Local Distribution System Research Articles

Geospatial Assessment and Mapping of Suitable Sites for a Utility-scale Solar PV Farm

Geospatial and multi-criteria decision-making techniques are applied to process and analyse datasets for determining suitable areas for multiple utilityscale solar photovoltaic farms in the city of Akure, Ondo State, southwestern Nigeria. Data processed include local electric power distribution system data, Shuttle Radar Topographic Mission elevation data, Landsat 8 and solar global horizontal irradiance. Multi-criteria decision-making techniques adopted are the analytical hierarchy process, reclassification, and overlay. These techniques were carried out considering criteria for siting solar photovoltaic farms. Criteria considered in this study are climate, topography, economic, environmental impact operational and technical while sub-criteria are solar global horizontal irradiance, slope, proximity and land cover. The outcome of the study shows that the study area covering a total extent of ~33,200 ha, 15%, 8%, 13% and 64% are highly suitable, suitable, moderately suitable, and unsuitable respectively for siting utility-scale solar photovoltaic farms within the study area. The study reveals the potential of multiple utility-scale solar photovoltaic farms in the study area. However, the proportions of areas suitable for solar photovoltaic farms are quite lower compared to findings from similar studies conducted in northwestern Nigeria. The study recommends solar photovoltaic sources as an alternative energy source in and around the study area.

Robust Survivability-Oriented Scheduling of Separable Mobile Energy Storage and Demand Response for Isolated Distribution Systems

Extreme circumstances in which a local distribution system is electrically isolated from the main power supply may not always be avoidable. Efforts must be made to keep the lights on for such an isolated distribution system (IDS) until reconnection to the main power source. In this paper, we propose a strategy to enhance IDS survivability utilizing the coordination of two flexible approaches, namely, separable energy storage systems (SMESSs), which construct non-wires links for energy transmission between the IDS and the external live power sources, and demand response (DR), which adjusts the internal electrical demand of the IDS to provide effective operating stress alleviation. Considering the uncertainty of renewable energy generation and loads, a two-stage robust optimization (RO) model involving the joint scheduling of these two approaches is constructed. The objective is to minimize the fuel consumption and the decreased and nonserved demand under the worst-case scenario to endow the IDS with extended survivability. Finally, test is conducted and the results demonstrate the effectiveness of the proposed method in enhancing the survivability of IDS.

Locally produced food for restaurants: a theoretical approach for the supply chain network design

PurposeThis paper evaluates the feasibility and benefits of a local food distribution system, which connects farmers and restaurant owners from a logistics perspective. This paper considers a platform to improve operations and investigates various schemes for delivering locally produced food to restaurants using a food hub.Design/methodology/approachTo compare distribution scenarios and derive managerial implications, a simulation model has been developed and executed in Matlab 2019a©. The model evaluates various settings of business connections between farmers and restaurateurs.FindingsResults of computational experiments highlight great potentials of such a system, particularly to reduce travel distances. To obtain these positive externalities, the local system requires specific attention during the design of logistical aspects and needs to be planned following a specific structure.Practical implicationsThe developed simulation model can be used to improve understanding of related short food supply chains by analyzing specific cases where the main actors involved differ in terms of type, number, and location.Originality/valueThe paper analyzes the feasibility and the effects of a new distribution system that can connect supply chain actors directly. The analyses focus on logistics aspects, a topic that is often neglected in sustainable consumption research. Furthermore, the paper does not focus of a single case study but develops a customizable model to be used in various settings.

Soft computing technique with maintenance and controlling for distributed energy using differential evolution based local power distribution system and fuzzy radial basis function neural network

Learning-based modelling methods are now being used to construct a precise prediction method for renewable energy sources. CI (Computational Intelligence) methods are proven to be effective in developing and optimising renewable instruments. Difficulty of this type of energy is determined by its coverage of enormous amounts of data as well as factors that must be properly analyzed. Soft computing approaches are widely recognized as critical instruments for improving performance of spinning electrical devices in both controls as well as design. The progress of gentle computing methods employed in rotating electrical machines is crucial for a wide range of energy conversion devices, including generators, high-performance electric engines and electric cars.This research proposes a novel technique for maintaining and controlling distributed energy systems. Here the maintenance and controlling data have been evaluated by differential evolution based local power distribution system (DE-LPDS) for control system as well as fuzzy radial basis function neural network (FRBFNN) is used in Micro-grid energy management system. The suggested energy management system is modelled to coordinate among many flexible sources by establishing priority resources, direct demand control signals, and power prices. Experimental results show various maintenance and controlling datasets in terms of QoS of 82%, energy efficiency of 95%, power consumption of 59 %, computational time of 34 ms and training accuracy of 95 % by proposed technique.

An Optimal Algorithmic Approach to Efficiently Automate Fault Isolation and Service Restoration on an Arbitrary Distribution Feeder System

Weather-related or other types of faults can negatively impact the continuity of the electricity delivery to the consumers and, thus, lead to poorer reliability scores. 90% of customer outage-minutes are due to events which affect local distribution systems. The radial configuration is simple and has a low cost design; however, when a fault occurs it often causes power outages beyond the location of the fault itself. Therefore, it is beneficial for utilities to automatically isolate the fault and, thus, restore power to as many consumers as possible. The benefits of fault isolation and service restoration include, but are not limited to: enhanced reliability and resiliency, reduced loss of revenue to the utility, and enhanced comfort and satisfaction for the utility’s consumers. This paper provides an algorithm to quickly isolate a fault and automatically restore power to as many nodes of the distribution system as possible by opening and closing switches already placed within the system. The expert model and centralized algorithm that are proposed in this paper guarantee an optimal solution and a short run-time regardless of the size of the distribution system. A mathematical proof of the optimal nature of the solution is provided. In addition, the model is validated in practice, solving two different-sized systems.

NET-ZERO CARBON CHARGING STATIONS MATHEMATICAL MODELING WITH RENEWABLE ENERGY INTEGRATION

This research proposal is aimed towards the development of charging stations which are powered by renewable energy sources. The two sources used to replace traditional fuels are the wind turbines and solar photovoltaic cells. The goal is to perform mathematical analysis for economical and eco-friendly charging station for electric vehicles. With the increase in use of electric vehicles, the use of EV chargers also increases, and enough chargers should be available throughout the globe for promoting this trend. The EV chargers are powered through grids and conventional energy synchronized with wind turbine, solar power and battery packs. The solar and wind energy provide the energy to the EV charger for charging of battery packs. But when they are completely charged or not in use, the excess generation is sent back into the local distribution system. This not only lowers the load on our distribution system but also reduces the losses experienced from GENCOs to DISCOs. The reverse metering is also enabled to earn from the investment. Through this no generation is wasted and we can get credit from the electricity company. The wind and solar power are not constant and vary according to the location and time, so a model is designed to optimize the system size for wind, solar and battery pack. The cost is optimized to keep the annual cost of the charging station to a minimum. A total of ten cities are chosen around the globe having different wind and solar characteristics. A mathematical model is prepared which estimates the source capacity. The simulation results justify that we can achieve zero carbon footprint for charging electric vehicles where sunny weather or winds prevail.

A Novel Technique for Optimal siting and Rating of Shunt Capacitors Placed to the Radial Distribution Systems

The overall efficacy of power distribution is reduced through power loss in distribution systems owing to branch resistance. For providing quality power to customers, power losses must be diminished, and voltages must be enhanced. This paper introduces a novel improvement for the traditional Salps Swarm Algorithm (SSA) called Enhance SSA (ESSA) for selecting Optimal Shunt Capacitor Ratings and their Locations (OSCRL). ESSA is viewed as an enhanced version of SSA with the aim of improving the SSA's poor performance. A multi-objective function was designed in this work for reducing real power loss and Total System Cost (TSC), as well as, improving feeder voltage profile and maximizing Net Savings (NSs) per year under security restrictions. For validating and evaluating the proposed ESSA technique, a practical 33-bus local Iraqi and standard IEEE 69-bus Radial Distribution Systems (RDSs) were used as test systems through utilizing MATLAB. The experimental results attained by the proposed ESSA are compared with other approaches currently available in the literature for addressing OSCRL problem. The experimental results prove the efficacy and supremacy of the ESSA to other literature algorithms with respect to diminishing power loss as well as TSC, reinforce bus voltage profile and increase NSs per year for multiple RDSs.

Improving Educational Processes Using Research of New Knowledge in the Railway Energy Efficiency Management System

Abstract At present, new knowledge about the physical nature and empirical phenomena in the field of distribution, losses, recuperation and consumption of electricity in railway transport is undergoing revolutionary changes. To date, the outputs of various types of traction electricity consumption on electric traction units (HEKV) and in the railway distribution network of the EU railway infrastructure manager (LDSŽ - Local Distribution System of Railways) have not been theoretically or practically analysed in available publications or on the scientific market. There are no empirical or experimental calculations and mathematical models at the level of mathematical approximation and intelligent prediction, i.e. at the level of preparation of technical specifications and documentation for expert software and effective ICT solutions to this problem. Research into new phenomena in the field of railway energy and research in the field of railway energy and research into expert systems and machine learning. The article describes the basic characteristics of determining the prediction of energy efficiency of traction electricity. Brings the results of the project “Research of new knowledge in the field of intelligent energy efficiency management system in rail transport using a modular neural network”, which aims to innovate procedures in solving the problem and didactic transformation of scientific content to simplify them into a subject understandable to students as interpretive and application concept of didactics of professional subjects. Transform the curriculum into students’ knowledge, attitudes and habits using teaching methods, organizational forms and material resources.

Environmental Injustices of Leaks from Urban Natural Gas Distribution Systems: Patterns among and within 13 U.S. Metro Areas.

Natural gas leaks in local distribution systems can develop as underground pipeline infrastructure degrades over time. These leaks lead to safety, economic, and climate change burdens on society. We develop an environmental justice analysis of natural gas leaks discovered using advanced leak detection in 13 U.S. metropolitan areas. We use Bayesian spatial regression models to study the relationship between the density of leak indications and sociodemographic indicators in census tracts. Across all metro areas combined, we found that leak densities increase with increasing percent people of color and with decreasing median household income. These patterns of infrastructure injustice also existed within most metro areas, even after accounting for housing age and the spatial structure of the data. Considering the injustices described here, we identify actions available to utilities, regulators, and advocacy groups that can be taken to improve the equity of local natural gas distribution systems.

Analysing utility-based direct load control programmes for heat pumps and electric vehicles considering customer segmentation

Utility controlled heat pumps and electric vehicles via Direct Load Control (DLC) programmes could potentially be a solution for tackling challenges in the distribution networks by balancing intermittent renewable electricity sources. However, in many countries, DLC programmes do not have satisfactory enrolment rates. This paper investigates acceptance and preferences of DLC programmes for heat pumps and electric vehicles (EV) offered by a local Distribution System Operator (DSO), using a discrete choice experiment on a sample of 556 respondents residing in Switzerland. We first found that the acceptance ranged between 33% and 71% in different socio-economic groups. Secondly, multinomial logit results showed that financial incentives were the most preferred attribute for heat pumps, whereas it was the overriding option for the EV DLC programme. Finally, we explored the source of heterogeneity in preferences among different socio-economic groups with a latent class model. Preferences are found to differ between three classes, different gender and employment groups tend to be sensitive to different attributes of the DLC programmes. We draw attention to attributes of the utility based DLC programmes and provide policy recommendations to successfully address the diverse household preferences when deploying DLC programmes.

Stakeholder objectives for joining an energy community: Flemish case studies

Energy communities (ECs) are considered an important element of the current energy transition. Most studies have focused on how to specifically engage citizens in such communities. In this paper, the emphasis is on the objectives of other stakeholders. Only by taking all motivations and interests into account can a successful project be established.In our study, relevant stakeholders, their objectives for joining an EC and the importance of each of these objectives were determined in a participatory manner through four Flemish pilot cases. The results provide an overview of general and context-specific elements that need to be taken into account when designing an EC as well as when setting up policy initiatives to stimulate large-scale EC roll-out. For potential members, financial incentives are the main drivers of participation but often not the decisive objectives. Their decision to join is influenced by a variable combination of social, economic, technical and environmental motivations. Local governments mainly want an EC to bring social and environmental advantages, and the local distribution system operator (DSO) only supports ECs when they can bring added value to their main grid and society as a whole and can help avoid major grid investments.

Crosstalk in Elliptical Sensor Arrays for Current Measurement

Contactless current sensors that use arrays of magnetic field sensors are a good alternative to core-based current sensors because the omission of the magnetic core offers many advantages. Particularly, circular sensor arrays have proven to feature good robustness against various error sources. As rectangular bus bars are frequently used for local high-current power distribution systems, elliptic arrays would require less space than circular arrays. Up until now, no publication on magnetic interference errors of elliptic sensor arrays has been presented. This article examines the crosstalk error for different sensor distribution methods, aspect ratios, numbers of sensors, and offset angles with calculations and measurements. Therefore, an interference conductor is positioned at different angles and distances relative to the elliptic arrays. We show that the crosstalk error can be reduced with our elliptic designs in comparison to a circular design with an equal number of sensors and an equal length of the semimajor axis. The projection distribution typically offers a five times smaller crosstalk error compared to the uniform curve segment length distribution. To support the design of elliptical arrays, instructions for the optimization against interference errors for elliptic sensor arrays are given in this article. Thus, an optimal offset angle for the reduction of the crosstalk error is presented.

A simple control strategy and dynamic energy management for the operation of combined grid-connected and standalone solar photovoltaic applications

There is an increased focus on energy savings in low-voltage DC (LVDC) loads for home appliances. The use of LVDC for the local distribution system enables easier integration with renewable sources. This work presents the control and management of power flow to DC loads in grid-tied photovoltaic (GPV) systems. This system provides bi-directional flow of power from the DC load to the AC grid, using a pulse width modulation (PWM) technique, employing a voltage source inverter between the DC nano grid and the AC main grid. The bidirectional converter controls the active power transferred in both directions while operating at unity power factor (UPF). The modified three-level hysteresis current controller and the voltage controller are designed as the inner loop and the outer loop, respectively, to control the bi-directional power flow. The corresponding grid voltages and currents are used to generate the reference currents. The proposed system has been validated through MATLAB/Simulink simulations and experimentation on a prototype system developed in the laboratory controlled by the dSPACE 1103 real-time digital controller board. The results show that a regulated DC voltage is obtained for dynamic changes of source and load like in a real-time environment. The control strategy with its validation shows the efficacy of the proposed system.

Business structure of electricity distribution system operator and effect on solar photovoltaic uptake: An empirical case study for Switzerland

Distribution System Operators are responsible for overseeing the connection of distributed energy sources, such as solar photovoltaic, to the low voltage electricity grid. While solar PV could contribute significantly to the decarbonization of the electricity supply, the technology's proliferation is not necessarily aligned with the business objectives of the Distribution System Operators. We conduct a statistical analysis to test whether solar photovoltaic in Switzerland is affected by the business model of the local Distribution System Operator. Our results indicate that the technology uptake patterns differ according to the business model despite a non-discriminatory connection policy. We conclude that Swiss policymakers provide additional support for solar photovoltaic in areas served by limited companies, due to their energy-generating potential, as well as those served by local municipalities, to achieve more consistent adoption rates. The findings of our work support future organizational studies of individual Distribution System Operators and comparisons to other jurisdictions with multiple Distribution System Operators of varying business models.

SPSO Based Optimal Integration of DGs in Local Distribution Systems under Extreme Load Growth for Smart Cities

Renewable energy-based distributed generators (DGs) are gaining more penetration in modern grids to meet the growing demand for electrical energy. The anticipated techno-economic benefits of these eco-friendly resources require their judicious and properly sized allocation in distribution networks (DNs). The preeminent objective of this research is to determine the sizing and optimal placing of DGs in the condensed DN of a smart city. The placing and sizing problem is modeled as an optimization problem to reduce the distribution loss without violating the technical constraints. The formulated model is solved for a radial distribution system with a non-uniformly distributed load utilizing the selective particle swarm optimization (SPSO) algorithm. The intended technique decreases the power loss and perfects the voltage profile at the system’s nodes. MATLAB is used for the simulation, and the obtained results are also validated by the Electrical Transient Analysis Program (ETAP). Results show that placing optimally sized DGs at optimal system nodes offers a considerable decline in power loss with an improved voltage profile at the network’s nodes. Distribution system operators can utilize the proposed technique to realize the reliable operation of overloaded urban networks.

Distributed Energy Resources Roadmap: How the State of Western Australia Is Leading in Integration

The transition to distributed energy resources (DERs) is happening rapidly in Western Australia, presenting serious and pressing risks to the safe and efficient operation of its main electricity grid, the South West Interconnected System (SWIS). DERs are smaller-scale devices that can either use, generate, or store electricity and form a part of the local distribution system serving homes and businesses.

Fuzzy logic power management for a PV/Wind microgrid with backup and storage systems

<span>This work introduces a power management scheme based on the fuzzy logic controller (FLC) to manage the power flows in a small and local distributed generation system. The stand-alone microgrid (MG) includes wind and PV generators as main power sources. The backup system includes a battery storage system (BSS) and a diesel generator (DG) combined with a supercapacitor (SC). The different energy sources are interconnected through the DC bus. The MG is modeled using MATLAB/Simulink Sim_Power System™. The SC is used to compensate for the shortage of power during the start-up of the DG and to compensate for the limits on the charging/discharging current of the BSS. The power balance of the system is the chief objective of the proposed management scheme. Some performance indexes are evaluated: the frequency-deviation, the stability of the DC bus voltage, and the AC voltage total harmonic distortion. The performance of the planned scheme is assessed by two 24-hours simulation sets. Simulation results confirm the effectiveness of FLC-based management. Moreover, the effectiveness of the FLC approach is compared with the deterministic approach. FLC approach has saved 18.7% from the daily load over the deterministic approach. The study shows that the quality of the power signal in the case of FLC is better than the deterministic approach.</span>

Optimal reconfiguration of balanced and unbalanced distribution systems using firefly algorithm

Abstract With increasing demand in energy, efficiency, reliability, and resiliency in the power systems, integration of distributed generation (DG) or renewable energy sources in the local distribution system is trending nowadays. The power system optimization in distribution networks plays a prominent role in planning reliable supply to the users. This paper presents a meta-heuristic approach to improve the system performance by considering: a) voltage profile improvement, b) minimize the active power loss, and c) overall operation cost as the objective functions of the distribution system reconfiguration (DSR). Modified Newton Raphson (MNR) is used for a load flow analysis of the 33 bus balanced test system and 25 bus unbalanced distribution system. To study the performance of the system objective functions, three different scenarios are considered: i) with DG integrated, ii) with DSR performed, and iii) DG placed along with DSR. These scenarios are compared with the base system configuration parameters along with convergence comparison of harmony search algorithm (HAS) and particle swarm optimization (PSO) with firefly algorithm (FFA) of the distribution systems.

Bullwhip Effect – Logistic Stability Examination in Serial and Arborescent Topologies with Demand Uncertainty and Delay

The paper analyzes the formation of the bullwhip effect in logistic systems as a significant threat to preserving stability in the face of non-negligible goods transport delay and uncertainty of demand and stock records. The popular order-up-to policy is selected as the method governing the goods flow. A dynamic model of entity interaction is constructed and examined, first, analytically, then in numerical tests for various scenarios of practical significance, e.g., a supply chain with external and local demand signals or real-world European goods distribution system. It has been found that the order-up-to policy does not trigger the bullwhip effect despite the delays in the goods delivery in the nominal operating conditions in supply chains. However, in networked environments, even the basic configuration triggers the bullwhip effect.

Individual and Collective Strategies to Limit the Impacts of Large Power Outages of Long Duration

As modern society becomes ever more dependent on the availability of electric power, the costs that could arise from individual and social vulnerability to large outages of long duration (LLD-outages) increases. During such an outage, even a small amount of power would be very valuable. This article compares individual and collective strategies for providing limited amounts of electric power to residential customers in a hypothetical New England community during a large electric power outage of long duration. We develop estimates of the emergency load required for survival and assess the cost of strategies to address outages that last 5, 10, and 20 days in either winter or summer. We find that the cost of collective solutions could be as much as 10 to 40 times less than individual solutions (less than $2 per month per home). However, collective solutions would require community-wide coordination, and if local distribution system lines are destroyed, only individual back-up systems could provide contingency power until those lines are repaired. Costs might be reduced if more robust distributed generation were employed that could be operated continuously with the ability to sell power back to the grid. Our cost-effectiveness analysis only assesses what could be done, developing estimates of preparedness cost. A decision about what should be done would require additional input from a range of stakeholders as well as some form of analytical deliberative process.