17 research outputs found
Energy storage design and integration in power systems by system-value optimization
Energy storage can play a crucial role in decarbonising power systems by balancing
power and energy in time. Wider power system benefits that arise from these
balancing technologies include lower grid expansion, renewable curtailment, and
average electricity costs. However, with the proliferation of new energy storage
technologies, it becomes increasingly difficult to identify which technologies are
economically viable and how to design and integrate them effectively.
Using large-scale energy system models in Europe, the dissertation shows that solely
relying on Levelized Cost of Storage (LCOS) metrics for technology assessments can
mislead and that traditional system-value methods raise important questions about
how to assess multiple energy storage technologies. Further, the work introduces a
new complementary system-value assessment method called the market-potential
method, which provides a systematic deployment analysis for assessing multiple
storage technologies under competition. However, integrating energy storage in
system models can lead to the unintended storage cycling effect, which occurs in
approximately two-thirds of models and significantly distorts results. The thesis
finds that traditional approaches to deal with the issue, such as multi-stage optimization
or mixed integer linear programming approaches, are either ineffective
or computationally inefficient. A new approach is suggested that only requires
appropriate model parameterization with variable costs while keeping the model
convex to reduce the risk of misleading results.
In addition, to enable energy storage assessments and energy system research around
the world, the thesis extended the geographical scope of an existing European opensource
model to global coverage. The new build energy system model âPyPSA-Earthâ
is thereby demonstrated and validated in Africa. Using PyPSA-Earth, the thesis
assesses for the first time the system value of 20 energy storage technologies across
multiple scenarios in a representative future power system in Africa. The results offer
insights into approaches for assessing multiple energy storage technologies under
competition in large-scale energy system models. In particular, the dissertation
addresses extreme cost uncertainty through a comprehensive scenario tree and finds
that, apart from lithium and hydrogen, only seven energy storage are optimizationrelevant
technologies. The work also discovers that a heterogeneous storage design
can increase power system benefits and that some energy storage are more important
than others. Finally, in contrast to traditional methods that only consider single
energy storage, the thesis finds that optimizing multiple energy storage options
tends to significantly reduce total system costs by up to 29%.
The presented research findings have the potential to inform decision-making processes
for the sizing, integration, and deployment of energy storage systems in
decarbonized power systems, contributing to a paradigm shift in scientific methodology
and advancing efforts towards a sustainable future
Enabling Competing Energy Storage Technologies: Towards a Carbon-Neutral Power System
Assessment of energy storage technologies at a macro-scale for grid integration, has often focused on singular technologies and neglected competition between them, thus leaving out of the optimization the decision of which energy storage to prioritize. We present a systematic deployment analysis method that enables system-value evaluation in perfect competitive markets and demonstrate its application to 20 different energy storage technologies across 40 distinct scenarios for a representative future power system in Africa. Our 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 various scenarios. This work provides insights into the role of multi-technology energy storage in carbon-neutral power systems and informs future research and policy decisions
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.Comment: 15 pages, 10 figure
Open source modeling for planing sustainable power development in resource-rich economies: case study for Kazakhstan
Power sector decarbonization is currently seen as a necessary condition of sustainable development in the modern world. options of resources-rich economies. Energy modeling is an effective measure to elaborate long-term decarbonisation policies. However, energy modeling evidence available for resources-rich economies remain up to the date limited, especially in part of realistic representation of the power system operation. We apply open code and open data approach to fill this gap considering a case study for Kazakhstan power system. The modeling input datasets have been validated against independent data sources with a satisfactory result. The simulation outputs are plausible both in terms reproducing the main features of the âpragmaticâ scenario and in providing useful insights for the implementation of net-zero pathways. Renewable energy sources have been found to be economically viable even under the considered âpragmaticâ scenario with quite conservative assumptions. Existing coal generation has been shown to dominate the investments costs hampering implementation of renewable power. A role of the power interconnection has been demonstrated for an economically optimal generation mix and a level of marginal electricity costs across the country. The results are intended to support energy transition implementation in the resources-rich economies under realistic technological assumptions
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
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.Comment: 36 pages, 14 figures, 3 table
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