Weather and electrical demand and consumption data of a small Mexican community.

The development of novel technologies to mitigate the effects of climate change through Smart Grids requires energy related data. Unfortunately, this type of data is not always available in Mexico, especially from non-large urban areas and at the household level. Therefore, we present a dataset that contains electrical demand and consumption time series of 5 households within a small community in Mexico, at various resolutions, as well as weather data. The electrical demand is given in 15 min resolution, while the electrical consumption is presented in both hourly and daily resolutions. The data is contained within 15 separate .csv files; one for each household's resolution. In turn, the weather data is given in two .csv files (for outdoor and indoor variables, respectively) that together contain 24 meteorological variables measured in a 5 min resolution that is not always consistent. The dataset comprises of two separate folders that contain either the electrical demand and consumption files or the weather files. This dataset could aid in the development of novel smart grid methods and algorithms that might be able to push the energy transition in Mexico and other developing countries forward.

Development a Low-Cost Wireless Smart Meter with Power Quality Measurement for Smart Grid Applications.

Developing a low-cost wireless energy meter with power quality measurements for smart grid applications represents a significant advance in efficient and accurate electric energy monitoring. In increasingly complex and interconnected electric systems, this device will be essential for a wide range of applications, such as smart grids, by introducing a real-time energy monitoring system. In light of this, smart meters can offer greater opportunities for sustainable and efficient energy use and improve the utilization of energy sources, especially those that are nonrenewable. According to the 2020 International Energy Agency (IEA) report, nonrenewable energy sources represent 65% of the global supply chain. The smart meter developed in this work is based on the ESP32 microcontroller and easily accessible components since it includes a user-friendly development platform that offers a cost-effective solution while ensuring reliable performance. The main objective of developing the smart meters was to enhance the software and simplify the hardware. Unlike traditional meters that calculate electrical parameters by means of complex circuits in hardware, this project performed the calculations directly on the microcontroller. This procedure reduced the complexity of the hardware by simplifying the meter design. Owing to the high-performance processing capability of the microcontroller, efficient and accurate calculations of electrical parameters could be achieved without the need for additional circuits. This software-driven approach with simplified hardware led to benefits, such as reduced production costs, lower energy consumption, and a meter with improved accuracy, as well as updates on flexibility. Furthermore, the integrated wireless connectivity in the microcontroller enables the collected data to be transmitted to remote monitoring systems for later analysis. The innovative feature of this smart meter lies in the fact that it has readily available components, along with the ESP32 chip, which results in a low-cost smart meter with performance that is comparable to other meters available on the market. Moreover, it is has the capacity to incorporate IoT and artificial intelligence applications. The developed smart meter is cost effective and energy efficient, and offers benefits with regard to flexibility, and thus represents an innovative, efficient, and versatile solution for smart grid applications.

Towards an Efficient Method for Large-Scale Wi-SUN-Enabled AMI Network Planning.

In a smart grid communication network, positioning key devices (routers and gateways) is an NP-Hard problem as the number of candidate topologies grows exponentially according to the number of poles and smart meters. The different terrain profiles impose distinct communication losses between a smart meter and a key device position. Additionally, the communication topology must consider the position of previously installed distribution automation devices (DAs) to support the power grid remote operation. We introduce the heuristic method AIDA (AI-driven AMI network planning with DA-based information and a link-specific propagation model) to evaluate the connectivity condition between the meters and key devices. It also uses the link-received power calculated for the edges of a Minimum Spanning Tree to propose a simplified multihop analysis. The AIDA method proposes a balance between complexity and efficiency, eliminating the need for empirical terrain characterization. Using a spanning tree to characterize the connectivity topology between meters and routers, we suggest a heuristic approach capable of alleviating complexity and facilitating scalability. In our research, the interest is in proposing a method for positioning communication devices that presents a good trade-off between network coverage and the number of communication devices. The existing literature explores the theme by presenting different techniques for ideal device placement. Still rare are the references that meticulously explore real large-scale scenarios or the communication feasibility between meters and key devices, considering the detailed topography between the devices. The main contributions of this work include: (1) The presentation of an efficient AMI planning method with a large-scale focus; (2) The use of a propagation model that does not depend on an empirical terrain classification; and (3) The use of a heuristic approach based on a spanning tree, capable of evaluating a smaller number of connections and, even so, proposing a topology that uses fewer router and gateway positions compared to an approach that makes general terrain classification. Experiments in four real large-scale scenarios, totaling over 230,000 smart meters, demonstrate that AIDA can efficiently provide high-quality connectivity demanding a reduced number of devices. Additional experiments comparing AIDA's detailed terrain-based propagation model to the Erceg-SUI Path Loss model suggest that AIDA can reach the smart meter's coverage with a fewer router positions.

A System-on-a-Chip Implementation of a Post-Quantum Cryptography Scheme for Smart Meter Data Communications.

The security of Smart Meter (SM) systems will be a challenge in the era of quantum computing because a quantum computer might exploit characteristics of well-established cryptographic schemes to reach a successful security breach. From a practical perspective, this paper focuses on the feasibility of implementing a quantum-secure lattice-based key encapsulation mechanism in a SM, hardware-constrained equipment. In this regard, the post-quantum cryptography (PQC) scheme, FrodoKEM, an alternate candidate for the National Institute for Standards and Technology (NIST) post-quantum standardization process, is implemented using a System-on-a-Chip (SoC) device in which the Field Programmable Gate Array (FPGA) component is exploited to accelerate the most time-consuming routines in this scheme. Experimental results show that the execution time to run the FrodoKEM scheme in an SoC device reduces to one-third of that obtained by the benchmark implementation (i.e., the software implementation). Also, the attained execution time and hardware resource usage of this SoC-based implementation of the FrodoKEM scheme show that lattice-based cryptography may fit into SM equipment.

Bio-inspired negotiation approach for smart-grid colocation datacenter operation.

Demand response programs allow consumers to participate in the operation of a smart electric grid by reducing or shifting their energy consumption, helping to match energy consumption with power supply. This article presents a bio-inspired approach for addressing the problem of colocation datacenters participating in demand response programs in a smart grid. The proposed approach allows the datacenter to negotiate with its tenants by offering monetary rewards in order to meet a demand response event on short notice. The objective of the underlying optimization problem is twofold. The goal of the datacenter is to minimize its offered rewards while the goal of the tenants is to maximize their profit. A two-level hierarchy is proposed for modeling the problem. The upper-level hierarchy models the datacenter planning problem, and the lower-level hierarchy models the task scheduling problem of the tenants. To address these problems, two bio-inspired algorithms are designed and compared for the datacenter planning problem, and an efficient greedy scheduling heuristic is proposed for task scheduling problem of the tenants. Results show the proposed approach reports average improvements between 72.9% and 82.2% when compared to the business as usual approach.

Data Security and Trading Framework for Smart Grids in Neighborhood Area Networks.

Due to the drastic increase of electricity prosumers, i.e., energy consumers that are also producers, smart grids have become a key solution for electricity infrastructure. In smart grids, one of the most crucial requirements is the privacy of the final users. The vast majority of the literature addresses the privacy issue by providing ways of hiding user's electricity consumption. However, open issues in the literature related to the privacy of the electricity producers still remain. In this paper, we propose a framework that preserves the secrecy of prosumers' identities and provides protection against the traffic analysis attack in a competitive market for energy trade in a Neighborhood Area Network (NAN). In addition, the amount of bidders and of successful bids are hidden from malicious attackers by our framework. Due to the need for small data throughput for the bidders, the communication links of our framework are based on a proprietary communication system. Still, in terms of data security, we adopt the Advanced Encryption Standard (AES) 128 bit with Exclusive-OR (XOR) keys due to their reduced computational complexity, allowing fast processing. Our framework outperforms the state-of-the-art solutions in terms of privacy protection and trading flexibility in a prosumer-to-prosumer design.

A data set for electric power consumption forecasting based on socio-demographic features: Data from an area of southern Colombia.

In this article, we introduce a data set concerning electric-power consumption-related features registered in seven main municipalities of Nariño, Colombia, from December 2010 to May 2016. The data set consists of 4427 socio-demographic characteristics, and 7 power-consumption-referred measured values. Data were fully collected by the company Centrales Eléctricas de Nariño (CEDENAR) according to the client consumption records. Power consumption data collection was carried following a manual procedure wherein company workers are in charge of manually registering the readings (measured in kWh) reported by the electric energy meters installed at each housing/building. Released data set is aimed at providing researchers a suitable input for designing and assessing the performance of forecasting, modelling, simulation and optimization approaches applied to electric power consumption prediction and characterization problems. The data set, so-named in shorthand PCSTCOL, is freely and publicly available at https://doi.org/10.17632/xbt7scz5ny.3.

A Cost Analysis of Implementing a Blockchain Architecture in a Smart Grid Scenario Using Sidechains.

Smart grid systems have become popular and necessary for the development of a sustainable power grid. These systems use different technologies to provide optimized services to the users of the network. Regarding computing, these systems optimize electrical services by processing a large amount of the data generated. However, privacy and security are essential in this kind of system. With a large amount of data generated, it is necessary to protect the privacy of users, because this data may reveal the users' personal information. Today, blockchain technology has proven to be an efficient architecture for solving privacy and security problems in different scenarios. Over the years, different blockchain platforms have emerged, attempting to solve specific problems in different areas. However, the use of different platforms fragmented the market, which was no different in the smart grid scenario. This work proposes a blockchain architecture that uses sidechains to make the system scalable and adaptable. We used three blockchains to ensure privacy, security, and trust in the system. To universalize the proposed solution, we used the Open Smart Grid Protocol and smart contracts. The results show that architecture security and privacy are guaranteed, making it feasible for implementation in real systems; although scalability issues regarding the storage of the data generated still exist.

Hybrid AC/DC microgrid test system simulation: grid-connected mode.

In this paper, a Microgrid (MG) test model based on the 14-busbar IEEE distribution system is proposed. This model can constitute an important research tool for the analysis of electrical grids in its transition to Smart Grids (SG). The benchmark is used as a base case for power flow analysis and quality variables related with SG and holds distributed resources. The proposed MG consists of DC and AC buses with different types of loads and distributed generation at two voltage levels. A complete model of this MG has been simulated using the MATLAB/Simulink environmental simulation platform. The proposed electrical system will provide a base case for other studies such as: reactive power compensation, stability and inertia analysis, reliability, demand response studies, hierarchical control, fault tolerant control, optimization and energy storage strategies.

Fog Computing Model to Orchestrate the Consumption and Production of Energy in Microgrids.

Energy advancement and innovation have generated several challenges for large modernized cities, such as the increase in energy demand, causing the appearance of the small power grid with a local source of supply, called the Microgrid. A Microgrid operates either connected to the national centralized power grid or singly, as a power island mode. Microgrids address these challenges using sensing technologies and Fog-Cloudcomputing infrastructures for building smart electrical grids. A smart Microgrid can be used to minimize the power demand problem, but this solution needs to be implemented correctly so as not to increase the amount of data being generated. Thus, this paper proposes the use of Fog computing to help control power demand and manage power production by eliminating the high volume of data being passed to the Cloud and decreasing the requests' response time. The GridLab-d simulator was used to create a Microgrid, where it is possible to exchange information between consumers and generators. Thus, to understand the potential of the Fog in this scenario, a performance evaluation is performed to verify how factors such as residence number, optimization algorithms, appliance shifting, and energy sources may influence the response time and resource usage.

SDN Architecture for 6LoWPAN Wireless Sensor Networks.

Wireless sensor networks (WSN) are being increasingly used for data acquisition and control of remote devices. However, they present some constraints in critical and large-scale scenarios. The main limitations come from the nature of their components, such as lossy links, and devices with power supply limitations, poor processing power and limited memory. The main feature of software-defined networks (SDN) is the separation between the control plane and the data plane, making available a logically unified view of the topology in the controllers. In this way, it is possible to build network applications that take into account this unified view, which makes the SDN an alternative approach to solve the mentioned limitations. This paper presents the SD6WSN (software-defined 6LoWPAN wireless sensor network) architecture, developed to control the behavior of the data traffic in 6LoWPAN according to the SDN approach. It takes into account the specific characteristics of WSN devices, such as low data transfer rate, high latency, packet loss and low processing power, and takes advantage of the flexibility provided by flow-based forwarding, allowing the development of specific networking applications based on a unified view. We provide a detailed description of how we have implemented SD6WSN in the Contiki operating system. The new architecture is assessed in two experiments. The first considers a typical advanced metering infrastructure (AMI) network and measures the overhead of SD6WSN control messages in configurations involving different path lengths. The results indicate that the overhead introduced is not excessive, given the advantages that the SDN approach can bring. The second considers a grid-topology to evaluate the average latency of the peer-to-peer communication. It was observed that the average latency in the SD6WSN is considerably lower than that obtained with standard 6LoWPAN, showing the potential of the proposed approach.

Infrastructure for Integration of Legacy Electrical Equipment into a Smart-Grid Using Wireless Sensor Networks.

At present, the standardisation of electrical equipment communications is on the rise. In particular, manufacturers are releasing equipment for the smart grid endowed with communication protocols such as DNP3, IEC 61850, and MODBUS. However, there are legacy equipment operating in the electricity distribution network that cannot communicate using any of these protocols. Thus, we propose an infrastructure to allow the integration of legacy electrical equipment to smart grids by using wireless sensor networks (WSNs). In this infrastructure, each legacy electrical device is connected to a sensor node, and the sink node runs a middleware that enables the integration of this device into a smart grid based on suitable communication protocols. This middleware performs tasks such as the translation of messages between the power substation control centre (PSCC) and electrical equipment in the smart grid. Moreover, the infrastructure satisfies certain requirements for communication between the electrical equipment and the PSCC, such as enhanced security, short response time, and automatic configuration. The paper’s contributions include a solution that enables electrical companies to integrate their legacy equipment into smart-grid networks relying on any of the above mentioned communication protocols. This integration will reduce the costs related to the modernisation of power substations.

State-of-the-Art Impacts of Smart Grid in the Power Systems Operation and Expansion Planning

ABSTRACT In this article, a state-of-the-art review on the impacts of Smart Grid in the operation and planning of the expansion of the Electric Power System is presented. The concept of Smart Grid is increasingly integrated in conventional networks, and the impact that this new technology generates on operation and planning must be investigated. Thus, in this article a survey of the main scientific publications was made with the purpose of determining the impacts and methodologies most used in this analysis. Efforts to analyze impacts are large because of the high degree of uncertainty of this new technology added to the problem. After the bibliographic survey, it was concluded that Robust Optimization and Genetic Algorithms are methodologies that are effective in problems of this nature and are the most adopted methods.

Computational Model for Microgeneration Simulation, From Solar and Wind Renewable Sources, With Optimal Allocation of Loads, Electric Vehicle and Energy Storage, In a Residential Electrical Micro Network

Abstract The electrical sector is under constant evolution. One of the areas refers to the consumers that come to be generators, implementing distributed generation, interconnected to a smart grid. This article discusses the improvement of an algorithm, already presented in the literature, to make the best temporal allocation of loads, electric vehicle, storage and many sources of generation, aiming at the maximum financial performance, that is, the lowest value for the energy invoice The modeling consists of a Mixed Integer Linear Programming (MILP) algorithm, which considers each component of the system and weighs the maintenance and shelf life of storage devices, basically batteries, loads that can be reallocated and the concept of Vehicle-to-grid, performing a daily analysis. The simulation has considered the hypothetical case of a residence, in which are included storage, electric vehicle and redistribution of loads, as well as wind and solar generation. Several scenarios are simulated, with or without the presence of some of the components. The results indicate that the simplest model, only redistributing the loads, can provide a sensible monetary savings of approximately 60%, while with the application of all the components modeled, there can be a reduction in the invoice of 90%.

Power Flow Analysis and Self-recovery of Electrical Energy Distribution Network Using Artificial Neural Networks

ABSTRACT A computational model for self-recovery of electricity distribution network was developed to simulate it, emulated by the IEEE 123 node model. The electrical system considered has automatic switches capable of identifying a momentary failure in the line and finding the best reconfiguration for its reclosing. An artificial neural network (ANN), backpropagation, was used to classify the type of failure and determine the best reconfiguration of the distribution network. Initially, five power failure scenarios were simulated in certain different parts of the power grid, and power flow analysis via OpenDSS was performed. Next, the most suitable switching was observed within the shortest time interval to restore the power supply. With the purpose of better visualization to identify the reclosing, an implementation was carried out via ELIPSE SCADA. In this way, it is possible to identify the faulted segment in order to isolate it, leaving the smallest number of consumers without power supply in shortest possible time. With the results of the simulations, tests and analyzes were performed to verify their robustness and speed, in the expectation that the model developed be faster than an experienced Operating Distribution Center.

Planning low-carbon electricity systems under uncertainty considering operational flexibility and smart grid technologies.

Electricity grid operators and planners need to deal with both the rapidly increasing integration of renewables and an unprecedented level of uncertainty that originates from unknown generation outputs, changing commercial and regulatory frameworks aimed to foster low-carbon technologies, the evolving availability of market information on feasibility and costs of various technologies, etc. In this context, there is a significant risk of locking-in to inefficient investment planning solutions determined by current deterministic engineering practices that neither capture uncertainty nor represent the actual operation of the planned infrastructure under high penetration of renewables. We therefore present an alternative optimization framework to plan electricity grids that deals with uncertain scenarios and represents increased operational details. The presented framework is able to model the effects of an array of flexible, smart grid technologies that can efficiently displace the need for conventional solutions. We then argue, and demonstrate via the proposed framework and an illustrative example, that proper modelling of uncertainty and operational constraints in planning is key to valuing operationally flexible solutions leading to optimal investment in a smart grid context. Finally, we review the most used practices in power system planning under uncertainty, highlight the challenges of incorporating operational aspects and advocate the need for new and computationally effective optimization tools to properly value the benefits of flexible, smart grid solutions in planning. Such tools are essential to accelerate the development of a low-carbon energy system and investment in the most appropriate portfolio of renewable energy sources and complementary enabling smart technologies.This article is part of the themed issue 'Energy management: flexibility, risk and optimization'.

A Power Planning Algorithm Based on RPL for AMI Wireless Sensor Networks.

The advanced metering infrastructure (AMI) is an architecture for two-way communication between electric, gas and water meters and city utilities. The AMI network is a wireless sensor network that provides communication for metering devices in the neighborhood area of the smart grid. Recently, the applicability of a routing protocol for low-power and lossy networks (RPL) has been considered in AMI networks. Some studies in the literature have pointed out problems with RPL, including sub-optimal path selection and instability. In this paper, we defend the viewpoint that careful planning of the transmission power in wireless RPL networks can significantly reduce the pointed problems. This paper presents a method for planning the transmission power in order to assure that, after convergence, the size of the parent set of the RPL nodes is as close as possible to a predefined size. Another important feature is that all nodes in the parent set offer connectivity through links of similar quality.

Multicast Delayed Authentication For Streaming Synchrophasor Data in the Smart Grid.

Multicast authentication of synchrophasor data is challenging due to the design requirements of Smart Grid monitoring systems such as low security overhead, tolerance of lossy networks, time-criticality and high data rates. In this work, we propose inf -TESLA, Infinite Timed Efficient Stream Loss-tolerant Authentication, a multicast delayed authentication protocol for communication links used to stream synchrophasor data for wide area control of electric power networks. Our approach is based on the authentication protocol TESLA but is augmented to accommodate high frequency transmissions of unbounded length. inf TESLA protocol utilizes the Dual Offset Key Chains mechanism to reduce authentication delay and computational cost associated with key chain commitment. We provide a description of the mechanism using two different modes for disclosing keys and demonstrate its security against a man-in-the-middle attack attempt. We compare our approach against the TESLA protocol in a 2-day simulation scenario, showing a reduction of 15.82% and 47.29% in computational cost, sender and receiver respectively, and a cumulative reduction in the communication overhead.