Optimized Strategic Planning of Future Norwegian Low-Voltage Networks with a Genetic Algorithm Applying Empirical Electric Vehicle Charging Data

Wruk, Julian; Cibis, Kevin; Resch, Matthias; Sæle, Hanne; Zdrallek, Markus

doi:10.3390/electricity2010006

Cited by 8 publications

(9 citation statements)

References 19 publications

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“…As automated LV network planning based on a GA was developed (Wruk et al, 2021) to yield the optimal reinforcement strategy with a minimum sum of the capital and operational expenditures. Such costs were caused by additional lines, substation upgrades and line voltage regulators.…”

Section: Evolutionary Algorithmsmentioning

confidence: 99%

Optimal Sequential Distribution Planning for Low-Voltage Network With Electric Vehicle Loads

Sangob

Sirisumrannukul

2021

Front. Energy Res.

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There has been a growing presence of electric vehicles in many countries including Thailand, where many forms of incentives have been provided to build integrated infrastructure, and to encourage drivers to switch to electric vehicles (EVs). Because the immediate entry of EVs unavoidably can alter household load profiles, reinforcement on the existing system based on traditional planning may not be sufficient and can introduce over or under capital and operating expenditure over the time horizon. Therefore, if distribution systems are unreadily prepared for such an uptake, three obvious problems can be expected: 1) voltage regulation, 2) overloads of the distribution feeders and the distribution transformers, and 3) high energy loss. In this paper, an activity-based, time-sequential Monte Carlo Simulation algorithm was comprehensively developed for uncontrollable and smart charging, given annually updated information of EV locations and number of EVs, their energy consumption, hourly average vehicle speed, number of daily trips, travel distance per trip, size of EV batteries, time to arrive home and time to leave home. Minimizing the annual sum of investment and operating costs over a planning period could then be sequentially solved by a Particle Swarm Optimization (PSO) algorithm. The results from a practical 122-bus, 24 kV/400 V distribution system with different scenarios of uncontrollable and smart charging show that the sequential optimization embedded with deterministic decision can help improve customer voltage profile, keep feeder and transformer loading within acceptable operating limits and offer significant cost savings from energy loss. As far as a large number of low-voltage networks, and the associated large sum of cost savings are concerned, the proposed planning framework is practical to be applied and expected to be served as a new guideline for future implementation in Thailand.

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Section: Evolutionary Algorithmsmentioning

confidence: 99%

Optimal Sequential Distribution Planning for Low-Voltage Network With Electric Vehicle Loads

Sangob

Sirisumrannukul

2021

Front. Energy Res.

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“…At present, the main research abroad is the dynamic demand VRP, that is, to take into account that the needs of customers change with time and assume that the possibility of change is very large, how to improve the original distribution plan to adapt to this time-changing distribution problem. Due to the continuous research of VRP problems, it has also led to the emergence of various advanced algorithms, and it is precisely because of these advanced algorithms that the solution of VRP problems has become easier and easier [ 4 ].…”

Section: Introductionmentioning

confidence: 99%

“…(3) ere is bad competition between industries, so it is necessary to improve the standard system of related industries. (4) e focus should be on cultivating third-party logistics enterprises. In China, as a large agricultural country, every year will produce a huge number of agricultural products and even consider the problem of export to other countries, but for now, China's protection measures for meat products, fruits, vegetables are quite inadequate.…”

Section: Introductionmentioning

confidence: 99%

The Optimization of Distribution Path of Fresh Cold Chain Logistics Based on Genetic Algorithm

Zhang¹

2022

Computational Intelligence and Neuroscience

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The products of the enterprise are the logistics objects of the enterprise. Therefore, the company’s products are the primary factor affecting logistics costs. The products of different enterprises may be different in terms of the type, nature, volume, quality, and physical and chemical properties of the products, which will have different impacts on the cost of logistics activities such as warehousing, transportation, and material handling of enterprises. More and more enterprises have taken the cost of logistics distribution as one of the important indicators affecting the development of enterprises; especially, cold chain logistics has been rapidly developed and valued in recent years, because the requirements of such products for delivery time, distribution efficiency, and distribution environment are very strict, whether the goods can be distributed in a standard and reasonable environment and whether the delivery vehicle can deliver the goods within the time specified by the customer have greatly affected the safety of frozen and refrigerated food. Therefore, this paper reduces the cost of the distributor through the optimization of the distribution path of cold chain logistics and makes the goods distributed can be delivered to the customer faster and more reasonably by establishing an integrated optimization platform, which is of great significance for how to reduce the cost of enterprises. Therefore, this paper starts from the function with the lowest distribution cost as the goal, comprehensively considers the specific characteristics of cold chain logistics, given the relevant constraints, uses the improved genetic algorithm to iterate on the given scheme, sends the improved new scheme to the simulation software for simulation operation, then sends the results obtained by the operation to the genetic algorithm for the next iteration, and repeats it in turn until the prespecified conditions can be terminated. Therefore, this paper summarizes some problems and development status in cold chain logistics and distribution routes by consulting relevant literature, optimizes the scheme by using VRP model combined with constraints, establishes a distribution system model, and finally verifies and analyzes to obtain a more reasonable and satisfactory solution. The innovation of this paper is that the research on the VRP problem is optimized through an improved genetic algorithm, certain improvements have been made in the coding method and the operation of selection, crossover, variation, etc., and the improved genetic algorithm can greatly reduce the number of program iterations. Then, we use the integrated optimization platform to import the solution into FlexSim for simulation, each simulation of the new solution will be transmitted to MATLAB through the Excel table for the next optimization iteration, and we repeat the above steps until the preset conditions are met after the termination. This would lead to a more realistic and satisfactory solution.

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“…Subsequently, POGs are derived based on the evaluations. The diverse power assumptions offer the advantage that publications [1][2][3][4][5][6][7] have not yet considered high charging capacities in LV grids for public charging points (PuCPs) with a simultaneous consideration of private charging points (PrCPs). This article also analyses the impact of different load management systems for private and/or public CI as well as HPs on grid planning.…”

Section: Literature Review and Noveltymentioning

confidence: 99%

“…An overview and summary of all power value assumptions can be seen in Table 10. 4 [3; 9] (no differentiation for HPs, as SF 7 is almost 1)…”

Section: First Planning and Operation Guidelinementioning

confidence: 99%

Development of Planning and Operation Guidelines for Strategic Grid Planning of Urban Low-Voltage Grids with a New Supply Task

et al. 2021

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In contrast to rural distribution grids, which are mostly “feed-in oriented” in terms of electrical power, urban distribution grids are “load oriented”, as the number of customer connections and density of loads in urban areas is significantly higher than in rural areas. Taking into account the progressive electrification of the transport and heating sector, it is necessary to assess the required grid optimization or expansion measures from a conventional, as well as an innovative point of view. This is necessary in order to be able to contain the enormous investment volumes needed for transforming the energy system and aligning the infrastructures to their future requirements in time. Therefore, this article first explains the methodological approach of allocating scenarios of the development of electric mobility and heat pumps to analyzed grids. The article continues with describing which power values need to be applied and which conventional and innovative planning measures are available for avoiding voltage band violations and equipment overloads within the framework of strategic grid planning. Subsequently, the results of grid planning studies are outlined and evaluated with an assessment model that evaluates capital as well as operational costs. On this basis, planning and operation guidelines for urban low-voltage grids are derived. The main result is that low-voltage grids can accommodate charging infrastructure for electric mobility, as well as heat pumps to a certain degree. In addition, it is concluded that conventional planning measures are not completely avoidable, but can be partially avoided or deferred through dynamic load management.

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Optimized Strategic Planning of Future Norwegian Low-Voltage Networks with a Genetic Algorithm Applying Empirical Electric Vehicle Charging Data

Cited by 8 publications

References 19 publications

Optimal Sequential Distribution Planning for Low-Voltage Network With Electric Vehicle Loads

Optimal Sequential Distribution Planning for Low-Voltage Network With Electric Vehicle Loads

The Optimization of Distribution Path of Fresh Cold Chain Logistics Based on Genetic Algorithm

Development of Planning and Operation Guidelines for Strategic Grid Planning of Urban Low-Voltage Grids with a New Supply Task

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