scholarly journals A Novel Algorithm with Multiple Consumer Demand Response Priorities in Residential Unbalanced LV Electricity Distribution Networks

Mathematics ◽  
2020 ◽  
Vol 8 (8) ◽  
pp. 1220
Author(s):  
Ovidiu Ivanov ◽  
Samiran Chattopadhyay ◽  
Soumya Banerjee ◽  
Bogdan-Constantin Neagu ◽  
Gheorghe Grigoras ◽  
...  
Keyword(s):  
Demand Response ◽  
Distribution System ◽  
Smart Grids ◽  
Low Voltage ◽  
Distribution Networks ◽  
Load Flow ◽  
Electricity Distribution ◽  
Energy Management Systems ◽  
Home Energy Management ◽  
Novel Algorithm

Demand Side Management (DSM) is becoming necessary in residential electricity distribution networks where local electricity trading is implemented. Amongst the DSM tools, Demand Response (DR) is used to engage the consumers in the market by voluntary disconnection of high consumption receptors at peak demand hours. As a part of the transition to Smart Grids, there is a high interest in DR applications for residential consumers connected in intelligent grids which allow remote controlling of receptors by electricity distribution system operators and Home Energy Management Systems (HEMS) at consumer homes. This paper proposes a novel algorithm for multi-objective DR optimization in low voltage distribution networks with unbalanced loads, that takes into account individual consumer comfort settings and several technical objectives for the network operator. Phase load balancing, two approaches for minimum comfort disturbance of consumers and two alternatives for network loss reduction are proposed as objectives for DR. An original and faster method of replacing load flow calculations in the evaluation of the feasible solutions is proposed. A case study demonstrates the capabilities of the algorithm.

scholarly journals Predictive Voltage Control: Empowering Domestic Customers With a Key Role in the Active Management of LV Networks

2020 ◽  
Vol 10 (7) ◽  
pp. 2635
Author(s):  
Micael Simões ◽  
André G. Madureira
Keyword(s):  
Distribution System ◽  
Smart Grids ◽  
Low Voltage ◽  
Voltage Control ◽  
Distribution Networks ◽  
Active Management ◽  
Storage Devices ◽  
Home Energy Management ◽  
System Operator ◽  
Home Energy Management System

In order to avoid voltage problems derived from the connection of large amounts of renewable-based generation to the electrical distribution system, new advanced tools need to be developed that are able to exploit the presence of Distributed Energy Resources (DER). This paper describes the approach proposed for a predictive voltage control algorithm to be used in Low Voltage (LV) distribution networks in order to make use of available flexibilities from domestic consumers via their Home Energy Management System (HEMS) and more traditional resources from the Distribution System Operator (DSO), such as transformers with On-Load Tap Changer (OLTC) and storage devices. The proposed algorithm—the Low Voltage Control (LVC)—is detailed in this paper. The algorithm was tested through simulation using a real Portuguese LV network and real consumption and generation data, in order to evaluate its performance in preparation for a field-trial validation in a Portuguese smart grids pilot.

scholarly journals Blockchain-Enabled Transactive Home Energy Management Systems in Distribution Networks

2020 ◽  
Author(s):  
Lawryn Edmonds ◽  
Bo Liu ◽  
Hongyu Wu ◽  
Hang Zhang ◽  
Don Gruenbacher ◽  
...  
Keyword(s):  
Energy Management ◽  
Distribution System ◽  
Distribution Networks ◽  
Electric Utility ◽  
Management Systems ◽  
Energy Management Systems ◽  
Customer Information ◽  
Viable Solution ◽  
Home Energy Management ◽  
System Operator

As home energy management systems (HEMSs) are implemented in homes as ways of reducing customer costs and providing demand response (DR) to the electric utility, homeowner’s privacy can be compromised. As part of the HEMS framework, homeowners are required to send load forecasts to the distribution system operator (DSO) for power balancing purposes. Submitting forecasts allows a platform for attackers to gain knowledge on user patterns based on the load information provided. The attacker could, for example, enter the home to steal valuable possessions when the homeowner is away. In this paper, we propose a framework using a smart contract within a private blockchain to keep customer information private when communicating with the DSO. The results show the HEMS users’ privacy is maintained, while the benefits of data sharing are obtained. Blockchain and its associated smart contracts may be a viable solution to security concerns in DR applications where load forecasts are sent to a DSO.

scholarly journals An Overview of the Building Energy Management System Considering the Demand Response Programs, Smart Strategies and Smart Grid

Energies ◽  
2020 ◽  
Vol 13 (13) ◽  
pp. 3299 ◽  
Author(s):  
Mohammad Shakeri ◽  
Jagadeesh Pasupuleti ◽  
Nowshad Amin ◽  
Md. Rokonuzzaman ◽  
Foo Wah Low ◽  
...  
Keyword(s):  
Smart Grid ◽  
Energy Management ◽  
Demand Response ◽  
Smart Grids ◽  
Management System ◽  
Management Systems ◽  
Energy Management System ◽  
Energy Management Systems ◽  
Home Energy Management ◽  
Demand Response Programs

Electricity demand is increasing, as a result of increasing consumers in the electricity market. By growing smart technologies such as smart grid and smart energy management systems, customers were given a chance to actively participate in demand response programs (DRPs), and reduce their electricity bills as a result. This study overviews the DRPs and their practices, along with home energy management systems (HEMS) and load management techniques. The paper provides brief literature on HEMS technologies and challenges. The paper is organized in a way to provide some technical information about DRPs and HEMS to help the reader understand different concepts about the smart grid, and be able to compare the essential concerns about the smart grid. The article includes a brief discussion about DRPs and their importance for the future of energy management systems. It is followed by brief literature about smart grids and HEMS, and a home energy management system strategy is also discussed in detail. The literature shows that storage devices have a huge impact on the efficiency and performance of energy management system strategies.

scholarly journals Incentive Price-Based Demand Response in Active Distribution Grids

2020 ◽  
Vol 11 (1) ◽  
pp. 180
Author(s):  
Karthikeyan Nainar ◽  
Jayakrishnan Radhakrishna Pillai ◽  
Birgitte Bak-Jensen
Keyword(s):  
Power Consumption ◽  
Demand Response ◽  
Distribution System ◽  
Low Voltage ◽  
Pv Systems ◽  
Home Energy Management ◽  
Demand Response Program ◽  
Battery Energy Storage Systems ◽  
Battery Energy ◽  
Distribution Grids

Integration of PV power generation systems at distribution grids, especially at low-voltage (LV) grids, brings in operational challenges for distribution system operators (DSOs). These challenges include grid over-voltages and overloading of cables during peak PV power production. Battery energy storage systems (BESS) are being installed alongside PV systems by customers for smart home energy management. This paper investigates the utilization of those BESS by DSOs for maintaining the grid voltages within limits. In this context, an incentive price based demand response (IDR) method is proposed for indirect control of charging/discharging power of the BESS according to the grid voltage conditions. It is shown that the proposed IDR method, which relies on a distributed computing application, is able to maintain the grid voltages within limits. The advantage of the proposed distributed implementation is that the DSOs can compute and communicate the incentive prices thereby encouraging customers to actively participate in the demand response program. An iterative distributed algorithm is used to compute the incentive prices of individual BESS to minimize the costs of net power consumption of the customer. The proposed IDR method is tested by conducting simulation studies on the model of a Danish LV grid for few study cases. The simulation results show that by using the proposed method for the control of BESS, node voltages are maintained within limits as well as the costs of net power consumption of BESS owners are minimized.

scholarly journals Gaussian Copula Methodology to Model Photovoltaic Generation Uncertainty Correlation in Power Distribution Networks

Energies ◽  
2021 ◽  
Vol 14 (9) ◽  
pp. 2349
Author(s):  
Harshavardhan Palahalli ◽  
Paolo Maffezzoni ◽  
Giambattista Gruosso
Keyword(s):  
Power Distribution ◽  
Distribution System ◽  
Low Voltage ◽  
Distribution Networks ◽  
Load Flow ◽  
Power Grids ◽  
Gaussian Copula ◽  
Expansion Planning ◽  
Probabilistic Load Flow ◽  
Photovoltaic Generators

Deterministic load flow analyses of power grids do not include the uncertain factors that affect the network elements; hence, their predictions can be very unreliable for distribution system operators and for the decision makers who deal with the expansion planning of the power network. Adding uncertain probability parameters in the deterministic load flow is vital to capture the wide variability of the currents and voltages. This is achieved by probabilistic load flow studies. Photovoltaic systems represent a remarkable source of uncertainty in the distribution network. In this study, we used a Gaussian copula to model the uncertainty in correlated photovoltaic generators. Correlations among photovoltaic generators were also included by exploiting the Gaussian copula technique. The large sets of samples generated with a statistical method (Gaussian copula) were used as the inputs for Monte Carlo simulations. The proposed methodologies were tested on two different networks, i.e., the 13 node IEEE test feeder and the non-synthetic European low voltage test network. Node voltage uncertainty and network health, measured by the percentage voltage unbalance factor, were investigated. The importance of including correlations among photovoltaic generators is discussed.

scholarly journals Evolution of the Electricity Distribution Networks—Active Management Architecture Schemes and Microgrid Control Functionalities

2021 ◽  
Vol 11 (6) ◽  
pp. 2793
Author(s):  
Katja H. Sirviö ◽  
Hannu Laaksonen ◽  
Kimmo Kauhaniemi ◽  
Nikos Hatziargyriou
Keyword(s):  
Smart Grids ◽  
Low Voltage ◽  
Unified Modeling Language ◽  
Distribution Networks ◽  
Active Management ◽  
Modeling Language ◽  
Electricity Distribution ◽  
Management Architecture ◽  
Network Operations ◽  
Microgrid Control

The power system transition to smart grids brings challenges to electricity distribution network development since it involves several stakeholders and actors whose needs must be met to be successful for the electricity network upgrade. The technological challenges arise mainly from the various distributed energy resources (DERs) integration and use and network optimization and security. End-customers play a central role in future network operations. Understanding the network’s evolution through possible network operational scenarios could create a dedicated and reliable roadmap for the various stakeholders’ use. This paper presents a method to develop the evolving operational scenarios and related management schemes, including microgrid control functionalities, and analyzes the evolution of electricity distribution networks considering medium and low voltage grids. The analysis consists of the dynamic descriptions of network operations and the static illustrations of the relationships among classified actors. The method and analysis use an object-oriented and standardized software modeling language, the unified modeling language (UML). Operational descriptions for the four evolution phases of electricity distribution networks are defined and analyzed by Enterprise Architect, a UML tool. This analysis is followed by the active management architecture schemes with the microgrid control functionalities. The graphical models and analysis generated can be used for scenario building in roadmap development, real-time simulations, and management system development. The developed method, presented with high-level use cases (HL-UCs), can be further used to develop and analyze several parallel running control algorithms for DERs providing ancillary services (ASs) in the evolving electricity distribution networks.

scholarly journals Blockchain-Enabled Transactive Home Energy Management Systems in Distribution Networks

2020 ◽  
Author(s):  
Lawryn Edmonds ◽  
Bo Liu ◽  
Hongyu Wu ◽  
Hang Zhang ◽  
Don Gruenbacher ◽  
...  
Keyword(s):  
Energy Management ◽  
Distribution System ◽  
Distribution Networks ◽  
Electric Utility ◽  
Management Systems ◽  
Energy Management Systems ◽  
Customer Information ◽  
Viable Solution ◽  
Home Energy Management ◽  
System Operator

As home energy management systems (HEMSs) are implemented in homes as ways of reducing customer costs and providing demand response (DR) to the electric utility, homeowner’s privacy can be compromised. As part of the HEMS framework, homeowners are required to send load forecasts to the distribution system operator (DSO) for power balancing purposes. Submitting forecasts allows a platform for attackers to gain knowledge on user patterns based on the load information provided. The attacker could, for example, enter the home to steal valuable possessions when the homeowner is away. In this paper, we propose a framework using a smart contract within a private blockchain to keep customer information private when communicating with the DSO. The results show the HEMS users’ privacy is maintained, while the benefits of data sharing are obtained. Blockchain and its associated smart contracts may be a viable solution to security concerns in DR applications where load forecasts are sent to a DSO.

scholarly journals Machine Learning and GIS Approach for Electrical Load Assessment to Increase Distribution Networks Resilience

Energies ◽  
2021 ◽  
Vol 14 (14) ◽  
pp. 4133
Author(s):  
Alessandro Bosisio ◽  
Matteo Moncecchi ◽  
Andrea Morotti ◽  
Marco Merlo
Keyword(s):  
Machine Learning ◽  
Distribution System ◽  
Low Voltage ◽  
Regression Tree ◽  
Distribution Networks ◽  
Machine Learning Algorithms ◽  
Extreme Weather Events ◽  
Medium Voltage ◽  
Weather Events ◽  
Building Area

Currently, distribution system operators (DSOs) are asked to operate distribution grids, managing the rise of the distributed generators (DGs), the rise of the load correlated to heat pump and e-mobility, etc. Nevertheless, they are asked to minimize investments in new sensors and telecommunication links and, consequently, several nodes of the grid are still not monitored and tele-controlled. At the same time, DSOs are asked to improve the network’s resilience, looking for a reduction in the frequency and impact of power outages caused by extreme weather events. The paper presents a machine learning GIS-based approach to estimate a secondary substation’s load profiles, even in those cases where monitoring sensors are not deployed. For this purpose, a large amount of data from different sources has been collected and integrated to describe secondary substation load profiles adequately. Based on real measurements of some secondary substations (medium-voltage to low-voltage interface) given by Unareti, the DSO of Milan, and georeferenced data gathered from open-source databases, unknown secondary substations load profiles are estimated. Three types of machine learning algorithms, regression tree, boosting, and random forest, as well as geographic information system (GIS) information, such as secondary substation locations, building area, types of occupants, etc., are considered to find the most effective approach.

scholarly journals Laplacian Matrix-Based Power Flow Formulation for LVDC Grids with Radial and Meshed Configurations

Energies ◽  
2021 ◽  
Vol 14 (7) ◽  
pp. 1866
Author(s):  
Zahid Javid ◽  
Ulas Karaagac ◽  
Ilhan Kocar ◽  
Ka Wing Chan
Keyword(s):  
Fixed Point ◽  
Power Flow ◽  
Low Voltage ◽  
Mathematical Formulation ◽  
Distribution Networks ◽  
Load Flow ◽  
Banach Fixed Point Theorem ◽  
Loading Conditions ◽  
Flow Equations ◽  
Uniqueness Of The Solution

There is an increasing interest in low voltage direct current (LVDC) distribution grids due to advancements in power electronics enabling efficient and economical electrical networks in the DC paradigm. Power flow equations in LVDC grids are non-linear and non-convex due to the presence of constant power nodes. Depending on the implementation, power flow equations may lead to more than one solution and unrealistic solutions; therefore, the uniqueness of the solution should not be taken for granted. This paper proposes a new power flow solver based on a graph theory for LVDC grids having radial or meshed configurations. The solver provides a unique solution. Two test feeders composed of 33 nodes and 69 nodes are considered to validate the effectiveness of the proposed method. The proposed method is compared with a fixed-point methodology called direct load flow (DLF) having a mathematical formulation equivalent to a backward forward sweep (BFS) class of solvers in the case of radial distribution networks but that can handle meshed networks more easily thanks to the use of connectivity matrices. In addition, the convergence and uniqueness of the solution is demonstrated using a Banach fixed-point theorem. The performance of the proposed method is tested for different loading conditions. The results show that the proposed method is robust and has fast convergence characteristics even with high loading conditions. All simulations are carried out in MATLAB 2020b software.

Sign in / Sign up

Export Citation Format

Share Document