scholarly journals Dynamic Tariff for Day-Ahead Congestion Management in Agent-Based LV Distribution Networks

Energies ◽  
2020 ◽  
Vol 13 (2) ◽  
pp. 318
Author(s):  
Niyam Haque ◽  
Anuradha Tomar ◽  
Phuong Nguyen ◽  
Guus Pemen
Keyword(s):  
Demand Response ◽  
Low Voltage ◽  
Dynamic Network ◽  
Distribution Networks ◽  
Congestion Management ◽  
Renewable Energy Resources ◽  
Monthly Basis ◽  
Agent Based ◽  
Local Decision ◽  
Residential Distribution

Capacity challenges are becoming more frequent phenomena in residential distribution networks with new forms of loads, distributed renewable energy resources (RES) and price-responsive applications. Different types of demand response programs have been introduced to tackle these challenges through iterative changes in price and/or contractual participations based on incentives. In this research, a dynamic network tariff-based demand response program is proposed to address congestion problems in low-voltage (LV) networks. The formulation takes advantage of the scalable architecture of the agent-based systems that allows local decision making with limited communication. Energy consumption schedules are developed on a day-ahead basis depending on the expected cost of overloading for a number of probable scenarios. The performance of the proposed approach has been tested through simulations in the unbalanced IEEE European LV test feeder. Simulation results reveal up to 82% reduction in congestion on a monthly basis, while maintaining the quality of supply in the network.

Demand response in low voltage distribution networks with high PV penetration

2017 ◽  
Author(s):  
N. Karthikeyan ◽  
Basanta Raj Pokhrel ◽  
Jayakrishnan R. Pillai ◽  
Birgitte Bak-Jensen ◽  
Kenn H. B. Frederiksen
Keyword(s):  
Demand Response ◽  
Low Voltage ◽  
Distribution Networks ◽  
Voltage Distribution ◽  
Pv Penetration

scholarly journals Review of Voltage and Reactive Power Control Algorithms in Electrical Distribution Networks

Energies ◽  
2019 ◽  
Vol 13 (1) ◽  
pp. 58 ◽  
Author(s):  
Daiva Stanelyte ◽  
Virginijus Radziukynas
Keyword(s):  
Smart Grids ◽  
Reactive Power ◽  
Low Voltage ◽  
Distribution Networks ◽  
Power Grids ◽  
Renewable Energy Resources ◽  
Distribution Grid ◽  
Harmonic Compensation ◽  
Distributed Power Generation ◽  
Control Devices

The traditional unidirectional, passive distribution power grids are rapidly developing into bidirectional, interactive, multi-coordinated smart grids that cover distributed power generation along with advanced information communications and electronic power technologies. To better integrate the use of renewable energy resources into the grid, to improve the voltage stability of distribution grids, to improve the grid protection and to reduce harmonics, one needs to select and control devices with adjustable reactive power (capacitor batteries, transformers, and reactors) and provide certain solutions so that the photovoltaic (PV) converters maintain due to voltage. Conventional compensation methods are no longer appropriate, thus developing measures are necessary that would ensure local reactive and harmonic compensation in case an energy quality problem happens in the low voltage distribution grid. Compared to the centralized methods, artificial intelligence (heuristic) methods are able to distribute computing and communication tasks among control devices.

scholarly journals Design and application of a distributed generation hosting capacity algorithm

2021 ◽  
Vol 32 (3) ◽  
pp. 1-13
Author(s):  
M. A. Sam ◽  
D. T. O Oyedokun ◽  
K.O Akpeji
Keyword(s):  
Distributed Generation ◽  
Distribution Network ◽  
Distribution Networks ◽  
Probabilistic Methods ◽  
Energy Resources ◽  
Practical Implementation ◽  
Low Carbon ◽  
Renewable Energy Resources ◽  
Residential Distribution

Distribution networks in Southern Africa and elsewhere are witnessing an unprecedented growth of consumer-side distributed generation (DG) courtesy of governmental interventions to maximise the utilisation of renewable energy resources through low-carbon grid-edge technologies. To deal with the increasing adoption of consumer-side DG, distribution network operators need to conduct technical studies to foster an understanding of the benefits and impacts of DG and the hosting capacity (HC) of existing distribution networks. This will aid the implementation of measures to manage grid exports. Using a distribution network in Namibia as a case study, this paper presents an algorithm for assessing the HC of consumer-side DG in existing distribution networks that are situated in areas anticipating high and uniform uptake of DG. The algorithm is a hybrid of deterministic and probabilistic methods. The uniqueness of the algorithm is the concept of calculating monthly HC. The algorithm was tested on a real existing residential distribution network and the results confirmed that HC varies monthly. However, the practical implementation of monthly HC requires upgrades to existing inverter technology, which currently contains a single export limit functionality. This opens the possibility to drive innovation in the inverter technology to develop a date-based multiple export limit functionality.

scholarly journals Design, Valuation and Comparison of Demand Response Strategies for Congestion Management

Energies ◽  
2020 ◽  
Vol 13 (22) ◽  
pp. 6085
Author(s):  
Osaru Agbonaye ◽  
Patrick Keatley ◽  
Ye Huang ◽  
Motasem Bani Mustafa ◽  
Neil Hewitt
Keyword(s):  
Northern Ireland ◽  
Demand Response ◽  
Distribution Networks ◽  
Congestion Management ◽  
Response Strategy ◽  
Response Strategies ◽  
Grouping Strategy ◽  
Smart Control ◽  
Pricing Schemes

Decarbonisation of heat and transport will cause congestion issues in distribution networks. To avoid expensive network investments, demand flexibility is necessary to move loads from peak to off-peak periods. We provide a method and metric for assessing and selecting the optimal demand response strategy for a given network congestion scenario and applied it to a case study network in Coleraine, Northern Ireland. We proposed a Price Approximation/Mean Grouping strategy to deal with the issue of congestions occurring at the lowest-price period in real-time pricing schemes. The Mean Grouping strategy increased the average lowest-price hours from 1.32 to 3.76. We show that a three-cluster tariff is effective in solving medium congestion issues in Northern Ireland and could save consumers an average of £117/year on their heating bill. However, for networks with low headroom suffering from serious congestion issues, a smart control strategy is needed.

scholarly journals Two-Stage Optimal Microgrid Operation with a Risk-Based Hybrid Demand Response Program Considering Uncertainty

Energies ◽  
2020 ◽  
Vol 13 (22) ◽  
pp. 6052
Author(s):  
Ho-Sung Ryu ◽  
Mun-Kyeom Kim
Keyword(s):  
Demand Response ◽  
Low Voltage ◽  
Risk Index ◽  
Optimal Operation ◽  
Energy Resources ◽  
Optimization Approach ◽  
Renewable Energy Resources ◽  
Two Stage ◽  
Operation Costs ◽  
Demand Response Program

Owing to the increasing utilization of renewable energy resources, distributed energy resources (DERs) become inevitably uncertain, and microgrid operators have difficulty in operating the power systems because of this uncertainty. In this study, we propose a two-stage optimization approach with a hybrid demand response program (DRP) considering a risk index for microgrids (MGs) under uncertainty. The risk-based hybrid DRP is presented to reduce both operational costs and uncertainty effect using demand response elasticity. The problem is formulated as a two-stage optimization that considers not only the expected operation costs but also risk expense of uncertainty. To address the optimization problem, an improved multi-layer artificial bee colony (IML-ABC) is incorporated into the MG operation. The effectiveness of the proposed approach is demonstrated through a numerical analysis based on a typical low-voltage grid-connected MG. As a result, the proposed approach can reduce the operation costs which are taken into account uncertainty in MG. Therefore, the two-stage optimal operation considering uncertainty has been sufficiently helpful for microgrid operators (MGOs) to make risk-based decisions.

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