arXiv subjects

Aristides Kiprakis

Publications and source records attributed to Aristides Kiprakis.

8 recordsLinked to original sources

arXiv2025

A model predictive control framework with customer-priority tiers for virtual power plant resilience during extreme weather: A UK heatwave case study

Due to changes in frequency and intensity of extreme weather events, such as heatwaves and storms, power systems around the globe are having to deal with increased imbalance between demand and supply and additional risk of loss of supply, calling for advanced control strategies that strengthen system resilience. This paper develops a Model Predictive Control (MPC) framework for coordination of Virtual Power Plants (VPPs) that manages photovoltaic (PV) systems, batteries, and loads before, during, and after extreme weather events. A multi-objective mixed-integer quadratically constrained program is solved to enforce customer-priority tiers, serving critical loads first, while minimizing operating cost and PV curtailment under network and device constraints. Simulations on the IEEE 33-bus distribution network with real UK heatwave data show that, under realistic forecast errors and modeling uncertainties, MPC improves resilience by 11-20% relative to traditional full-horizon optimization. These results indicate the practical viability of receding-horizon coordination for resilient, low-carbon VPP operation during extreme weather.

eess.SY↗

arXiv2023

The Value of Competing Energy Storage in Decarbonized Power Systems

As the world seeks to transition to a sustainable energy future, energy storage technologies are increasingly recognized as critical enablers. However, the macro-energy system assessment of energy storage has often focused on isolated storage technologies and neglected competition between them, thus leaving out which energy storage to prioritise. The article applies a systematic deployment analysis method that enables system-value evaluation in perfect competitive markets and demonstrates its application to 20 different energy storage technologies across 40 distinct scenarios for a representative future power system in Africa. Here, each storage solution is explored alone and in competition with others, examining specific total system costs, deployment configuration, and cost synergies between the storage technologies. The results demonstrate the significant benefits of optimizing energy storage with competition compared to without (+10% cost savings), and highlight the relevance of several energy storage technologies in different scenarios. This work provides insights into the role of energy storage in decarbonizing power systems and informs future research and policy decisions. There is no one-size-fits-all energy storage, but rather an ideal combination of multiple energy storage options designed and operated in symbiosis.

physics.soc-ph↗

arXiv2023

Feed-forward Disturbance Compensation for Station Keeping in Wave-dominated Environments

When deploying robots in shallow ocean waters, wave disturbances can be significant, highly dynamic and pose problems when operating near structures; this is a key limitation of current control strategies, restricting the range of conditions in which subsea vehicles can be deployed. To improve dynamic control and offer a higher level of robustness, this work proposes a Cascaded Proportional-Derivative (C-PD) with Feed-forward (FF) control scheme for disturbance mitigation, exploring the concept of explicitly using disturbance estimations to counteract state perturbations. Results demonstrate that the proposed controller is capable of higher performance in contrast to a standard C-PD controller, with an average reduction of ~48% witnessed across various sea states. Additional analysis also investigated performance when considering coarse estimations featuring inaccuracies; average improvements of ~17% demonstrate the effectiveness of the proposed strategy to handle these uncertainties. The proposal in this work shows promise for improved control without a drastic increase in required computing power; if coupled with sufficient sensors, state estimation techniques and prediction algorithms, utilising feed-forward compensating control actions offers a potential solution to improve vehicle control under wave-induced disturbances.

cs.RO↗

arXiv2022

PyPSA-Earth. A New Global Open Energy System Optimization Model Demonstrated in Africa

Macro-energy system modelling is used by decision-makers to steer the global energy transition toward an affordable, sustainable and reliable future. Closed-source models are the current standard for most policy and industry decisions. However, open models have proven to be competitive alternatives that promote science, robust technical analysis, collaboration and transparent policy decision-making. Yet, two issues slow the adoption: open models are often designed with limited geographic scope, hindering synergies from collaboration, or are based on low spatially resolved data, limiting their use. Here we introduce PyPSA-Earth, the first open-source global energy system model with data in high spatial and temporal resolution. It enables large-scale collaboration by providing a tool that can model the world energy system or any subset of it. This work is derived from the European PyPSA-Eur model using new data and functions. It is suitable for operational as well as combined generation, storage and transmission expansion studies. The model provides two main features: (1) customizable data extraction and preparation scripts with global coverage and (2) a PyPSA energy modelling framework integration. The data includes electricity demand, generation and medium to high-voltage networks from open sources, yet additional data can be further integrated. A broad range of clustering and grid meshing strategies help adapt the model to computational and practical needs. A data validation for the entire African continent is performed and the optimization features are tested with a 2060 net-zero planning study for Nigeria. The demonstration shows that the presented developments can build a highly detailed energy system model for energy planning studies to support policy and technical decision-making. We welcome joining forces to address the challenges of the energy transition together.

physics.soc-ph↗

arXiv2022

Beyond cost reduction: Improving the value of energy storage in electricity systems

An energy storage technology is valuable if it makes energy systems cheaper. Traditional ways to improve storage technologies are to reduce their costs; however, the cheapest energy storage is not always the most valuable in energy systems. Modern techno-economical evaluation methods try to address the cost and value situation but do not judge the competitiveness of multiple technologies simultaneously. This paper introduces the market potential method as a new complementary valuation method guiding innovation of multiple energy storage. The market potential method derives the value of technologies by examining common deployment signals from energy system model outputs in a structured way. We apply and compare this method to cost evaluation approaches in a renewables-based European power system model, covering diverse energy storage technologies. We find that characteristics of high-cost hydrogen storage can be more valuable than low-cost hydrogen storage. Additionally, we show that modifying the freedom of storage sizing and component interactions can make the energy system 10% cheaper and impact the value of technologies. The results suggest looking beyond the pure cost reduction paradigm and focus on developing technologies with suitable value approaches that can lead to cheaper electricity systems in future.

eess.SY↗

arXiv2022

Fast Mapping of Flexibility Regions at TSO-DSO Interfaces under Uncertainty

The gradual decommissioning of fossil fuel-driven power plants, that traditionally provide most operational flexibility in power systems, has led to more frequent grid stability issues. To compensate for the lack of flexible resources, Distributed Energy Resources (DERs) in distribution networks can be employed. To facilitate the use of DERs, the aggregated flexibility in a distribution grid is commonly represented on a $PQ$-plane displaying the feasible active and reactive power exchange with the upstream grid. This paper proposes a fast feasible operating region mapping mechanism that utilizes a linear power flow approximation in combination with linearized generator, current, and voltage constraints to construct a high-dimensional polyhedral feasible set of DER power injections. The obtained polytope is projected onto the $PQ$-plane using Fourier-Motzkin Elimination to represent the aggregate network flexibility. Additionally, uncertainty in DER generation is addressed using chance-constraints. Our analysis of a modified 33-bus IEEE test system demonstrates that the proposed method obtains more accurate approximations than former geometric methods and is ten times faster than the tested optimization-based method.

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arXiv2022

Reducing energy system model distortions from unintended storage cycling through variable costs

Energy model distortions may unknowingly appear and represent unrealistic and non-physical effects that can mislead optimal model decisions. A prominent misleading effect is unintended storage cycling that was observed in previous literature by simultaneous charging and discharging of the same storage in 12 of 18 energy models. Especially for popular net-zero energy model scenarios, unintended storage cycling can cause high distortions and, hence, urges for its removal. Methods to remove such misleading effects exist, but are not computational efficient and sometimes not effective such as MILP formulations. Other techniques are successful, but only if renewable energy target constraints exist. This paper explores how to eradicate unintended storage cycling for models without renewable target constraints by correctly setting variable costs of relevant system components. We find through 124 simulations that determining appropriate levels of variable costs depends on the solver accuracy used for the optimization. If set too loose, the solver prevents the removal of unintended storage cycling. We further find that reliable data for variable costs in energy modelling needs to be improved and provide a list of recommended model inputs as well as a minimum variable cost threshold that can significantly reduce the magnitude and likeliness of unintended storage cycling. Finally, our results suggest that variable cost additives may remove other known unintended energy cycling effects, such as unintended line cycling or sector cycling.

physics.soc-ph↗

arXiv2021

PyPSA meets Africa: Developing an open source electricity network model of the African continent

Electricity network modelling and grid simulations form a key enabling element for the integration of newer and cleaner technologies such as renewable energy generation and electric vehicles into the existing grid and energy system infrastructure. This paper reviews the models of the African electricity systems and highlights the gaps in the open model landscape. Using PyPSA (an open Power System Analysis package), the paper outlines the pathway to a fully open model and data to increase the transparency in the African electricity system planning. Optimisation and modelling can reveal viable pathways to a sustainable energy system, aiding strategic planning for upgrades and policy-making for accelerated integration of renewable energy generation and smart grid technologies such as battery storage in Africa.

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