Moth Search Optimization for Optimal DERs Integration in Conjunction to OLTC Tap Operations in Distribution Systems

In this paper, a newly developed moth search optimization (MSO) technique is introduced to solve the complex distributed energy resources (DER) integration problems of distribution systems. In order to overcome some of the limitations observed in the standard variant of MSO, minor corrections are also suggested. On the other hand, a new optimization problem is formulated for optimal deployment of dispatchable distributed generations and shunt capacitors while simultaneously optimizing the tap positions of on-load tap-changing transformers, already deployed in grid substations. The objective of this work is to minimize the cost of annual energy loss and node voltage deviations over multiple load levels. The proposed model is implemented and solved for two benchmark test distribution networks of 33 and 118 buses. The suggested corrections are also validated by comparing the performance of the proposed approach with standard MSO and other available optimization methods. The simulation results show that the developed model optimally utilizes the existing distribution system resources and generates higher deployment benefits at lesser DER penetration as compared to the planning model which ignores these resources

Complexity Dynamics of Gumowski-Mira Map

In the context of nonlinear dynamics, interesting dynamic behavior of Gumowski-Mira Map has been noted under various feasible circumstances. Evolutionary phenomena are discussed through the study of bifurcation analysis leading to period-doubling and chaos. The appearance of chaos in the method is identified by plotting Lyapunov characteristic exponents (LCE) and Topological Entropy within certain parameter range. Dynamic Lyapunov Indicator (DLI) has been procured for further identification of regular and chaotic motions of the Gumowski-Mira Map. The numerical results through the indicator DLI clearly demonstrate the behavior of our map. The correlation dimension has been calculated numerically for the dimension of the chaotic attractor

Modified African Buffalo Optimization for Strategic Integration of Battery Energy Storage in Distribution Networks

This article presents a two-layer optimization scheme for simultaneous optimal allocation of wind turbines (WTs) and battery energy storage systems (BESSs) in power distribution networks. The prime objective of this formulation is to maximize the renewable hosting capacity of the system. For outer-layer, a new objective function is developed by combining multiple objectives such as annual energy loss in feeders, back-feed power, BESSs conversion losses, node voltage deviation, and demand fluctuations caused by renewables subject to various system security and reliability constraints. Furthermore, a modified variant of African buffalo optimization (ABO) introduced to overcome some of the limitations observed in its standard variant. The proposed modifications are first validated and then introduced for simultaneous optimal integration of multiple distributed energy resources in distribution systems. The proposed modified ABO is employed to determine the optimization variables of outer-layer. Whereas, a heuristic is proposed to solve the inner-layer optimization problem aiming to determine the optimal dispatch of BESSs suggested by outer-layer optimization. By considering the high investment and operating cost of BESSs, minimum energy storage capacity has been ensured during the planning stage. To present the efficacy of developed model, it is implemented on a 33-bus, benchmark test distribution system for various test cases. The comparative simulation results show that the proposed optimization model and modified ABO is very promising to improve the performance of active distribution systems

Transaction-Oriented Dynamic Power Flow Tracing for Distribution Networks – Definition and Implementation in GIS Environment

There is a growing interest from owners of distributed energy resources (DERs) to actively participate in the energy market through peer-to-peer (P2P) energy trading. Many strategies have been proposed to base P2P energy trading on. However, in those schemes neither the costs of assets usage nor the losses incurred are so far taken into account. This article presents a transaction-oriented dynamic power flow tracing (PFT) platform for distribution networks (DNs) implemented in a geographic information system (GIS) environment. It introduces a new transaction model that quantifies the use of the DN, apportions the losses and unlocks a flexible use of the surplus generation enabling that prosumers can adopt simultaneously different mechanisms for participation in energy trading, maximizing renewable energy usage. The platform is also helpful for future distribution system operators (DSOs) to overcome the status invisibility of low voltage (LV) DNs, determine who makes use of the assets, debit the losses on them and explore the effects from new connections. A case study is conducted over the IEEE European LV Test Feeder. The tool provides a clear, intuitive, temporal and spatial assessment of the network operation and the resulting power transactions, including losses share and efficiency of DERs

Modified Taguchi-Based Approach for Optimal Distributed Generation Mix in Distribution Networks

In this paper, a new two-stage optimization framework is proposed to determine the optimal-mix integration of dispatchable Distributed Generation (DG), in power distribution networks, in order to maximize various techno-economic and social benefits simultaneously. The proposed framework incorporates some of the newly introduced regulatory policies to facilitate low carbon networks. A modified Taguchi Method (TM), in combination with a node priority list, is proposed to solve the problem in a minimum number of experiments. Nevertheless, the standard TM is computationally fast but has some inherent tendencies of local trapping and usually converges to suboptimal solutions. Therefore, two modifications are suggested. A roulette wheel selection criterion is applied on priority list to select the most promising DG nodes and then modified TM determines the optimal DG sizes at these nodes. The proposed approach is implemented on two standard test distribution systems of 33 and 118 buses. To validate the suggested improvements, various algorithm performance parameters such as convergence characteristic, best and worst fitness values, and standard deviation are compared with existing variants of TM, and improved genetic algorithm. The comparison shows that the suggested corrections significantly improve the robustness and global searching ability of TM, even compared to meta-heuristic methods

Optimal Planning and Operational Management of Open-Market Community Microgrids

In this article, a new business model comprising multiple stakeholders is proposed to develop a frame for future flexible retail energy market in community microgrids. The microgrid comprises multiple and different distributed energy resources (DERs) such as renewable generation units, battery energy storage systems (BESSs), and micro diesel engines (MDE), to minimize daily operational costs of the system. To solve the defined complex optimization model, some operational strategies are proposed and then genetic algorithm is adopted to determine the hourly optimal power dispatch. The case study shows that the proposed model minimizes the daily operating cost of the community system effectively

Multi-criteria decision making monarch butterfly optimization for optimal distributed energy resources mix in distribution networks

The optimal integration of distributed energy resources (DERs) is a multiobjective and complex combinatorial optimization problem that conventional optimization methods cannot solve efficiently. This paper reviews the existing DER integration models, optimization and multi-criteria decision-making approaches. Further to that, a recently developed monarch butterfly optimization method is introduced to solve the problem of DER mix in distribution systems. A new multiobjective DER integration problem is formulated to find the optimal sites, sizes and mix (dispatchable and non-dispatchable) for DERs considering multiple key performance objectives. Besides, a hybrid method that combines the monarch butterfly optimization and the technique for order of preference by similarity to ideal solution (TOPSIS) is proposed to solve the formulated large-scale multi-criteria decision-making problem. Whilst the meta-heuristic optimization method generates non-dominated solutions (creating Pareto-front), the TOPSIS approach selects that with the most promising outcome from a large number of alternatives. The effectiveness of this approach is verified by solving single and multiobjective dispatchable DER integration problems over the benchmark 33-bus distribution system and the performance is compared with the existing optimization methods. The proposed model of DER mix and the optimization technique significantly improve the system performance in terms of average annual energy loss reduction by 78.36%, mean node voltage deviation improvement by 9.59% and average branches loadability limits enhancement by 50%, and minimized the power fluctuation induced by 48.39% renewable penetration. The proposed optimization techniques outperform the existing methods with promising exploration and exploitation abilities to solve engineering optimization problems

Mobile Power Infrastructure Planning and Operational Management for Smart City Applications

The paper presents new strategies and algorithms for future mobile power infrastructure planning and operational management in smart cities. The efforts have been made to develop a resilient Electric Vehicle (EV) infrastructure for smart city applications. The goal of this work is to maximize the profit of utility and EV owners participating in real-time smart city energy market subjected to numerous techno-economic constraints of the EVs and power distribution system. For effective real-time applications, the knowledge of artificial intelligence and internet of things (IoT) are used in the proposed model. In order to validate the proposed model for smart city applications, IEEE 33-bus radial distribution network is adopted as a small city power network. The simulation results of proposed model are found to be encouraging when it is compared with the case in which conventional strategies are used

Techno-Economic Feasibility Analysis of Grid-Connected Microgrid Design by Using a Modified Multi-Strategy Fusion Artificial Bee Colony Algorithm

The present work investigates the techno-economic solution that can address the problem of rural electrification. To maintain a continuous power supply to this village area, a grid-connected microgrid system was designed that consists of solar photovoltaic (SPV) and battery energy storage systems (BESS). The recently introduced multi-strategy fusion artificial bee colony (MFABC) algorithm was hybridized with the simulated annealing approach and is referred to as the MFABC+ algorithm. This was employed to determine the optimal sizing of different components comprising the integrated system as well as to maximize the techno-economic objectives. For validation, the simulation results obtained by the MFABC+ algorithm are compared with the results obtained using HOMER software, the particle swarm optimization algorithms and the original MFABC algorithm. It was revealed that the MFABC+ algorithm has a better convergence rate and the potential ability to provide compromising results in comparison to these existing optimization tools. It was also discovered through the comprehensive evaluation that the proposed system has the potential capability to meet the electricity demand of the village for 24 × 7 at the lowest levelized cost of electricity

Reliability and Network Performance Enhancement by Reconfiguring Underground Distribution Systems

Contemporary distributions are now going to underground their overhead distribution lines due to techno-social reasons. Reliability and loss reduction are the two prime objectives for distribution system operation. Since failure rates of ungrounded cables are the function of Joules heating besides their physical lengths, the reliability evaluation of undergrounded distribution systems needs to be reviewed. This paper suggested a suitable modification in existing reliability indices in order to make them more appropriate for underground distribution systems. A multi-objective network reconfiguration problem is formulated to enhance the reliability and performance of distribution systems while duly addressing the variability and uncertainty in load demand and power generation from renewables. The application results on a standard test bench shift the paradigm of the well-known conflicting nature of reliability and network performance indices defined for overhead distribution systems