Real-Time Control of Power Exchange at Primary Substations: An OPF-Based Solution

Nowadays, integration of more renewable energy resources into distribution systems to inject more clean en- ergy introduces new challenges to power system planning and operation. The intermittent behaviour of variable renewbale resources such as wind and PV generation would make the energy balancing more difficult, as current forecasting tools and existing storage units are insufficient. Transmission system operators may withstand some level of power imbalance, but fluctuations and noise of profiles are undesired. This requires local management performed or encouraged by distribution system operators. They could try to involve aggregators to exploit flexibility of loads through demand response schemes. In this paper, we present an optimal power flow-based algorithm written in Python which reads flexibility of different loads offered by the aggregators from one side, and the power flow deviation with respect to the scheduled profile at transmission-distribution coupling point from the other side, to define where and how much load to adjust. To demonstrate the applicability of this core, we set-up a real- time simulation-based test bed and realised the performance of this approach in a real-like environment using real data of a network

Fault Detection, Isolation and Restoration Test Platform Based on Smart Grid Architecture Model Using Internet-of-Things Approaches

To systematically shift existing distribution outage management paradigms to smart and more efficient schemes, we need to have an architectural overview of Smart Grids to reuse the assets as much as possible. Smart Grid Architecture Model offers a support to design such emerging use cases by representing interoperability aspects among component, function, communication, information, and business layers. To allow this kind of interoperability analysis for design and implementation of Fault Detection, Isolation and Restoration function in outage management systems, we develop an Internet-of-Things-based platform to perform real time co-simulations. Physical components of the grid are modeled in Opal-RT real time simulator, an automated Fault Detection, Isolation and Restoration algorithm is developed in MATLAB and an MQTT communication has been adopted. A 2-feeder MV network with a normally open switch for reconfiguration is modeled to realize the performance of the developed co-simulation platform

A Review on Internet of Things Solutions for Intelligent Energy Control in Buildings for Smart City Applications

A smart city exploits sustainable information and communication technologies to improve the quality and the performance of urban services for citizens and government, while reducing resources consumption. Intelligent energy control in buildings is an important aspect in this. The Internet of Things can provide a solution. It aims to connect numerous heterogeneous devices through the internet, for which it needs a flexible layered architecture in which the things, the people and the cloud services are combined to facilitate an application task. Such flexible IoT hierarchical architecture model will be introduced in this paper with an overview of each key component for intelligent energy control in buildings for smart cities

Techno-economic impacts of automatic undervoltage load shedding under emergency

Different schemes for voltage control under emergency are adopted in different jurisdictions around the world. While some features, such as Automatic Voltage Regulation (AVR), are common in all countries, for what concerns undervoltage load shedding (UVLS), to contrast voltage instability or collapse, different schemes are adopted. Most US transmission system operators (TSOs) adopt automatic UVLS schemes, with different capabilities and settings while TSOs in EU usually do not implement automatic UVLS but leave the decisions to the control room operators. The two options may lead to different impacts in terms of trajectory and final status of the transmission grid under emergency, with different unserved energy. In this paper we analyze the impacts from a technical and economic perspective, modeling the grid behavior with different UVLS schemes (none, manual and automatic). The comparison between the different schemes is done resorting to the Incident Response System (IRS), a software tool developed by the authors in the EU-FP7 SESAME project. An illustrative example to a realistic test case is presented and discussed. This paper shows that automatic UVLS is superior to Manual UVLS, from both technical and economic point of view, due to the fast evolution of voltage collapse phenomena and insufficient time for system operators' manual reaction. The benefits of the scheme involving the automatic UVLS can be then compared with the investment costs of equipping the network with those devices

Challenges and necessities of vulnerability assessment for electricity infrastructures

Many studies and definitions of vulnerability have been published considering multiple aspects collectively which resulted in ambiguities in practical use. Therefore, a clear classification for vulnerability assessment isolating different dimensions of the origins of vulnerability is proposed in this paper. Under the framework, focuses can be brought on a specific dimension for a better understanding of where the system vulnerability arises. A generic pattern of system vulnerabilities, especially operational vulnerabilities, can be subsequently developed for its mitigation

A Novel Integrated Real-time Simulation Platform for Assessing Photovoltaic Penetration Impacts in Smart Grids

For future planning and development of smart grids, it is important to evaluate the impacts of PV distributed generation, especially in densely populated urban areas. In this paper we present an integrated platform, constituted by two main components: a PV simulator and a real-time distribution network simulator. The first simulates real-sky solar radiation of rooftops and estimates the PV energy production; the second simulates the behaviour of the network when generation and consumption are provided at the different buses. The platform is tested on a case study based on real data for a district of the city of Turin, Italy

A Novel Internet-of-Things Infrastructure to Support Self-Healing Distribution Systems

In this paper, we present a novel distributed software infrastructure to foster new services in smart grids with particular emphasis on supporting self-healing distribution systems. This infrastructure exploits the rising Internet-of-Things paradigms to build and manage an interoperable peer-to-peer network of our prototype smart meters, also presented in this paper. The proposed three-phase smart meter, called 3-SMA, is a low cost and open-source Internet-connected device that provides features for self-configuration. In addition, it selectively run onboard-algorithms for smart grid management depending on its deployment on the distribution network. Finally, we present the experimental results of Hardware-In-the-Loop simulations we performed

Planning and real-time management of smart grids with high PV penetration in Italy

For planning and development and in real-time operation of smart grids, it is important to evaluate the impacts of photovoltaic (PV) distributed generation. In this paper, we present an integrated platform, constituted by two main components: a PV simulator and a real-time distribution network simulator. The first, designed and developed following the microservice approach and providing REST web services, simulates real-sky solar radiation on rooftops and estimates the PV energy production; the second, based on a digital real-time power systems simulator, simulates the behaviour of the electric network under the simulated generation scenarios. The platform is tested on a case study based on real data for a district of the city of Turin, Italy. In the results, we show possible applications of the platform for power flow forecasting during real-time operation and to detect possible voltage and transformers capacity problems during planning due to high penetration of Renewable Energy Sources. In particular, the results show that the case study distribution network, in the actual configuration, is not ready to accommodate all the generation capacity that can be installed as, in certain hours of the day and in certain days of the year, the capacity of some transformers is exceeded

Creation of a computational framework for the European transmission grid with Power-to-Gas

The presence of high penetration of Variable Renewable Energy Sources (VRES) is one of the key aspects of the modern electricity system. The new challenges to be faced require novel technologies which enhance the flexibility of the transmission system. In this paper, the exploitation of the power-to-gas technology (PtG) is considered as a solution for the flexibility challenges, allowing to absorb the excess of electricity produced by VRES and at the same time, producing synthetic natural gas (SNG). This work presents a computational framework based on DC Optimal Power Flow capable to simulate the day-ahead market and the following intra-day market, applied to a simplified European transmission network, by considering different scenarios for both load and generation. PtG plants model are modelled based on the real measurements of a 2-MW Alkaline (AEC) electrolyser. The results of a given PtG placement configuration, applied to a current scenario (2017) and two future scenarios (2030&2040) show that the fast response of PtG units improves the system performance and reduces the VRESs’ imbalance up to ~90% in terms of imbalance time duration and ~40% in terms of peak imbalance power. These results lead to further investigations, about the optimal PtG units’ placement and sizing, as well as their economic and technical consequences on the transmission network operation