Joakim Munkhammar

Joakim Munkhammar
Uppsala University | UU · Department of Civil and Industrial Engineering

Doctor of Philosophy

About

102
Publications
64,095
Reads
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2,150
Citations
Introduction
My research is focused on developing mathematical models and forecasting methods for solar irradiance variability, electric vehicle charging, distributed photovoltaic power generation and electricity use. I am also occasionally involved in various applied mathematics projects.
Additional affiliations
September 2018 - present
Uppsala University
Position
  • Professor (Associate)
Description
  • Mathematical modeling and machine learning methodology applied to distributed photovoltaic power generation and electric vehicle charging.
November 2017 - September 2018
Uppsala University
Position
  • Professor (Assistant)
November 2015 - November 2017
Uppsala University
Position
  • PostDoc Position

Publications

Publications (102)
Article
Full-text available
We suggest a procedure for estimating Nth degree polynomial approximations to unknown (or known) probability density functions (PDFs) based on N statistical moments from each distribution. The procedure is based on the method of moments and is setup algorithmically to aid applicability and to ensure rigor in use. In order to show applicability, pol...
Article
Full-text available
This paper presents an N-state Markov-chain mixture distribution approach to model the clear-sky index. The model is based on dividing the clear-sky index data into bins of magnitude and determining probabilities for transitions between bins. These transition probabilities are then used to define a Markov-chain, which in turn is connected to a mixt...
Article
Full-text available
This study presents a spatiotemporal Markov-chain mixture distribution model of the clear-sky index for an arbitrary number of locations, and is particularly suited for simulations of small-scale spatial networks with a span of 10 km or less. The model is statistical, but in practice data-driven and based on clear-sky index input from an arbitrary...
Article
Full-text available
This study presents a Markov-chain mixture (MCM) distribution model for forecasting normalized solar irradiance, the clear-sky index. The model is presented in general, but applied to, and tested on, minute resolution clear-sky index data for the two different climatic regions of Norrköping, Sweden, and Hawaii, USA. Model robustness is evaluated ba...
Article
Full-text available
This study utilizes the Markov-chain mixture distribution model (MCM) for very short term load forecasting of residential electricity consumption. The model is used to forecast one step ahead half hour resolution residential electricity consumption data from Australia. The results are compared with Quantile Regression (QR) and Persistence Ensemble...
Article
Full-text available
Hidden state models are among the most widely used and efficient schemes for solar irradiance modeling in general and forecasting in particular. However, the complexity of such models – in terms of the number of states – is usually needed to be specified a priori. For solar irradiance data this assumption is very difficult to justify. In this paper...
Article
The use of electric vehicles (EVs) has been on the rise during the past decade, and the number is expected to rapidly increase in the future. At aggregated level, the large EV charging loads, if not well regulated, will cause great stress on the existing grid infrastructures. On the other hand, considered as a resource-efficient and cost-effective...
Article
Simplification of building energy models is one of the most common approaches for efficiently estimating the energy performance of buildings over a whole city. In city-scale models, the abstraction of a building into an information model and the division of the model into representative thermal zones cannot be building-specific but must be generic...
Article
Full-text available
The integration of photovoltaic (PV) systems and electric vehicles (EVs) in the built environment, including at workplaces, has increased significantly in the recent decade and has posed new technical challenges for the power system, such as increased peak loads and component overloading. Several studies show that improved matching between PV gener...
Article
This study uses the N-state Markov-chain mixture distribution model and the multiple-component N-state Markov-chain mixture distribution model to simulate global, beam, and diffuse horizontal clear-sky index. The models are data-driven such that when trained on single or multiple clear-sky index time-series, the models generate arbitrarily long syn...
Conference Paper
Motivated by the need for more sustainable energy , power generation is increasingly shifted to small scale distributed generation, which enables residential customers to produce photovoltaic electricity and participate in the energy generation mix. Hence, insight into the expected spatial spread of new residential photovoltaic systems is of great...
Article
The interest for co-located wind and solar photovoltaic (PV) parks, also known as hybrid power parks (HPPs), is increasing both in industry and in the scientific community. Co-locating wind and PV can lead to synergies in power production, infrastructure, and land usage, which may lower the overall plant cost compared to single technology systems....
Article
Full-text available
Several studies have presented electric vehicle smart charging schemes to increase the temporal matching between photovoltaic generation and electric vehicle charging, including a smart charging scheme with an objective to minimize the net-load variance. This method has proved, through simulations, that the self consumption could be increased, but...
Chapter
DESCRIPTION This chapter gives an overview of established state-of-the-art mathematical approaches for generating synthetic solar irradiance data. The most important scientific studies from the last half-century are identified and discussed, and the general development of the field is characterized. The mathematical methods used for modeling both d...
Chapter
DESCRIPTION This chapter starts by reflecting on the learning outcomes from the book. The rest of the chapter is dedicated to the possible next steps for the field of synthetic solar irradiance. Previous applications of synthetic solar irradiance are discussed highlighting areas for improvement. Future potential applications are suggested, as well...
Article
Full-text available
Photovoltaic (PV) systems and electric vehicles (EVs) integrated in local distribution systems are considered to be two of the keys to a sustainable future built environment. However, large-scale integration of PV generation and EV charging loads poses technical challenges for the distribution grid. Each grid has a specific hosting capacity limitin...
Article
Full-text available
Scenario-based stochastic model predictive control traditionally considers the optimal strategy to be the expectation of the optimal strategies across all scenarios. However, while the stochastic problem involving uncertainties can be substantiated by a large number of scenarios, the expectation of the respective optimal control strategies derived...
Article
We show that the Riemann zeta function for $\mathrm{Re}(s)>1$ can be represented as a sum of geometric series $\zeta(s) = 1 + \sum_{n=1}^\infty 1/(/\alpha_n^s - 1)$, where $\alpha_n$ is the $n$:th not perfect power (2,3,5,6,7,...). This result is then used to compute the sum of a generalised Euler-Goldbach series_{n=1}^\infty 1/(w_n^2-1), where $\b...
Research
Original article: Estimating the spatiotemporal potential of self-consuming photovoltaic energy to charge electric vehicles in rural and urban Nordic areas, Journal of Renewable and Sustainable Energy 12, 046301 (2020); https://doi.org/10.1063/5.0006893
Article
The currently increasing penetration of photovoltaic (PV) generation and electric vehicle (EV) charging in electricity distribution grids leads to higher system uncertainties. This makes it vital for load flow analyses to use probabilistic methods that take into account the uncertainty in both load and generation. Such probabilistic load flow (PLF)...
Article
The present paper echos a recent data article, “A comprehensive dataset for the accelerated development and benchmarking of solar forecasting methods” [J. Renewable Sustainable Energy 11, 036102 (2019)]. The carefully composed dataset by Pedro, Larson, and Coimbra (PLC) presents a rare opportunity for solar forecasters to develop transparent and re...
Article
Full-text available
The penetration of electric vehicles (EVs) and photovoltaic (PV) systems has increased globally in the last decade. For planning purposes, the spatiotemporal variability of distributed PV power generation and EV charging needs to be quantified for urban and rural areas. This study introduces a state-of-the-art, open and generally applicable model f...
Article
Full-text available
The integration of photovoltaic (PV) and electric vehicle (EV) charging in residential buildings has increased in recent years. At high latitudes, both pose new challenges to the residential power systems due to the negative correlation between household load and PV power production and the increase in household peak load by EV charging. EV smart c...
Article
Photovoltaics (PV) and electric vehicles (EVs) are two emerging technologies often considered as cornerstones in the energy and transportation systems of future sustainable cities. They both have to be integrated into the power systems and be operated together with already existing loads and generators and, often, into buildings, where they potenti...
Article
Short-term probabilistic solar forecasts are an important tool in decision-making processes in which uncertainty plays a non-negligible role. Purely statistical models that produce temporal or spatiotemporal probabilistic solar forecasts are generally trained individually, and the combined forecasts therefore lack the temporal or spatiotemporal cor...
Article
An error in integration was detected in the simulation code estimating the CRPS, where generated forecast results of the CRPS for in particular PeEn forecasts were overestimated (on average 44 percent). The CRPS resulting from the MCM model forecasts were also overestimated, although to a much lesser degree (on average 0.5 percent), the results of...
Conference Paper
Full-text available
This paper presents an electric vehicle (EV) smart charging scheme at residential buildings based on installed photovoltaic (PV) output and household electricity consumption. The proposed EV charging scheme is designed to determine the optimal EV charging schedules for the purpose of minimizing the load-variance or flattening the load profile. When...
Conference Paper
Electric vehicles (EVs) and photovoltaics (PV) are swiftly being adopted to improve sustainability in both the transportation and the electricity sectors. Residential buildings might benefit from self-consuming the locally produced PV electricity to charge the EVs of the residents. However, the temporal mismatch between midday solar power productio...
Article
Full-text available
[This corrects the article DOI: 10.1371/journal.pone.0174573.].
Article
Full-text available
Clear-sky index (CSI) generative models are of paramount importance in, e.g., studying the integration of solar power in the electricity grid. Several models have recently been proposed with methodologies that are related to hidden Markov models (HMMs). In this paper, we formally employ HMMs, with Gaussian distributions, to generate CSI time-series...
Conference Paper
This paper presents a novel method for downscaling hourly solar irradiance data to higher resolution in both space and time. The method is based on transforming any point in two-dimensional space and time to a position in a propagating cloud field, the internal spatial variability of which is modelled with a Gaussian copula. By relating the mean ho...
Conference Paper
Two probabilistic forecasting models for the clear-sky index, based on the Markov-chain mixture distribution (MCM) and copula clear-sky index generators, are presented and evaluated. In terms of performance, these models are compared with two benchmark models: a Quantile Regression (QR) model and the Persistence Ensemble (PeEn). The models are test...
Book
Full-text available
One of the challenges in solar engineering is that the availability of the solar resource varies with time and location. An important engineering task is to design solar energy systems that are able to collect as much solar radiation as possible under these constraints. This book introduces the basic properties of solar radiation that are required...
Article
Full-text available
Renewable distributed generation and electric vehicles (EVs) are two important components in the transition to a more sustainable society. However, both pose new challenges to the power system due to the intermittent generation and EV charging load. In this case study, a power system consisting of a low- and medium-voltage rural and urban distribut...
Article
Full-text available
In the recent years, the number of electric vehicles (EVs) on the road have been rapidly increasing. Charging this increasing number of EVs is expected to have an impact on the electricity grid especially if high charging powers and opportunistic charging are used. Several models have been proposed to quantify this impact. Multiple papers have obse...
Article
Full-text available
In order to contribute to the reduction of greenhouse gas emissions, electric vehicles (EVs) should be charged using electricity from renewable energy sources. This paper describes a study of photovoltaics (PV) utilization for EV charging in two Scandinavian cities: Tromsø in Norway and Uppsala in Sweden, with the objective to evaluate self-suffici...
Conference Paper
Full-text available
This study presents a model for estimating building-applied photovoltaic (PV) energy yield and electric vehicle (EV) charging temporally over time and spatially on a city scale. The model enables transient assessment of the synergy between EV and PV, thus is called the EV-PV Synergy Model. Spatio-temporal data on solar irradiance is used in combina...
Conference Paper
This paper evaluates the impacts of electric vehicles' (EVs') smart charging algorithms on reducing the peak of the total load of households. Two smart charging schemes are proposed. The first scheme-postponed charging-is defined as reducing the charging power if the total load exceeds the fuse size, thereby sometimes postponing the charging. The s...
Article
Full-text available
This paper presents a Markov-chain probability distribution mixture approach to the clear-sky index (CSI). The main assumption is that the temporal variability of the state of clear and the state of cloudy can be described by a two-state Markov-chain, and the variability within each state can be approximated by a probability distribution, unique fo...
Article
Full-text available
This paper presents a study into the effect of aggregation of customers and an increasing share of photovoltaic (PV) power in the net load on prediction intervals (PIs) of probabilistic forecasting methods applied to dis- tribution grid customers during winter and spring. These seasons are shown to represent challenging cases due to the increased v...
Article
Abstract Probabilistic load forecasting (PLF) is of important value to grid operators, retail companies, demand response aggregators, customers, and electricity market bidders. Gaussian processes (GPs) appear to be one of the promising methods for providing probabilistic forecasts. In this paper, the log-normal process (LP) is newly introduced and...
Article
Full-text available
Photovoltaics (PV) and electric vehicles (EVs) are promising technologies for increasing energy efficiency and the share of renewable energy sources in power and transport systems. As regards the deployment, use and system integration of these technologies, spatio-temporal modeling of PV power production and EV charging is of importance for several...
Article
Full-text available
This paper presents a study into the utilization of Gaussian Processes (GPs) for probabilistic forecasting of residential electricity consumption, photovoltaic (PV) power generation and net demand of a single household. The covariance function that encodes prior belief on the general shape of the time series plays a vital role in the performance of...
Article
An important factor in grid integration of solar power is the so-called dispersion-smoothing effect, i.e., that differences in cloudiness over dispersed systems make the aggregate output less variable. This effect has been studied for irradiance step-changes on different time horizons, but not so much for instantaneous irradiance. In this paper, an...
Conference Paper
In order to mitigate the potential harmful effects of global warming reduced energy use, increased share of renewable energy, and decreased use of fossil fuels are essential measures. EU policy obliges the member states to reduce building energy use, increase renewable energy utilization, and encourage combined heat and power production. Technologi...
Conference Paper
With the rapid increase in the penetration level of electric vehicles (EVs), accurate modelling of the impacts of EVs on the electricity grid in cities is of important value to grid operators. In this paper, data from five charging stations (CSs) in Uppsala, Sweden are analysed. Then a spatial model is developed and validated using the previously a...
Conference Paper
Full-text available
The smoothing effect on the aggregate output of photovoltaic (PV) systems from spatial distribution and aggregation of electricity demand for deterministic forecasts are well-known. However, deterministic forecasting is limited in the sense that the inherent uncertainty is neglected. This paper therefore presents a study into the effect of aggregat...
Conference Paper
Full-text available
Renewable distributed generation and electric vehicles (EVs) are two important components in the transitions to a more sustainable society. However, both distributed generation and EV charging pose new challenges to the power system due to intermittent generation and high-power EV charging. In this case study, a power system consisting of a low-and...
Conference Paper
Full-text available
With the rapid increase in the penetration level of electric vehicles (EVs), accurate modelling of the impacts of EVs on the electricity grid in cities is of important value to grid operators. In this paper, data from five charging stations (CSs) in Uppsala, Sweden are analysed. Then a spatial model is developed and validated using the previously a...
Article
This paper presents and applies an improved model for the instantaneous power generation from distributed photovoltaic (PV) systems intended for probabilistic load flow (PLF) simulations. The model combines a probability distribution model for the instantaneous solar irradiance at individual sites with an improved spatial correlation model and uses...
Conference Paper
This paper investigates the electricity use of completely autonomous electric vehicle (AEV) fleets in cities. A set of principles for autonomous vehicle fleets in cities is defined, mathematical relations for optimal utility conditions are derived and a Monte Carlo simulation model is developed based on the assumption of central charging. Results s...
Conference Paper
This paper aims to investigate the relative difference in accuracy between forecasting net demand, i.e., electricity con- sumption less the photovoltaic (PV) power production, directly and indirectly, where the latter implies forecasting consumption and production separately before subtraction. Depending on the variability and penetration of PV pow...
Article
Full-text available
This study presents a method for using copulas to model the temporal variability of the clear-sky index, which in turn can be used to produce realistic time-series of photovoltaic power generation. The method utilizes the autocorrelation function of a clear-sky index time-series, and based on that a correlation matrix is set up for the dependency b...
Conference Paper
Full-text available
This study presents a method for using copulas to model the temporal variability of the clear-sky index. The method utilizes the autocorrelation function and correlated outputs for N time-steps are obtained. Results from the copula model are compared with the original data set and a distribution model based on random clear-sky index data in terms o...
Article
Full-text available
tAccurate forecasting simultaneously becomes more important and more challenging due to the increasing penetration of photovoltaic (PV) systems in the built environment on the one hand, and the increasing stochastic nature of electricity consumption, e.g., through electric vehicles (EVs), on the other hand. Until recently, research has mainly focus...
Data
Data set on household electricity use used in this paper. (TXT)
Conference Paper
Access to public charging stations is an important step towards electrification of the transportation sector. The number of electric vehicles (EVs) on the roads increases rapidly. This growth will have a significant impact on the electricity grid via EV charging. Accurate prediction of these impacts is essential to plan new charging stations and to...
Conference Paper
Access to public charging stations is an important step towards electrification of the transportation sector. The number of electric vehicles (EVs) on the roads increases rapidly. This growth will have a significant impact on the electricity grid via EV charging. Accurate prediction of these impacts is essential to plan new charging stations and to...
Article
This paper presents a method for generating correlated instantaneous solar irradiance data for an arbitrary set of spatially dispersed locations. Based on the empirical clear-sky index distribution for one location and the cross-correlation between clear-sky index data at all location pairs, a copula is used to represent the dependence between loca...
Conference Paper
Full-text available
Estimating solar irradiance over several locations in a spatial network is of interest for a wide variety of applications, in particular for simulations of distribution grid with high photovoltaic (PV) penetration. This paper presents a method for estimating the clear-sky index for N locations in any spatial network of locations. The model is based...
Article
Increasing the self-consumption of photovoltaic (PV) power is an important aspect to integrate more PV power in the power system. The profit for the PV system owner can increase and the stress on the power grid can be reduced. Previous research in the field has focused on either self-consumption of PV power in individual buildings or PV power curta...
Article
Estimating solar irradiance, in particular its variability, on Earth's surface is paramount for solar engineering and for improving the utilization of solar energy. This paper presents a novel approach to statistical modeling of instantaneous solar irradiance by using a multivariate probability distribution-a copula-to describe the dependency betwe...
Chapter
Based on recent results from general relativistic statistical mechanics and black hole information transfer limits a space-time entropy-action equivalence is proposed as a generalization of the holographic principle. With this conjecture, the action principle can be replaced by the second law of thermodynamics, and for the Einstein-Hilbert action t...
Conference Paper
Improved probability distribution models for power generation are useful e.g. forprobabilistic power flow simulations. This paper presents a distribution modelfor photovoltaic (PV) power generation based on the clear-sky index.With the use of minute-resolution data on globalhorizontal irradiation (GHI) we fit unimodal normal,bimodal normal and trim...
Conference Paper
Full-text available
Grid-connected photovoltaics (PV) has been dependent on different supporting schemes to be a competitive alternative to conventional electricity generation. Selling prices of PV power production are now lower than buying prices in several countries, which makes it more profitable to match periods of high generation with household consumption. In si...
Article
In this paper we develop a probability distribution model combining household power consumption, electric vehicle (EV) home-charging and photovoltaic (PV) power production. The model is set up using a convolution approach to merge three separate existing probability distribution models for household electricity use, EV home-charging and PV power pr...
Thesis
Technological improvements along with falling prices on photovoltaic (PV) panels and electric vehicles (EVs) suggest that they might become more common in the future. The introduction of distributed PV power production and EV charging has a considerable impact on the power system, in particular at the end-user in the electricity grid. In this PhD...
Conference Paper
This paper presents a Bernoulli distribution model for plug-in electric vehicle (PEV) charging based on high resolution activity data for Swedish driving patterns. Based on the activity 'driving vehicle' from a time diary study a Monte Carlo simulation is made of PEV state of charge which is then condensed down to Bernoulli distributions representi...
Article
This paper presents a high-resolution bottom-up model of electricity use in an average household based on fit to probability distributions of a comprehensive high-resolution household electricity use data set for detached houses in Sweden. The distributions used in this paper are the Weibull distribution and the Log-Normal distribution. These fitte...