Stochastic optimisation-based valuation of smart grid options under firm DG contracts

Under the current EU legislation, Distribution Network Operators (DNOs) are expected to provide firm connections to new DG, whose penetration is set to increase worldwide creating the need for significant investments to enhance network capacity. However, the uncertainty around the magnitude, location and timing of future DG capacity renders planners unable to accurately determine in advance where network violations may occur. Hence, conventional network reinforcements run the risk of asset stranding, leading to increased integration costs. A novel stochastic planning model is proposed that includes generalized formulations for investment in conventional and smart grid assets such as Demand-Side Response (DSR), Coordinated Voltage Control (CVC) and Soft Open Point (SOP) allowing the quantification of their option value. We also show that deterministic planning approaches may underestimate or completely ignore smart technologies

Option valuation of smart grid technology projects under endogenous and exogenous uncertainty

Electricity demand and renewables penetration are set to increase worldwide over the coming decades as part of the global decarbonisation effort. As a result, distribution networks are expected to face challenges related to increased peaks and undesirable voltage excursions. Hence, significant network reinforcements may be required over the next decades. However, a very significant challenge in realizing this transition is the increased uncertainty that surrounds future distributed generation and load connections in terms of size, location and timing. This uncertainty inadvertently will give rise to the prospect of inefficient investments and stranded assets given that current planning practices remain deterministic. It follows that new planning frameworks are needed that allow the quantification of option value and achieve reduction of stranding risk by encouraging cost-efficient strategic investments through smart technologies under both endogenous and exogenous sources of uncertainty. This thesis presents multi-epoch stochastic optimization models, for the distribution network planning problem, that consider a set of investment options with different techno-economical characteristics so as to reflect the multitude of choices available to planners in a realistic setting characterized by endogenous or exogenous uncertainty. These optimization models are rendered tractable through the use of novel decomposition schemes that effectively help manage the associated increased computational burden. The corresponding simulation results validate that smart technologies constitute valuable options for enabling cost effective integration of distributed generation units and underline the importance of early investment in such assets under decision-dependent uncertainty. In addition, the results emphasize that deterministic approaches systematically undervalue the flexibility that smart assets provide, thereby posing a barrier to the advent of the flexible smart grid paradigm.Open Acces

SatNOGS: Satellite Networked Open Ground Station

Abstract—The SatNOGS, or Satellite Network Open Ground Stations, project promotes and supports free and open space applications. It seeks to solve the problem of connecting many satellite users/observers to many ground station operators. Modern open software, web, and hardware techniques are used in implementing the Network, Database, Client, and Ground Station sub- projects. Modularity in all the systems promotes the dual-use of ground stations by not interfering with local operation while utilizing the great amount of time a civilian, non-commercial ground station would otherwise sit idle

Long-Term Expansion Planning of the Transmission Network in India under Multi-Dimensional Uncertainty

Considerable investment in India’s electricity system may be required in the coming decades in order to help accommodate the expected increase of renewables capacity as part of the country’s commitment to decarbonize its energy sector. In addition, electricity demand is geared to significantly increase due to the ongoing electrification of the transport sector, the growing population, and the improving economy. However, the multi-dimensional uncertainty surrounding these aspects gives rise to the prospect of stranded investments and underutilized network assets, rendering investment decision making challenging for network planners. In this work, a stochastic optimization model is applied to the transmission network in India to identify the optimal expansion strategy in the period from 2020 until 2060, considering conventional network reinforcements as well as energy storage investments. An advanced Nested Benders decomposition algorithm was used to overcome the complexity of the multistage stochastic optimization problem. The model additionally considers the uncertainty around the future investment cost of energy storage. The case study shows that deployment of energy storage is expected on a wide scale across India as it provides a range of benefits, including strategic investment flexibility and increased output from renewables, thereby reducing total expected system costs; this economic benefit of planning with energy storage under uncertainty is quantified as Option Value and is found to be in excess of GBP 12.9 bn. The key message of this work is that under potential high integration of wind and solar in India, there is significant economic benefit associated with the wide-scale deployment of storage in the system

Selective Forwarding Attack on IoT Home Security Kits

Efforts have been made to improve the security of the Internet of Things (IoT) devices, but there remain some vulnerabilities and misimplementations. This paper describes a new threat to home security devices in which an attacker can disable all functionality of a device, but to the device’s owner, everything still appears to be operational. We targeted home security devices because their security is critical as people may rely on them to protect their homes. In particular, we exploited a feature called “heartbeat”, which is exchanged between the devices and the cloud in order to check that the devices are still connected. Even though network traffic was encrypted, we successfully identified the heartbeats due to their fixed size and periodic nature. Thereafter, we established a man-in-the-middle attack between the device and the cloud and selectively forwarded heartbeats while filtering out other traffic. As a result, the device appears to be still connected (because the heartbeat traffic is being allowed through), while in reality the device’s functionality is disabled (because non-heartbeat traffic is being filtered out). We applied this exploit on a set of six devices, and five were found to be vulnerable. Consequently, an intruder can use this exploit to disable a home security device and break into a house without the awareness of the owner. We carried out a responsible disclosure exercise with the manufacturers of the affected devices, but the response has been limited. This shows that IoT security is still not taken completely seriously and many threats are still undiscovered. Finally, we provide some recommendations on how to detect and prevent the threats posed by insecure IoT devices, which ironically include IoT home security kits

An Autoethnographic Miniature On The Tensions And Boundaries Of Researcher Experiences

Peer reviewe

Is Demonstrating the Concept of Multi-Use Too Soon for the North Sea?:Barriers and Opportunities from a Stakeholder Perspective

Multi-use (MU) has been promoted as a viable approach to the effective planning and mitigation of user-conflicts in the marine realm. Despite several research and pilot projects demonstrating the approach’s feasibility and benefits, commercially viable MU applications remain patchy and few. Further, MU is neither systematically applied nor purposively planned for even in the imminent event of incompatible and conflicting use of marine space. This paper seeks to identify barriers and opportunities for mainstreaming MU based on desktop study and iterative stakeholder consultation. The findings reveal that the MU concept was frequently framed as ‘co-location’ or ‘co-existence’ and aimed toward mitigating conflict among users. Practice was ahead of theory with little attention to synergistic and efficiency aspects. Barriers for MU application include shortcomings in legislation, sectoral thinking, and burdensome administrative procedures. The main opportunity lies in creating a conducive policy environment where MU risks and transaction costs become low and competitive, respectively. Solutions at the sea basin and national level, upon which further MU application can be anchored, are proposed

Modelling Smart Grid Technologies in Optimisation Problems for Electricity Grids

Copyright © 2023 by the authors. The decarbonisation of the electricity grid is expected to create new electricity flows. As a result, it may require that network planners make a significant amount of investments in the electricity grids over the coming decades so as to allow the accommodation of these new flows in a way that both the thermal and voltage network constraints are respected. These investments may include a portfolio of infrastructure assets consisting of traditional technologies and smart grid technologies. One associated key challenge is the presence of uncertainty around the location, the timing, and the amount of new demand or generation connections. This uncertainty unavoidably introduces risk into the investment decision-making process as it may lead to inefficient investments and inevitably give rise to excessive investment costs. Smart grid technologies have properties that enable them to be regarded as investment options, which can allow network planners to hedge against the aforementioned uncertainty. This paper focuses on key smart technologies by providing a critical literature review and presenting the latest mathematical modelling that describes their operation.This research received no external funding

Long-term expansion planning of the transmission network in India under multi-dimensional uncertainty

Considerable investment in India’s electricity system may be required in the coming decades in order to help accommodate the expected increase of renewables capacity as part of the country’s commitment to decarbonize its energy sector. In addition, electricity demand is geared to significantly increase due to the ongoing electrification of the transport sector, the growing population, and the improving economy. However, the multi-dimensional uncertainty surrounding these aspects gives rise to the prospect of stranded investments and underutilized network assets, rendering investment decision making challenging for network planners. In this work, a stochastic optimization model is applied to the transmission network in India to identify the optimal expansion strategy in the period from 2020 until 2060, considering conventional network reinforcements as well as energy storage investments. An advanced Nested Benders decomposition algorithm was used to overcome the complexity of the multistage stochastic optimization problem. The model additionally considers the uncertainty around the future investment cost of energy storage. The case study shows that deployment of energy storage is expected on a wide scale across India as it provides a range of benefits, including strategic investment flexibility and increased output from renewables, thereby reducing total expected system costs; this economic benefit of planning with energy storage under uncertainty is quantified as Option Value and is found to be in excess of GBP 12.9 bn. The key message of this work is that under potential high integration of wind and solar in India, there is significant economic benefit associated with the wide-scale deployment of storage in the system