Martin Densing

• Doctor of Philosophy
• Researcher at Paul Scherrer Institute

We present a scenario generation method for representative days of wind and solar power availability for use in energy-system models. The method uses principal component analysis (PCA) such that the correlations between solar and wind can be captured. PCA is applied to daily time series of hourly profiles of regional solar and wind power availabili...

In large-scale energy market models, the price-demand relationship is usually represented by a linear function. In this paper, nonlinear demand functions are fitted to electricity market bid data; in particular, exponential and polynomial (cubic) functions are estimated from EPEX day-ahead data (i.e. Central Western European market area). The corre...

The recent signals in the energy sector indicate a major transformation taking shape in the energy sector in the decades to come. The potential trends are highlighted in three scenarios published by the World Energy Council in September 2019 and further presented in detail and in a long-term perspective in this article. Compared to developments of...

Electricity markets in Europe become increasingly interconnected due to new grid connections and market coupling regulations. This paper examines the interdependencies between the Swiss electricity market and those of neighbouring countries. The Swiss market serves as a good example for a smaller electricity market which is increasingly affected by...

Weassess the impact on the European electricity market of the European Union “Clean energy for all Europeans” package, which implements the EU Nationally Determined Contribution in Paris COP 21. We focus on the year 2030,which is the yearwith defined climate targets. For the assessment, weemploy a game-theoretic framework of the wholesale electrici...

A stored commodity is sold under a capacity constraint depending on an exogenous random market price, and, alternatively, a service contract can be provided in which the selling amount must be held constant over time independent of price changes. The seller of the commodity is assumed to optimize the trade-off between the received payment for the p...

Transnational municipal networks have led to an increase in the adoption of local energy planning and climate strategies in recent decades. As such, methods are needed to assess local energy systems on a broad scale. This study demonstrates one such approach for Switzerland. Clustering techniques are applied to multidimensional municipal data sets...

The European energy system is undergoing, and will continue to in the future, a transition towards a more sustainable energy system. An important part of this will be the deployment of smart energy solutions in the household sector, including smart meters, controls, appliances, and their integration in home networks. This study is in support of the...

In the medium to long term, stationary fuel cells and hydrogen (FCH) technologies and applications are considered as potentially significant elements in energy systems with a high share of variable renewable energies. Besides the gain in flexibility for the energy system, FCH technologies are associated with the mitigation of greenhouse gas emissio...

With over 50% of the world's population residing in cities, urban areas have the potential to contribute significantly to global CO2 emissions reductions through careful urban energy systems planning and community participation. However, urban policymakers must operate within the constraints imposed by national energy policies. This study aims to u...

This study presents a framework to quantitatively evaluate decentralized generation and storage technology (DGST) performance and policy impacts in a rural setting. The role of DGSTs in the future energy systems planning of a rural agglomeration in Switzerland is examined using a cost optimization modeling approach. Heat and electricity demand for...

We present a meta-analysis of long-term energy-system scenario studies. The meta-analysis comprises a qualitative taxonomy of modeling approaches and a quantitative decomposition of scenario results across heterogenous studies. The analysis is exemplified by technology-detailed scenario studies of the Swiss electricity system. In the decomposition...

Approximately 2 out of 10 people in the world still live without access to electricity. The UN “Sustainable Energy to All – SE4All” initiative aims at eradicating this electricity access deficit by 2030. To estimate the financial effort required to achieve this target we analyse two long-term scenarios developed by the Paul Scherrer Institute and t...

The energy sector of Sub-Saharan Africa today faces major challenges with total installed electricity generation capacity less than 100 GW and 590 million people lacking access to electricity. We analyse two long-term explorative scenarios, developed together with the World Energy Council, to assess the policy and technology mixes required to achie...

We discuss multiperiod stochastic programming formulations of time-consistent extensions of average value-at-risk (AVaR); AVaR measures the risk of a random financial value. Multiperiod risk measures that are recursively defined over time are known to be time consistent. For a multiperiod extension of AVaR for stochastic value processes, we reformu...

After a review of hydropower optimization models, we focus on price-driven hydropower dispatch models under uncertainty of the electricity price. We present two modeling approaches for pumped-storage plants. In the first model, the water level is constrained in expectation. We discuss the marginal price of water, which is obtained analytically, and...

We consider price-driven dispatch planning under price uncertainty: A storable commodity is optimally sold and purchased over time. First, we consider models where the storage level is constrained in expectation. The dual of the corresponding optimization problem is related to the newsvendor problem. Exact solutions of bang-bang type are given. The...

We discuss the functional principal component analysis (FPCA) of the occupation times of the Ornstein–Uhlenbeck process. For the eigenvalue problem of the covariance operator of the occupation times we derive the corresponding integral equation in the large time limit and we solve numerically for the principal components. The formulation applies th...

In the study, we analyse scenarios of car technology deployment and the global energy system using the Global Multi-regional MARKAL (GMM) cost optimisation model. We consider some of the conditions under which new drivetrain technologies, particularly battery electric vehicles (BEVs), may be more cost competitive under different hypothetical states...

Coherent risk measures play an important role in building and solving optimization models for decision problems under uncertainty. We consider an extension to multiple time periods, where a risk-adjusted value for a stochastic process is recursively defined over the time steps, which ensures time consistency. A prominent example of a single-period...