Simon Stock

M.Sc.
Wissenschaftlicher Mitarbeiter

Kontakt

Simon Stock, M. Sc.
E-6 Elektrische Energietechnik
  • Elektrische Energietechnik
Sprechzeiten
Jederzeit
Harburger Schloßstraße 36,
21079 Hamburg
Gebäude HS36, Raum C3 0.006
Tel: +49 40 42878 2378
Logo

Forschungsprojekte

Einsatz von KI in der Betriebsführung von Verteilnetzen

Einsatz von KI in der Betriebsführung von Verteilnetzen

Technische Universität Hamburg (TUHH); Laufzeit: 2020 bis 2024

VeN²uS
Vernetzte Netzschutzsysteme - Adaptiv und vernetzt

VeN²uS

Vernetzte Netzschutzsysteme - Adaptiv und vernetzt

Bundesministerium für Wirtschaft und Klimaschutz (BMWK); Laufzeit: 2021 bis 2024

Forschungsschwerpunkt

Optimaler Betrieb und Energiemanagement von elektrischen Verteilnetzen (Smart Grids) mithilfe von künstlicher Intelligenz

Publikationen

TUHH Open Research (TORE)

2023

2022

2021

Lehrveranstaltungen

Stud.IP
zur Veranstaltung in Stud.IP Studip_icon
Negotiation Management
Untertitel:
Course within the elective module "Projekt- und Verhandlungsmanagement" for IWI students (3 ECTS) AND Elective course for all TUHH students as a Management elective (2 ECTS)
Semester:
WiSe 23/24
Veranstaltungstyp:
PBL -Projekt-/problembasierte Lehrveranstaltung (Lehre)
Veranstaltungsnummer:
lv2669_w23
DozentIn:
Christian Lüthje, Jan-Niklas Anders
Beschreibung:

General description of course content and course goals

We negotiaate everday in privat and professional contexts. Leading negotiations successfully has a significant impact on future careers. Yet, we tend to have limited knowledge about the theory and empirical evidence regarding successful negotiating. Many people approach negotiations in a rather intuitive and unplanned way which often results in sub-optimal negotiation outcomes.

The purpose of this interactive and problem-based course is to theortically understand the strategies and process of negotiationas practiced in a variety of business-related settings (e.g. negotiations about working conditions, negotiations with customers and suppliers). The course will highlight the components of an effectivenegotiation (strategy, perparation, execution, evaluation) and offer the students the opportunity to analyze their own behavior in negotiations in order to improve.

The course structure is experiential and problem-based, combining lectures, classdiscussion, mini-cases and small erxercises, and more comprehensive negotiation practices in longer sessions. Through participation in negotiation exercises,students will have the opportunity to practice their communication andpersuasion skills and to experiment with a variety of negotiating strategiesand tactics. Students will apply the lessons learned toongoing, real-world negotiations.


Content:

The studentswill find answers to the following fundamental questions of negotiation strategies in theoryand practice:

  • How do negotiations influence everyday life and business processes?
  • What are key features of negotiations?
  • What are different forms of negotiations? What kinds of negotiation can be distinguished?
  • Which theoretical approaches to a theory of negotiation can be distinguished?
  • How can game theory be applied to negotiation?
  • What makes an effective negotiator?
  • Which factors should be considered when planning negotiations?
  • What steps must be followed to reach a deal?
  • Are there specific negotiation tactics?
  • What are the typical barriers to an agreement and how to deal with them?
  • What are possible cognitive (mental) errors and how to correct them?

Knowledge

Students know...

  • the theory basics of negotiations (e.g. game theory, behavioral theories)
  • the types and the pros and cons of diffrent negotiation strategies
  • the process of negotiation, inlcuding goal formulation, preparation/planning, execution and evaluation 
  • about some key issues impacting negotiations (e.g. team building and roles, barriers to reaching a deal, cognitive biases, multi-phase negotiations)

Skills

Students arecapable of...

  • simultaneously considering multiple factors in negotiation situations and taking reasoned actions when preparing and conducting negotiations.
  • Analyzing and handling the key challenges of uncertainty, risk, intercultural differences, and time pressure in realistic negotiation situations.
  • assessing the typical barriers to an agreement (e.g. lack of trust), dealing with hardball tactics (e.g. good cop, bad cop; lowball, highball; intimidation), and avoiding cognitive traps (e.g. unchecked emotions, overconfidence).
  • reflecting on their decision-making in uncertain negotiation situations and derive actions for future decisions.

Social Competence

Studentscan...

  • provide appropriate feedback and handle feedback on their own performance constructively.
  • constructively interact with their team members in role playing in negotiations sessions
  • develop joint solutions in mixed teams and present them to others in real-world negotiation situatio

    Self-Reliance

    Students areable to...

    • assess possible consequences of their own negotiation behavior
    • define own positions and tasks in the negotiation preparation process.
    • justify and make elaborated decisions in authentic negotiation situations.




Leistungsnachweis:
Theoretical and practical work
ECTS-Kreditpunkte:
3 for IWI students, 2 as a Manag
Weitere Informationen aus Stud.IP zu dieser Veranstaltung
Heimatinstitut: Institut für Innovationsmarketing (W-3)
In Stud.IP angemeldete Teilnehmer: 38
Anzahl der Dokumente im Stud.IP-Downloadbereich: 1

Betreute Abschlussarbeiten

laufende
beendete

2021

  • Hund, P. (2021). Modellierung eines elektrischen Netzes zur Demonstration des Einflusses von virtueller Trägheit durch umrichterbasierte Energieanlagen.

  • Hund, P. (2021). Koordinierte Bereitstellung von virtueller Trägheit durch erneuerbare umrichterbasierte Energieanlagen in Verteilnetzen mithilfe von künstlicher Intelligenz.

  • Möller, P. (2021). Erfassung der Knotenspannung in Niederspannungsnetzen auf Basis von dezentralen Messeinrichtungen mithilfe von Machine learning.

  • Plant, R. (2021). Estimation of Power System Inertia in an Inverter-Dominated Distribution Grid Using Machine Learning.

2020

  • Dressel, M. (2020). Modellierung der Zustandsschätzung eines elektrischen Netzes mit Hilfe von Graph neuronalen Netzen.

  • Schmidt, M. (2020). Vorhersage von zuverlässig bereitstellbarer Regelleistung aus Erneuerbaren Energien mithilfe von neuronalen Netzen.