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

Abstract

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 ...

Distributed Energy Resources Management 2018

“…This paper provides a summary of the Special Issue of Energies covering the published articles [1][2][3][4][5][6][7][8][9][10][11][12][13], which address several topics related to distributed energy resources management. Table 1 identifies the most relevant topics in each publication of the 2018 Edition.…”

“…With focus on microgrids, demand side management was managed using a multi-objective approach proposed by Singh and Jha in [7]. Usability indices (peak shaving for example) were determined in order to analyze the contribution of demand side management to the optimal operation of the microgrid.…”

“…The Special Issue "Distributed Energy Resources Management 2018" includes 13 papers [1][2][3][4][5][6][7][8][9][10][11][12][13], and is a continuation of the Special Issue "Distributed Energy Resources Management" published in https://www.mdpi.com/journal/energies/special_issues/distributed_energy_resources_ management2018. The success of the previous Special Issue, for which the summary is published in [14], shows the unquestionable relevance of distributed energy resources in the operation of power and energy systems at both the distribution level, and at the wide power system level.…”

Economic Evaluation, Use of Renewable Energy, and Sustainable Urban Development Mamminasata Metropolitan, Indonesia

“…The world population is projected to increase by 1.3 billion by 2030, to a total of 8.3 billion; at the same time, total world GDP, compared to 2011, is predicted to double. The integration of renewable energy sources with conventional networks while meeting the energy needs for the various development activities engaged in currently is a challenge [5]. World energy consumption grows by an average of 1.6% per year and will increase by 36% by 2030.…”

Optimal energy management of microgrid using advanced multi-objective particle swarm optimization

“…Modern meta-heuristic methods are able to guarantee an optimal solution because they ensure to provide an optimal solution to complex nonlinear problems that other methods cannot solve in a reasonable time frame or at all. These EC 37,6 modern meta-heuristics include evolutionary algorithms such as GA, swarm-based intelligence such as PSO, DE (Singh and Jha, 2019), ALO algorithm (Nehrir and Wang, 2009) and others. Ramli et al (2018) proposed a new approach for optimally sizing of PV/wind/diesel hybrid microgrid system using multi-objective SADE algorithm.…”