Joakim Widén

Correlations Between Large-Scale Solar and Wind Power in a Future Scenario for Sweden

Future power systems are likely to include large amounts of variable power generation such as solar and wind power. As a variable output has to be balanced by the power systems reserves, it is important to study the time variability, coincidence, and correlations between power sources. The effect of output smoothing from dispersion of wind power plants is well established, but there is a need to study more renewables in combination. This study analyses large-scale solar and wind power in a future scenario for Sweden, using climatic data covering eight years with an hourly resolution. It is shown that solar and wind power are negatively correlated on all time scales, from hourly to annual, but that the correlation is strongest for monthly totals. Combining solar and wind power reduces total variations in terms of standard deviation, but hour-to-hour variability is always higher with a larger share of solar power.

Load matching and grid interaction of net zero energy buildings

Net Zero Energy Building” has become a prominent wording to describe the synergy of energy efficient building and renewable energy utilization to reach a balanced energy budget over a yearly cycle. Taking into account the energy exchange with a grid infrastructure overcomes the limitations of seasonal energy storage on-site. Even though the wording “Net Zero Energy Building” focuses on the annual energy balance, large differences may occur between solution sets in the amount of grid interaction needed to reach the goal. The paper reports on the analysis of example buildings concerning the load matching and grid interaction. Indices to describe both issues are proposed and foreseen as part of a harmonized definition framework. The work is part of subtask A of the IEA SHCP Task40/ECBCS Annex 52: “Towards Net Zero Energy Solar Buildings”.

Models of domestic occupancy, activities and energy use based on time-use data: deterministic and stochastic approaches with application to various building-related simulations

Time-use data (TUD) have a large potential for improving occupancy and load modelling and for introducing realistic behavioural patterns into various simulations. In this article, previously developed models of occupancy, activities and energy use based on TUD are extended and described in a general framework. Two extensions are studied: deterministic conversion of empirical TUD is extended into a complete thermal load model encompassing both occupancy and various end-uses and a Markov-chain approach for generating synthetic TUD sequences is extended to include a model for load management. Three examples of building-related applications are presented: simulation of indoor climate in a low-energy building, household electricity load management in response to time-differentiated electricity tariffs and simulations of load matching in a net zero energy building. The main conclusion is that the extended model framework can generate detailed and realistic behavioural patterns that allow diversity and correlations between end-uses to be taken into account.

Net load variability in Nordic countries with a highly or fully renewable power system

Increasing the share of intermittent renewable energy (IRE) resources such as solar, wind, wave and tidal energy in a power system poses a challenge in terms of increased net load variability. Full ...

Analysis of grid interaction indicators in net zero-energy buildings with sub-hourly collected data

This paper aimed to contribute to the discussion about the role of net zero-energy buildings (ZEBs) or nearly ZEBs in future energy systems, from the perspective of the resulting import/export interaction with the surrounding energy grid (commonly named grid interaction (GI)). This investigation analyses three buildings with measured data at sub-hourly time resolution. The goal of this paper was to quantify the effect of using high-resolution data (one or a few minutes) versus hourly resolution in the GI analysis of buildings with an on-site generation system. A limited set of quantitative GI indicators have been selected: the generation multiple, the dimensioning rate and the connection capacity credit. Additionally, this paper presents graphical representations describing in an intuitive way the yearly or daily variation of the indicators. Some general trends have been identified and the usefulness of the selected indicators is demonstrated. Findings show conclusively that sub-hourly analysis will give more accurate information. Differences between peak values measured with hourly and sub-hourly time resolution can be significant. If detailed GI analysis at the individual building level is required, one should consider going for detailed sub-hourly analysis.

A Bernoulli distribution model for plug-in electric vehicle charging based on time-use data for driving patterns

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 representing charging for each hour during weekday and weekend day. These distributions are then used as a basis for simulations of PEV charging patterns. Results regarding charging patterns for a number of different PEV parameters are shown along with a comparison with results from a different stochastic model for PEV charging. A convergence test for Monte Carlo simulations of the distributions is also provided. In addition to this we show that multiple PEV charging patterns are represented by Binomial distributions via convolution of Bernoulli distributions. Also the distribution for aggregate charging of many PEVs is shown to be normally distributed. Finally a few remarks regarding the applicability of the model are given along with a discussion on potential extensions.

Simulating occupancy in office buildings with non-homogeneous Markov chains for Demand Response analysis

Demand Response (DR) is a promising solution to deal with supply/demand imbalances in the power systems. To appreciate the availability of DR, it is important to include end user behavior in the analysis. In this paper, a model that can generate representative occupancy profiles in single office rooms is presented. The used method is non-homogeneous Markov chain modeling, along with exploratory data analysis of occupancy data, and an estimation of occupancy levels for different months and weekdays. The Markov chain model is calibrated with occupancy sensor data from 24 single rooms collected from an office building floor in Sweden. The simulation results have been statistically compared with a test data set consisting of occupancy data in 23 other rooms on the same floor. It was shown that the model could reproduce key occupancy properties of the test data.

Probabilistic Load Flow for Power Grids With High PV Penetrations Using Copula-Based Modeling of Spatially Correlated Solar Irradiance

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 a Gaussian copula to allow correlated sampling from the distributions for an arbitrary set of distributed PV systems. We show that the model realistically reproduces the spatially distributed clear-sky index over a set of sites, based on comparisons with irradiance sensor network data. We also demonstrate that the probability distributions for system parameters such as customer voltage, substation loading, and power losses, obtained from PLF simulations with the model, differ substantially from those of a nonspatial approach. The results show that spatial irradiance modeling needs to be incorporated in PLF simulations in order not to overestimate the grid impacts of PV systems.

Simple flexibility factor to facilitate the design of energy-flex-buildings

Buildings can facilitate a safe and uninterrupted transition from traditional production-respond to future demand-respond energy systems by delivering flexibility service to the system with smart control of their energy loads. Current methods used for building design and performance evaluation are focused on minimizing the building energy use and do not quantify the flexibility potential of the buildings. As the energy flexibility is of interest for the built and network environment, this paper presents a simple energy flexibility factor, which combines the needs of both and can be easily applied during the simulation/design and operation phases of a building.

PV system layout for optimized self-consumption

With decreasing subsidies for PV systems, increased self-consumption of PV electricity could improve the profitability of grid-connected residential PV systems. Self-consumption is in this paper de ...