018

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Smart grid (SG) vision has come to incorporate various communication technologies, which facilitate residential users to adopt different scheduling schemes in order to manage energy usage with reduced carbon emission. In this work, we have proposed a residential load management mechanism with the incorporation of energy resources (RESs) i.e., solar energy. For this purpose, a real-time electricity price (RTP), energy demand, user preferences and renewable energy parameters are taken as an inputs and genetic algorithm (GA) has been used to manage and schedule residential load with the objective of cost, user discomfort, and peak-to-average ratio (PAR) reduction. Initially, RTP is used to reduce the energy consumption cost. However, to minimize the cost along with reducing the peaks, a combined pricing model, i.e., RTP with inclining block rate (IBR) has been used which incorporates user preferences and RES to optimally schedule load demand. User comfort and cost reduction are contradictory objectives, and difficult to maximize, simultaneously. Considering this trade-off, a combined pricing scheme is modelled in such a way that users are given priority to achieve their objective as per their requirements. To validate and analyze the performance of the proposed algorithm, we first propose mathematical models of all utilized loads, and then multi-objective optimization problem has been formulated. Furthermore, analytical results regarding the objective function and the associated constraints have also been provided to validate simulation results. Simulation results demonstrate a significant reduction in the energy cost along with the achievement of both grid stability in terms of reduced peak and high comfort..

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An Artificial Immune Network for Distributed Demand-Side Management in Smart Grids

Cited by 12 publications

References 22 publications

Network Planning Method for Capacitated Metro‐Based Underground Logistics System

Network Planning Method for Capacitated Metro‐Based Underground Logistics System

Object-Oriented Usability Indices for Multi-Objective Demand Side Management Using Teaching-Learning Based Optimization

Smart Energy Optimization Using Heuristic Algorithm in Smart Grid with Integration of Solar Energy Sources

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