### Professeur-e HES Associé-e

Büro: ENP.23.N417

Rue de l'Industrie 23, 1950 Sion, CH

**Bereich**

Technique et IT

**Hauptstudiengang**

Energie et techniques environnementales

- Réseaux électriques
- Réseaux électriques avancés

2023

2022

2018

**Zusammenfassung:**

Multiple research works and power systems operational practices have qualitatively associated the progressive connection of stochastic renewable energy resources with the increase of power systems reserve requirements. At the same time, the price and technology of MW-class Battery Energy Storage Systems (BESSs) have considerably improved, which opens up the possibility to make electric distribution networks dispatchable. In this paper, we investigate the impact on the bulk power system of dispatchable electric distribution networks that host a large share of stochastic resources. The essential questions inspiring this research are: (1) Assuming that BESSs are deployed to achieve dispatchability of distribution grids embedding stochastic resources, what is the impact on the bulk power system reserve requirement? (2) Is this large-scale integration of BESSs economically viable compared to centralized reserve procurement from traditional power plants? To address these questions, we consider the case of the Danish transmission grid and the associated fleet of conventional power plants and compare it against locally dispatched distribution grids. We perform stochastic simulations to quantify and validate the amount of reserve necessary to operate these power systems with a desired reliability level. We establish a numerical equivalence between saved conventional reserve capacity and amount of BESS storage deployed in distribution networks. Then, we quantify the economic pay-back times of BESSs capital expenditure (CAPEX). The results show that: (1) large scale deployment of BESSs with dispatchable distribution networks is a viable technical solution to address flexibility requirements for the bulk power system and (2) this solution is economically viable with a pay-back time in the range of 11–14 years compared to providing flexibilities from conventional power plants.

2015

**Zusammenfassung:**

This paper describes the application of stochastic grey-box modelling to identify electrical power consumption-to-temperature models of a domestic freezer using experimental measurements. The models are formulated using stochastic differential equations (SDEs), estimated by maximum likelihood estimation (MLE), validated through the model residuals analysis and cross-validated to detect model over-fitting. A nonlinear model based on the reversed Carnot cycle is also presented and included in the modelling performance analysis. As an application of the models, we apply model predictive control (MPC) to shift the electricity consumption of a freezer in demand response experiments, thereby addressing the model selection problem also from the application point of view and showing in an experimental context the ability of MPC to exploit the freezer as a demand side resource (DSR).

2014

**Zusammenfassung:**

This paper presents the design of a control strategy for the energy management of a grid-connected microgrid with local distributed energy resources as: 10-kW photovoltaic plant, 11-kW wind turbine, and 15-kW–190-kWh vanadium-based electric storage system. According to future regulations, the renewable energy producers will also have to provide a day-ahead hourly production plan. The overall idea is, by knowing the meteorological forecasts for the next 24 h, to dispatch the microgrid in order to be able to grant the scheduled hourly production by means of proper management of the storage system. The usage of the storage system is, however, minimized by the energy management strategy. The system design is validated by experimental testing carried out in SYSLAB, a distributed power system test facility at Risø Campus, Technical University of Denmark.

2019

**Zusammenfassung:**

Distributed energy resources (DERs) installed in active distribution networks (ADNs) can be exploited to provide both active and reactive power reserves to the upper-layer grid (i.e., sub-transmission and transmission systems) at their connection point. This paper introduces a method to determine the capability area of an ADN for the provision of both active and reactive power reserves while considering the forecast errors of loads and stochastic generation, as well as the operational constraints of the grid and DERs. The method leverages a linearized load flow model and introduces a set of linear scenario-based robust optimization problems to estimate the reserve provision capability (RPC) area of the ADN. It is proved that, under certain assumptions, the RPC area is convex. The performance of the proposed method is tested on a modified version of the IEEE 33-bus distribution test system.

*Proceedings of the 13th IEEE PowerTech (POWERTECH) 2019*

**Zusammenfassung:**

The flexibility of distributed energy resources (DERs) accommodated in active distribution networks (ADNs) can be aggregated and then used to provide ancillary services to the transmission system. In this context, this paper presents a linear optimization method for the transmission system operator (TSO) to allocate its required active power reserve from aggregated resources installed in active distribution systems (ARADSs) as well as dispatchable bulk power plants (DBPPs). It consists in a linear optimization problem that minimizes the sum of the expected cost of active power reserve allocated from all possible providers (including ARADSs and DBPPs) and the expected cost of load not served over a desired time horizon. The value of lost load (VOLL) index is used as a criterion to realize an economical balance between the expected cost of allocated reserve and expected cost of load not served. The method leverages scenarios of power system contingencies and forecast errors of loads and renewable generation to represent typical operational uncertainties. A simulation proofof-concept using real-data from the transmission system operator of Switzerland, Swissgrid, is provided to illustrate the performance of the method.

2018

*Proceedings of the 2018 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe)*

**Zusammenfassung:**

Uncertainty levels in forecasting of renewable generation and demand are known to affect the amount of reserve required to operate the power grid with a given level of reliability. In this paper, we quantify the effects on the system reserve and reliability, due to the local dispatch of stochastic demand and renewable generation. The analysis is performed considering the model of the IEEE 39-bus system, with detailed dynamic models of conventional generation, wind generation, demand and an under-frequency load shedding mechanism. The analysis compares to cases: the base case, where renewable generation and demand power are stochastic and the power reserve is provided by conventional generation, against the case where the operation of traditionally stochastic resources is dispatched according to pre-established dispatch plans thanks to controlling local flexibility. Simulations reproduce the post-contingency dynamic behavior of the grid due to outages of generators. The contingencies are selected to trigger under frequency load shedding mechanisms, hence to demonstrate the different levels of system operation reliability for the two case studies. Simulation results show that dispatching traditionally stochastic generation scores better regarding to expected energy not served, producing an increase of the system reliability.

**Zusammenfassung:**

This paper addresses the allocation of frequency control services (FCSs) from aggregated resources of active distribution systems (ARADSs) for balancing the transmission system while considering credible contingencies as well as forecast error of loads and generations through scenarios. First the paper introduces a generic framework for modeling ARADS including distributed energy resources (DERs) as seen from the transmission system operator (TSO) perspective. Afterwards, based on the proposed modeling framework and relying on a DC power flow model, the problem is formulated as a linear optimization problem consisting in minimizing the cost of FCSs provision and deployment from all possible providers including ARADSs and GENCOs. Nodal and total Expected Load Not Served (ELNS) indices are used to measure the security of the transmission system for the different scenarios. Finally, a proofof- concept of the proposed planning strategy is proposed by considering the IEEE 24-bus system.

*Proceedings of the 15th International Conference on the European Energy Market (EEM) 2018*

**Zusammenfassung:**

Transmission System Operators (TSOs) deploy frequency control reserves and regulating power to maintain the load-generation balance in real-time operation of power systems. In the Nordic countries, the TSOs buy regulating power from the Nord Pool regulating power market. In this paper, we developed a tool to quantify the price of regulating power as a function of both economic parameters such as spot (day-ahead) market price, and technical factors representing the current state of the system. First, the Nord Pool is considered as a single bidding area and an aggregated regulating power price is obtained, proving the validity of a simple non-linear algebraic model, when there is no influence of interconnections with neighboring areas. Then, we developed a case study for the West Denmark area, to demonstrate that for complex systems, where there is possibility of trade with other areas and there is high penetration of intermittent generation (e.g., wind power), this simple formulation is no longer valid. Finally, to solve this inconsistency, an improved model is here proposed by considering the effect of interconnections through two scenarios: one for unconstrained trade through the interconnections with neighbouring areas, and the second one where at least one of the interconnecting lines is congested. In addition, the wind penetration level is included as a parameter the non-linear algebraic model.

2014

*Proceedings of the 48th International Universities' Power Engineering Conference (UPEC)*

**Zusammenfassung:**

The paper discusses and describes a system for energy management of a 10 kW PV plant coupled with a 15 kW-190 kWh storage system. The overall idea is, by knowing the meteorological forecast for the next 24h, to dispatch the PV system and to be able to grant the scheduled hourly energy profile by a proper management of the storage. Due to forecast inaccuracies, the energy manager controls the storage in order to ensure that the plan for hourly energy production is respected, minimizing the storage itself usage. The experimental study is carried out in SYSLAB, a distributed power system test facility at DTU Riso Campus and part of PowerLabDK. Both the PV and the storage are connected to the local network and are fully controllable through the SCADA system. The control management and the models are implemented in Matlab-Simulink, which can be interfaced with SYSLAB.

2013

*Proceedings of 4th IEEE PES Innovative Smart Grid Technologies Europe (ISGT Europe)*

**Zusammenfassung:**

This paper presents a control scheme based on distributed model predictive control (DMPC) for coordinating flexible distributed energy resources (DER) of heterogeneous type in the Smart Grid with minimum system integration effort. This approach can be used for reducing the peak power exchange between the grid and a cluster of units in the same feeder in price-driven demand response applications. Preliminary simulations prove that the proposed coordination scheme for DMPC succeeds in coordinating flexible DER unit, achieving significant peak shaving when required. The rationale of this approach consists in coordinating independent units equipped with local MPC controller via simple information passing and hiding in the local controllers the units' dynamics.

*Proceedings of the 4th International Youth Conference on Energy (IYCE)*

**Zusammenfassung:**

This paper presents the grey-box modeling of a vapor-compression refrigeration system for residential applications based on maximum likelihood estimation of parameters in stochastic differential equations. Models obtained are useful in the view of controlling refrigerators as flexible consumption units, which operation can be shifted within temperature and operational constraints. Even if the refrigerators are not intended to be used as smart loads, validated models are useful in predicting units consumption. This information can increase the optimality of the management of other flexible units, such as heat pumps for space heating, in order to smooth the load factor during peak hours, enhance reliability and efficiency in power networks and reduce operational costs.

**Zusammenfassung:**

Inducing a shift in the electricity consumption using a broadcasted dynamic price for the energy is often proposed as a resource for providing regulating power and it is becoming an increasing research focus for enabling higher penetration of renewable energy in the current power system. This paper shows how using indirect control (or control by price) without any precautions, might easily lead to congestions in nearly saturated distribution grids. An auto tuning local controller which acts on the price signal at distribution level is proposed for solving the congestion. Simulations are performed with the CIGRE' MV reference network with 346 electrically heated buildings as Demand Side Resources, DSRs. The dynamic hourly price of the regulating power provided by Nord Pool Spot market has been used as indirect control signal for the flexible demand.

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