Digitalization of the power business: How to make this work?

As a result of the digitalization of the power business in Norway and Europa, a lot of new possibilities and challenges arise. In 2014 an expert committee one outlined a proposal for the future grid company structure in Norway (Reiten, 2014). In addition, new technologies are being implemented in the system. Wind power, solar power, un-regulated small hydro power production, battery storage domestic and industrial and electrification of transport. Transmission System Operators (TSOs) have a responsibility to supply industry and communities with reliable electric power. However, the operators have been virtually blind to slowly occurring changes in the load profile that reduce the expected regularity of the power supply. This paper will focus on the possibilities and challenges the power business are facing. The paper will describe what technologies is needed i.e Real time probabilistic risk calculations, artificial intelligence, machine learning and smart grid technology. The main question is: can the power business and the introduction of new system tools manage without probabilistic risk calculation for making use of the digitalization and the corresponding big data?Digitalization of the power business: How to make this work?publishedVersionNivå

A Model for Techno-Economic Optimization of Wind Power Combined with Hydrogen Production in Weak Grids

This paper presents a two-step method for dimensioning and time-sequential operation of Wind-hydrogen (H2) plants operating in power markets. Step 1 involves identification of grid constraints and marginal power losses through load flow simulations. Step 2 involves solving a model for optimization of the component sizes (wind turbine, electrolyser, H2 storage, fuel cell) and the corresponding time-sequential operation of each component. Results are presented through a case study of a Norwegian island with good wind resources, a weak connection to the main transmission grid and a commuting ferry, constituting the H2 load. Main results show that if H2 consumers are willing to pay at least 0.31–0.34 € per Nm3, the wind power penetration could be cost-effectively increased by 1.8–1.9 MW by including an average H2 load of 1.36 MW. The H2 plant is very dependent on power import and H2 storage capacity is only 1.5–2 days of average demand. The operational flexibility of the H2 plant opens for a more optimal power exchange with the grid. It is concluded that H2 produced from wind power could be competitive with fossil fuels. H2 is however not cost-effective as electric energy storage for wind power plants operating in power markets

Transmission Expansion Planning in the Nordic System for Wind Power Integration based on Ant Colony Optimization

This paper presents a transmission expansion algorithm based on ant colony optimization. It was developed and tested on a model for the Nordic area. The main focus of this work was to build a transmission expansion planning tool able to cope with the new challenge of large wind power integration. Thus, the optimization uses hourly time steps to include wind and load variations. Nevertheless, the overall simulation time to find good solutions is quite fast using heuristic information. The ant colony optimization method proved to be flexible and delivered reasonable results for the calculated scenario of wind power integration for 2030

Ant colony optimization and analysis of time step resolution in transmission expansion computations for wind power integration

This paper investigates the necessary time step resolution in a transmission expansion planning algorithm based on ant colony optimization. A maximal and efficient wind power integration is the main motivation for the grid expansion, which requires a planning tool dealing with wind energy fluctuations. For the analysis a power system model for the Nordic area is used, including a wind power production scenario for 2030. A comparison of simulation results with different time step resolutions, including average and peak values for wind power production, is presented in this paper

Ant colony optimization and analysis of time step resolution in transmission expansion computations for wind power integration

This paper investigates the necessary time step resolution in a transmission expansion planning algorithm based on ant colony optimization. A maximal and efficient wind power integration is the main motivation for the grid expansion, which requires a planning tool dealing with wind energy fluctuations. For the analysis a power system model for the Nordic area is used, including a wind power production scenario for 2030. A comparison of simulation results with different time step resolutions, including average and peak values for wind power production, is presented in this paper

A Model for Techno-Economic Optimization of Wind Power Combined with Hydrogen Production in Weak Grids

This paper presents a two-step method for dimensioning and time-sequential operation of Wind-hydrogen (H2) plants operating in power markets. Step 1 involves identification of grid constraints and marginal power losses through load flow simulations. Step 2 involves solving a model for optimization of the component sizes (wind turbine, electrolyser, H2 storage, fuel cell) and the corresponding time-sequential operation of each component. Results are presented through a case study of a Norwegian island with good wind resources, a weak connection to the main transmission grid and a commuting ferry, constituting the H2 load. Main results show that if H2 consumers are willing to pay at least 0.31–0.34 € per Nm3, the wind power penetration could be cost-effectively increased by 1.8–1.9 MW by including an average H2 load of 1.36 MW. The H2 plant is very dependent on power import and H2 storage capacity is only 1.5–2 days of average demand. The operational flexibility of the H2 plant opens for a more optimal power exchange with the grid. It is concluded that H2 produced from wind power could be competitive with fossil fuels. H2 is however not cost-effective as electric energy storage for wind power plants operating in power markets

Improved System Performance by Integration of Adjustable Speed Hydro (ASH) Machines

Abstract The main purpose of this paper is to show how theAdjustable Speed Hydro (ASH) machine behaves with respect totransient and dynamic conditions in power systems. The ASHmachine gives a contribution to increased efficiency in ,thepenstocWturbine system as well as an improved flexibility withrespect to the electrical system. By means of its quick response tonetwork events, the ASH machine is able to obtain an increasedstability margin and thereby a more safe operation of the powersystem. With proper location and parametrisation of Power SystemStabilisers (PSS), the ASH machine can make considerable supportto damping of large scale power oscillations in transmissionnetworks. On the other hand, this represents new opportunities forthe power producer as well as for the system operator in utilisingthe transmission network even better. The paper has shown thattransmission lines appearing as bottlenecks with respect to powerdemand may increase their transfer capacity as ASH machines areintroduced in the network. In tum, this may lead to a postponementof high investment costs for new overhead lines. Furthermore, thepaper has given a quantification of how much the power export outof an example region can be increased due to introduction of ASHmachines.6 Halama

Bio‐inspired hybrid BFOA‐PSO algorithm‐based reactive power controller in a standalone wind‐diesel power system

With an increase in the penetration of renewable energy sources such as wind into the power systems, the operation and control of voltage/reactive power have become more complicated and challenging than ever. As a result, the reactive power imbalance between reactive power generation and demand instigates a reduction in system voltage stability. To deal with the aforesaid scenarios, automatic voltage regulator (AVR) and static synchronous compensator (STATCOM) are incorporated to curtail the voltage deviations in a standalone wind‐diesel power system. In this article, a hybrid bacterial foraging optimization algorithm‐particle swarm optimization (hBFOA‐PSO) algorithm is proposed for optimizing the PI controller parameters of AVR and STATCOM to further improve the system voltage/reactive power performance. Additionally, H∞‐loop shaping technique is designed to analyze the performance indexes (ie, robustness and stability) of the presented controller with the aim of handling the unstructured uncertainties from generation and loading situation. In order to present the efficiency of the proposed controllers, the performance of the hBFOA‐PSO controller is compared with the performance of the BFOA, PSO, and modified grey wolf optimization (MGWO)‐based PI controllers for the same wind‐diesel system. The dynamic responses of the wind‐diesel system for different disturbance cases have been investigated in the MATLAB/SIMULINK environment