On the Fairness of Centralised Decision-Making Strategies in multi-TSO Power Systems

In this paper, we consider an interconnected power system, where the different Transmission System Operators (TSOs) have agreed to transferring some of their competences to a Centralised Control Center (CCC). In such a context, a recurrent difficulty for the CCC is to define decision-making strategies which are fair enough to every TSO of the interconnected system. We address this multiobjective problem when the objective of every TSO can be represented by a real-valued function. We propose an algorithm to elect the solution that leads to the minimisation of the distance with the utopian minimum after having normalised the different objectives. We analyse the fairness of this solution in the sense of economics. We illustrate the approach with the IEEE 118 bus system partitioned in 3 areas having as local objective the minimisation of active power losses, the maximisation of reactive power reserves, or a combination of both criteria.multi-area power system, centralised control, multi-objective optimisation, fairness.

External Network Modeling for MVAr Scheduling in Multi Area Power Systems

International audienceMulti area power systems work most often with a poor inter-regional coordination about reactive power concerns. Transmission system operators typically do not possess a detailed knowledge about voltage profile across interconnected power systems. In this context, reactive power scheduling may be inefficient and inter-regional reactive power flows become a decisive issue. This inefficiency, associated with economic constraints and increasing stress on interconnection lines, may lead to conflicts, which could be partially avoided with a better scheduling strategy. In addition to inter-utility agreements, part of the solution could be to use appropriate external network modeling. Different modeling are thus presented in this paper and illustrated with an IEEE 118 bus system with 2 separately controlled regions, whose scheduling objective is to minimize active power losses. The regional scheduling process is described and the state of the interconnected power system is compared with a global optimization. Finally, the influence of the external network modeling parameters and the accuracy of their forecast is commented

On the Environmental and Economic Impact of Utility-Scale Renewable Energy Deployment

As per the U.S Energy Information Administration’s latest inventory of electricity generators, renewable energy, most notably solar and wind, will account for roughly 70% of nearly 40 gigawatts of new electricity generating capacity to start commercial operation in 2021. The year 2021 will also set a record in the deployment of utility-scale solar capacity by adding 15.4 gigawatts of capacity to the grid, which surpasses the 12 gigawatts increase in 2020. The rapid increase of renewable energy is expected to significantly decrease emissions of greenhouse gases and change the load profile in the power grid by suppressing production from conventional generators. This paper aims to propose a framework to study the impact of utility-scale solar PV deployment on the generation resource allocation and investigate the economics and policy of electricity generation and carbon emissions. The investigation is carried on the generation resource pool of the southeast region of the U.S augmented by a substantial amount of utility-scale solar generation

On the Fairness of Centralised Decision-Making Strategies in multi-TSO Power Systems

International audienceIn this paper, we consider an interconnected power system, where the different Transmission System Operators (TSOs) have agreed to transferring some of their competences to a Centralised Control Center (CCC). In such a context, a recurrent difficulty for the CCC is to define decision-making strategies which are fair enough to every TSO of the interconnected system. We address this multiobjective problem when the objective of every TSO can be represented by a real-valued function. We propose an algorithm to elect the solution that leads to the minimisation of the distance with the utopian minimum after having normalised the different objectives. We analyse the fairness of this solution in the sense of economics. We illustrate the approach with the IEEE 118 bus system partitioned in 3 areas having as local objective the minimisation of active power losses, the maximisation of reactive power reserves, or a combination of both criteria

Experimental investigation of the mooring system of a wave energy converter in operating and extreme wave conditions

A proper design of the mooring systems for Wave Energy Converters (WECs) requires an accurate investigation of both operating and extreme wave conditions. A careful analysis of these systems is required to design a mooring configuration that ensures station keeping, reliability, maintainability, and low costs, without affecting the WEC dynamics. In this context, an experimental campaign on a 1:20 scaled prototype of the ISWEC (Inertial Sea Wave Energy Converter), focusing on the influence of the mooring layout on loads in extreme wave conditions, is presented and discussed. Two mooring configurations composed of multiple slack catenaries with sub-surface buoys, with or without clump-weights, have been designed and investigated experimentally. Tests in regular, irregular, and extreme waves for a moored model of the ISWEC device have been performed at the University of Naples Federico II. The aim is to identify a mooring solution that could guarantee both correct operation of the device and load carrying in extreme sea conditions. Pitch motion and loads in the rotational joint have been considered as indicators of the device hydrodynamic behavior and mooring configuration impact on the WEC

On Accelerated Aging of Mechanical Assets in Distribution Systems with Renewable Generation

The integration challenges associated with the widespread adoption of the photovoltaic generation can be divided into operational and the maintenance issues. Work done in recent years has addressed issues like voltage rise and unbalance. Less attention was directed to the maintenance challenges like accelerated aging of mechanically controlled voltage support assets under rapidly changing conditions. In particular, there is need for analysis on the mechanism of accelerated wear and tear of devices such as on-load tap changers and capacitor banks exposed to rapid voltage fluctuations. Such an analysis relies on development of lifetime models of switching devices to study the impact of increased stress, whether electrical or mechanical, on operational life. This article focuses on developing such models and proposes the framework to study the impact of non-scheduled distributed generation on aging of mechanically-switched devices commonly used in distribution feeders

PyProD: A Machine Learning-Friendly Platform for Protection Analytics in Distribution Systems

This paper introduces PyProD, a Python-based machine learning (ML)-compatible test-bed for evaluating the efficacy of protection schemes in electric distribution grids. This testbed is designed to bridge the gap between conventional power distribution grid analysis and growing capability of ML-based decision making algorithms, in particular in the context of protection system design and configuration. PyProD is shown to be capable of facilitating efficient design and evaluation of ML-based decision making algorithms for protection devices in the future electric distribution grid, in which many distributed energy resources and pro-sumers permeate the system

Capacity usage determination of a Capacitor-less D-STATCOM considering Power System Uncertainties

The increasing adoption of distributed energy resources (DERs), particularly solar generation and the use of unconventional loads such as plug-in electric vehicles (PHEVs), has a profound impact on the planning and operation of electric distribution systems. In particular, PHEV charging introduces stochastic peaks in energy consumption, while solar generation is fraught with variability during intermittent clouds. The stochastic nature of such DERs renders the operation of mechanical assets such as on-load tap changers and switched capacitor banks ineffective. A possible solution to mitigate the undesirable effects of DERs is using solid-state-based devices such as a distribution static synchronous compensator (D-STATCOM). This paper examines the capacity usage of a capacitor-less D-STATCOM in distribution systems while considering the uncertainties associated with using the aforementioned DERs. We propose a Monte Carlo simulation to study the capacity usage problem with DER inputs sampled from the proposed underlying distributions

Impact of Short-Term Variations in the Generation Output of Geographically Dispersed PV Systems

When viewed in hourly intervals, a solar photovoltaic (PV) system appears to have a more stable output than usual. However, there are short-term rapid variations in its generation output that result from transient cloudiness and weather disturbances in the atmosphere. By using Monte Carlo simulations applied to a Markov model, this study demonstrates the short-term intermittency of the transient weather conditions and estimates the generation of geographically dispersed PV systems with a capacity of ten percent of peak demand of a statewide grid in one-minute intervals. This study found that geographically distributed PV systems evaluated in one-minute intervals could cope with peaks of a statewide power grid because of the smoothing effect caused by the geographical spread. The purpose of the exercise is to create a framework for integration and optimization of multiple generation sources in order to meet the uncertainty of the fast changing PV output under certain weather conditions.