Smart streetlights for smart cities

Streetlights are a key asset in any city as they provide a sense of safety and security to the public, especially pedestrians, and increase the quality of life by artificially extending the day. Streetlights that are smart and operate intelligently and autonomously can provide added benefits of additional lower energy consumption and lower carbon emissions. Such an asset can also provide the extra connectivity and sensor data flows required to allow algorithms centrally or locally deployed to act on relevant information to optimise asset energy usage and provide a degree of automation of operation. This article will discuss a smart street lighting system developed by Autonomous-IoT, a UK-based SME

Power loss minimisation of off-grid solar DC nano-grids - part II : a quasi-consensus-based distributed control algorithm

This paper investigates the power loss minimization problem of solar DC nanogrids that are designed to provide energy access to households in off-grid areas. We consider nano-grids with distributed battery storage energy systems and that are enabled by multi-port DC-DC converters. As the nano-grids are not connected to the national grid and have batteries and converters distributed in each household, addressing the power loss problem while ensuring supply-demand balance is a challenge. To address the challenge, we propose a novel quasi-consensus based distributed control approach. The proposed approach consists of two algorithms namely, incremental loss consensus algorithm and voltage consensus algorithm. The incremental loss consensus algorithm is proposed to optimally schedule the battery charge/discharge operation while ensuring that supply-demand balance and the battery constraints are satisfied. The voltage consensus algorithm is proposed to determine optimal distribution voltage set points which act as optimal control signals. Both algorithms are implemented in a distributed manner, where minimal information exchange between households is required to obtain the optimal control actions. Simulation results of a solar DC nano-grid with five interconnected households verify the effectiveness of the proposed approach at addressing the nano-grid power loss problem

Power loss minimization of off-grid solar DC nano-grids—part I : centralized control algorithm

Peer-to-peer interconnection of households having on-site batteries, multi-port converters and solar panels to form a multi-port converter-enabled solar DC nano-grid is an emerging approach for providing affordable energy access in rural areas. Battery charge and discharge losses, distribution losses and converter losses are significant problem when operating such nano-grids. This paper presents a centralized control algorithm that can help address the power loss problem. The proposed algorithm uses a new problem formulation where the power loss problem is formulated as a two-stage convex optimization problem. The first stage of the optimization problem is an optimal battery dispatch problem for determining optimal battery charge and discharge currents. The second stage is an optimal current flow problem for determining optimal distribution voltages which corresponds to the optimal battery currents. Simulation results of the nano-grid show that the proposed algorithm can minimize the nano-grid power losses while facilitating the power exchange between the households. The proposed algorithm is suitable for small nano-grids where privacy of households is not a concern. In Part II of this paper we propose a distributed control algorithm that preserves the privacy of the households especially where the size of the nano-grid is large

State of charge based droop control for coordinated power exchange in low voltage DC nanogrids

Decentralized battery and solar photovoltaic (PV) system organized in the form of an autonomous low voltage DC nanogrid is a potentially low cost and scalable solution for electrifying rural areas without access to the national grid. Each DC nanogrid can be installed on a single home and used to supply basic lighting, charge mobile phones and power a television set. To provide enough power to meet productive energy uses such as irrigation, the DC nanogrid can be connected to neighboring DC nanogrids to form a cluster and exchange power. However, to achieve a coordinated power exchange in the cluster, new control strategies are required. In this paper, we propose a decentralized droop control method which uses a state of charge of the battery to coordinate the power exchange. The power exchange is achieved by scheduling a terminal voltage set point at each DC nanogrid based on the state of charge of the battery. The performance of the proposed method at achieving the power exchange is analyzed through simulations in Matlab/Simulink. The method does not require inter-unit communication. Therefore, the method is reliable, robust and scalable. Also, the method maintains low amounts of power flow in distribution lines during power exchange to reduce distribution line power losses

Forecast of electric vehicle uptake across counties in England : Dataset from S-curve analysis

Regional data from the UK Government's Department for Transport has been analyzed to produce a forecasted dataset of the uptake of electric vehicles (EVs) within Counties of England to the first quarter of the year 2100 using an S-curve methodology. This data includes all vehicles, not just cars. The historic proportion of electric vehicles in the fleets of these regions is calculated using data from 2011 Q4 to 2021 Q1. This data is then analyzed using SCATE, the S-Curve Adoption Tool for EVs to forecast the future proportion of electric vehicles in these Counties. Two data tables are presented: the reformatted historic data and the data from the S-curve analysis. Data is also presented for the collective UK

Intelligent sensor network for future fuel mix detection and measurement

Integrating hydrogen and other unconventional gasses in emerging energy networks will play a major role in the transition to a net-zero energy system. This will also bring significant technical challenges that require an efficient, reliable, and low-cost solution to measure and classify the flow of complex gas mixtures. The inaccuracy of measurement and detection of leakage during production, storage, transportation and refuelling operations can result in serious economic implications and safety risks. These challenges are not limited to resolving the uncertainty in quality control but also encompass efficient flow metering, quality assurance, eliminating measurement errors and integration of the sensor technologies. In this article, we will discuss the challenges of integrating gas measurement and detection technologies and identify potential opportunities for innovation

OPEN : an open-source platform for developing smart local energy system applications

This paper presents OPEN, an open-source software platform for integrated modelling, control and simulation of smart local energy systems. Electric power systems are undergoing a fundamental transition towards a significant proportion of generation and flexibility being provided by distributed energy resources. The concept of ‘smart local energy systems’ brings together related strategies for localised management of distributed energy resources, including active distribution networks, microgrids, energy communities, multi-energy hubs, peer-to-peer trading platforms and virtual power plants. OPEN provides an extensible platform for developing and testing new smart local energy system management applications, helping to bridge the gap between academic research and industry translation. OPEN combines features for managing smart local energy systems which are not provided together by existing energy management tools, including multi-phase distribution network power flow, energy market modelling, nonlinear energy storage modelling and receding horizon optimisation. The platform is implemented in Python with an object-oriented structure, providing modularity and allowing it to be easily integrated with third-party packages. Case studies are presented, demonstrating how OPEN can be used for a range of smart local energy system applications due to its support of multiple model fidelities for simulation and control

Distributed State of Charge-Based Droop Control Algorithm for Reducing Power Losses in Multi-Port Converter-Enabled Solar DC Nano-Grids

This paper aims to address the power loss problem of multi-port converter-enabled solar DC nano-grids (or simply nano-grids) that are designed to provide energy access in rural areas. Nano-grids are low voltage DC energy systems that are built for energy access by gradually interconnecting households that have solar panels, batteries and multi-port converters. Due to low distribution voltage levels (≤120 V), scattered households in rural areas and bidirectional power exchange between the households, power losses such as distribution line losses, battery charge/discharge losses and converter losses are significant in nano-grids. As batteries are distributed in each household and the nano-grid network configuration is dynamic in nature owing to the gradual interconnection of households, addressing the power loss problem using conventional optimization techniques is a challenge. To address the challenge, we propose a novel distributed state of charge-based droop control algorithm that does not require prior knowledge of the nano-grid network configuration. The proposed algorithm minimizes the power losses by reducing the magnitude of power flow in the nano-grid at each time instant through battery state of charge balancing. Numerical and simulation results demonstrate the effectiveness of the proposed algorithm