Open-Source, Open-Architecture SoftwarePlatform for Plug-InElectric Vehicle SmartCharging in California

This interdisciplinary eXtensible Building Operating System–Vehicles project focuses on controlling plug-in electric vehicle charging at residential and small commercial settings using a novel and flexible open-source, open-architecture charge communication and control platform. The platform provides smart charging functionalities and benefits to the utility, homes, and businesses.This project investigates four important areas of vehicle-grid integration research, integrating technical as well as social and behavioral dimensions: smart charging user needs assessment, advanced load control platform development and testing, smart charging impacts, benefits to the power grid, and smart charging ratepayer benefits

Implementation of electrolysers in the power system as a load management mechanism

Abstract unavailable please refer to PD

Influences of a hydrogen electrolyser demand on distribution network under different operational constraints and electricity pricing scenarios

With the long term goal of greenhouse gases reduction by at least 80% set by the UK government, and 100% renewable penetration aimed in Scotland by 2020, water electrolyser and hydrogen fuel cell vehicles provide the potential to contribute to the goals through increasing penetration of renewables in and reducing the CO2 emissions in road transportation. The project on Impact of Electrolysers on the Distribution Network carried out by SSEPD secured innovation funding with an aim to investigate the potential impact of this type of technology on the electrical network. In this project, electrolyser needs to supply sufficient amount of H2 to provide for 10 fuel cell buses running daily in Aberdeen urban area. A number of trials looking at various commercial arrangements and technical requirements are designed to test potential ability of electrolysers to operate under different pricing strategies or schemes designed to help integration of renewable resources

Active Load Management of Hydrogen Refuelling Stations for Increasing the Grid Integration of Renewable Generation

Hydrogen Fuel Cell Electric Vehicles (FCEV) can help reduce carbon emissions, air pollution and dependency on fossil fuels in the transport sector. Clean hydrogen fuel can be generated by a power-to-gas process at refuelling stations equipped with water electrolysers, especially in renewable rich areas. Coupled with onsite hydrogen tanks, the fast response capability of electrolysis, could potentially turn the station demand into a flexible electricity load since the hydrogen can be stored and used when needed. This paper presents a novel real-time load management scheme that actively operates a hydrogen refuelling station to relieve thermal network constraints, handles the fluctuations from renewables, and releases network headroom for connecting renewable generation. The key components involved in the refuelling station and their operational characteristics are explicitly modelled in the analysis. The economic impact of the different operational strategies is also examined. In the case study, the effectiveness of the proposed control strategy to avoid overloading and save curtailment in the local distribution network is verified by running the real-time network simulation at 1 minute steps over a 1 hour window and 5 day window respectively. Moreover, a whole year simulation of the station operation shows that the proposed active control strategy enables wind farms in the local network to avoid 9.5 times more curtailment than under passive control strategy. The station’s net cost of electricity consumption thus can be reduced by 7.5%., by making use of excess electricity that would otherwise be curtailed. A further 5% reduction on the cost would be possible if the incentive rewards for offering network constraint management services are in place

An examination of the feasibility of producing green hydrogen from curtailed, onshore wind power using a North Wales case study

Onshore wind power is considered one of the most important future energy sources, but its intermittent and variable nature present a number of challenges to increasing the supply and penetration of wind energy in our energy systems, including the loss of renewable energy through curtailment. Hydrogen, which has for many years been considered an interesting option is now seriously considered as a possible solution to some of these challenges presented by renewable energy intermittency, variability as well as the decarbonisation challenge of other sectors. Use of hydrogen in this way has recently seen a convergence of political and industry support. This study will aim to examine the feasibility of producing hydrogen from curtailed onshore wind energy using a wind farm in North Wales as a case study. The research begins with a literature review and an analysis of the technical, economic, and environmental feasibility of hydrogen production from onshore wind before presenting an original economic model, offering results on the specific economic feasibility of producing hydrogen from the curtailed generation of a wind farm in North Wales. The results suggest that supplying hydrogen into the transport sector is the most economically feasible solution. The results also consider the economic feasibility of wholesale and gas grid supply. The results are analysed within the geographical context of the case study site and the opportunities for supply and demand of hydrogen which currently exist or planned future development. This research provides in depth analysis and tools to enable better understanding the relationship between onshore wind and hydrogen production in Wales, UK

Classifying and modelling demand response in power systems

Demand response (DR) is expected to play a major role in integrating large shares of variable renewable energy (VRE) sources in power systems. For example, DR can increase or decrease consumption depending on the VRE availability, and use generating and network assets more efficiently. Detailed DR models are usually very complex, hence, unsuitable for large-scale energy models, where simplicity and linearity are key elements to keep a reasonable computational performance. In contrast, aggregated DR models are usually too simplistic and therefore conclusions derived from them may be misleading. This paper focuses on classifying and modelling DR in large-scale models. The first part of the paper classifies different DR services, and provides an overview of benefits and challenges. The second part presents mathematical formulations for different types of DR ranging from curtailment and ideal shifting, to shifting including saturation and immediate load recovery. Here, we suggest a collection of linear constraints that are appropriate for large-scale power systems and integrated energy system models, but sufficiently sophisticated to capture the key effects of DR in the energy system. We also propose a mixed-integer programming formulation for load shifting that guarantees immediate load recovery, and its linear relaxation better approximates the exact solution compared with previous models

Assessment of novel distributed control techniques to address network constraints with demand side management

The development of sustainable generation, a reliable electricity supply and affordable tariffs are the primary requirements to address the uncertainties in different future energy scenarios. Due to the predicted increase in Distributed Generation (DG) and load profile changes in future scenarios, there are significant operational and planning challenges facing netwrok operators. These changes in the power system distribution network require a new Active Network Management (ANM) control system to manage distribution constraint issues such as thermal rating, voltage, and fault levels. The future smart grid focuses on harnessing the control potential from demand side via bidirectional power flow, transparent information communication, and contractual customer participation. Demand Side Management (DSM) is considered as one of the effective solutions to defer network capacity reinforcement, increase energy efficiency, facilitate renewable access, and implement low carbon energy strategy. From the Distribution Network Operator's (DNO) perspective, the control opportunity from Demand Response (DR) and Decentralized Energy Resource (DER) contributes on capacity investment reduction, energy efficiency, and enable low carbon technologies. This thesis develops a new decentralized control system for dealing effectively with the constraint issues in the Medium Voltage (MV) distribution network. In the decentralized control system, two novel control approaches are proposed to autonomously relieve the network thermal constraint via DNO's direct control of the real power in network components during the operation period. The first approach, Demand Response for Power Flow Management (DR-PFM), implements the DSM peak clipping control of Active Demand (AD), whilst the second approach, Hybrid Control for Power Flow Management (HC-PFM), implements the hybrid control of both AD and DER. The novelty of these two new control algorithms consists in the application of a Constraint Satisfaction Problem (CSP) based programming model on decision making of the real power curtailment to relieve the network thermal overload. In the Constraint Programming (CP) model, three constraints are identified: a preference constraint, and a network constraint. The control approaches effectively solve the above constraint problem in the CSP model within 5 seconds' time response. The control performance is influenced by the pre-determined variable, domain and constraint settings. These novel control approaches take advantages on flexible control, fast response and demand participation enabling in the future smart grid.The development of sustainable generation, a reliable electricity supply and affordable tariffs are the primary requirements to address the uncertainties in different future energy scenarios. Due to the predicted increase in Distributed Generation (DG) and load profile changes in future scenarios, there are significant operational and planning challenges facing netwrok operators. These changes in the power system distribution network require a new Active Network Management (ANM) control system to manage distribution constraint issues such as thermal rating, voltage, and fault levels. The future smart grid focuses on harnessing the control potential from demand side via bidirectional power flow, transparent information communication, and contractual customer participation. Demand Side Management (DSM) is considered as one of the effective solutions to defer network capacity reinforcement, increase energy efficiency, facilitate renewable access, and implement low carbon energy strategy. From the Distribution Network Operator's (DNO) perspective, the control opportunity from Demand Response (DR) and Decentralized Energy Resource (DER) contributes on capacity investment reduction, energy efficiency, and enable low carbon technologies. This thesis develops a new decentralized control system for dealing effectively with the constraint issues in the Medium Voltage (MV) distribution network. In the decentralized control system, two novel control approaches are proposed to autonomously relieve the network thermal constraint via DNO's direct control of the real power in network components during the operation period. The first approach, Demand Response for Power Flow Management (DR-PFM), implements the DSM peak clipping control of Active Demand (AD), whilst the second approach, Hybrid Control for Power Flow Management (HC-PFM), implements the hybrid control of both AD and DER. The novelty of these two new control algorithms consists in the application of a Constraint Satisfaction Problem (CSP) based programming model on decision making of the real power curtailment to relieve the network thermal overload. In the Constraint Programming (CP) model, three constraints are identified: a preference constraint, and a network constraint. The control approaches effectively solve the above constraint problem in the CSP model within 5 seconds' time response. The control performance is influenced by the pre-determined variable, domain and constraint settings. These novel control approaches take advantages on flexible control, fast response and demand participation enabling in the future smart grid