An Integrated Market for Electricity and Natural Gas Systems with Stochastic Power Producers

In energy systems with high shares of weather-driven renewable power sources, gas-fired power plants can serve as a back-up technology to ensure security of supply and provide short-term flexibility. Therefore, a tighter coordination between electricity and natural gas networks is foreseen. In this work, we examine different levels of coordination in terms of system integration and time coupling of trading floors. We propose an integrated operational model for electricity and natural gas systems under uncertain power supply by applying two-stage stochastic programming. This formulation co-optimizes day-ahead and real-time dispatch of both energy systems and aims at minimizing the total expected cost. Additionally, two deterministic models, one of an integrated energy system and one that treats the two systems independently, are presented. We utilize a formulation that considers the linepack of the natural gas system, while it results in a tractable mixed-integer linear programming (MILP) model. Our analysis demonstrates the effectiveness of the proposed model in accommodating high shares of renewables and the importance of proper natural gas system modeling in short-term operations to reveal valuable flexibility of the natural gas system. Moreover, we identify the coordination parameters between the two markets and show their impact on the system's operation and dispatch

A system dynamics approach to study the long-term interaction of the natural gas market and electricity market comprising high penetration of renewable energy resources

Due to the gas consumption of some power plants for electricity generation and providing an acceptable level of flexibility, the interaction of natural gas markets and electricity markets is inevitable. One of the main challenges of policymakers in the energy sector coupling is the investigation of such interactions. Our main goal is to analyze the effect of the penetration of renewable energy resources on the behavior of gas markets and vice versa from the policymaker’s viewpoint. Moreover, we tend to study the effect of an external shock on the behavior of the whole system and the role of renewable resources in mitigating these side effects. Therefore, we used System Dynamic Approach to model the long-term behavior of the natural gas markets to extend the existed models of the electricity markets behavior and couple these markets. The Net Present Value method was used for the economic assessment of the investment in the development of gas reserves, and new stock and flow variables were defined to simulate this development. The simulations are performed for four scenarios by using a valid case study. Considering the results of simulations and sensitivity analysis, as the wind capacity incentive rose, the gas and electricity prices declined and their fluctuation increased during the time horizon. Although the effect of the gas market shock on the system depends on the time of occurrence, as the penetration of renewable units increased, the severity of its side effects decreased and the price jumps in the markets were mitigated.© 2022 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).fi=vertaisarvioitu|en=peerReviewed

Coupling power and gas systems models

The interconnections between gas and electricity networks and markets are relevant to the Regulation 2017/1938 on security of gas supply. Indeed, gas-fired power plants require gas to be able to deliver electricity to the network, and a number of facilities in the gas transmission network need electricity to work adequately. The only way to address the interactions between those two systems is by using an integrated model. We adopt a techno economic approach based on the PLEXOS® software, as a suitable compromise to represent large scale transmission systems adding economic detail to both the gas and electricity parts. This technical report presents the European market model (including a more detailed description of the Italian power market) for the year 2016, focusing on the structure of the model, the main assumptions and input data. The performance of the model for simulating the Italian power and gas markets is briefly evaluated.JRC.C.3-Energy Security, Distribution and Market

Strategic market participation of an energy storage system in a competitive electricity market considering short-run uncertainties

This thesis proposes an efficient method for scheduling and operating a power system with a single storage unit. The method utilizes a market clearing mechanism that incorporates distributed robust chance constraint (DRCC) methods to manage the risk associated with uncertain flexible technologies. The study assumes a fully centralized market setup and aims to optimize utility within the power sector while accounting for the presence of a storage system. The approach assumes an affine response to uncertainty, enabling the market operator to identify the most effective plan for executing flexibility to maximize social welfare in the day-ahead market and manage potential power imbalances in real-time operations. The dispatch mechanism takes into account the "availability costs" of flexible assets to manage their utilization efficiently. The study demonstrates that the proposed method enhances social welfare by taking advantage of the synergies between interconnected power networks and storage, particularly in situations where renewable energy generation is uncertain. However, the model is sensitive to the choice of price differences, availability costs, and investment costs, and cannot precisely advise building an energy storage system to provide flexibility response.This thesis proposes an efficient method for scheduling and operating a power system with a single storage unit. The method utilizes a market clearing mechanism that incorporates distributed robust chance constraint (DRCC) methods to manage the risk associated with uncertain flexible technologies. The study assumes a fully centralized market setup and aims to optimize utility within the power sector while accounting for the presence of a storage system. The approach assumes an affine response to uncertainty, enabling the market operator to identify the most effective plan for executing flexibility to maximize social welfare in the day-ahead market and manage potential power imbalances in real-time operations. The dispatch mechanism takes into account the "availability costs" of flexible assets to manage their utilization efficiently. The study demonstrates that the proposed method enhances social welfare by taking advantage of the synergies between interconnected power networks and storage, particularly in situations where renewable energy generation is uncertain. However, the model is sensitive to the choice of price differences, availability costs, and investment costs, and cannot precisely advise building an energy storage system to provide flexibility response

A review of co-optimization approaches for operational and planning problems in the energy sector

This paper contributes to a comprehensive perspective on the application of co-optimization in the energy sector – tracking the frontiers and trends in the field and identifying possible research gaps – based on a systematic literature review of 211 related studies. The use of co-optimization is addressed from a variety of perspectives by splitting the studies into ten key categories. Research has consistently shown that co-optimization approaches can be technically challenging and it is usually a data-intensive procedure. Overall, a set of techniques such as relaxation, decomposition and linear approaches have been proposed for reducing the inherent nonlinear model's complexities. The need to coordinate the necessary data from multiples actors might increase the complexity of the problem since security and confidentiality issues would also be put on the table. The evidence from our review seems to suggest a pertinent role for addressing real-case systems in future models instead of using theoretical test cases as considered by most studies. The identified challenges for future co-optimization models include (i) dealing with the treatment of uncertainties and (ii) take into account the trade-offs among modelling fidelity, spatial granularity and geographical coverage. Although there is also a growing body of literature that recognizes the importance of co-optimization focused on integrating supply and demand-side options, there has been little work in the development of co-optimization models for long-term decision-making, intending to recognize the impact of short-term variability of both demand and RES supply and well suited to systems with a high share of RES and under different demand flexibility conditions. The research results represent a further step towards the importance of developing more comprehensive approaches for integrating short-term constraints in future co-optimized planning models. The findings provide a solid evidence base for the multi-dimensionality of the co-optimization problems and contriThis work is supported by the National Council for Scientific and Technological Development (CNPq), Brazil. This work has been supported by FCT – Fundaça˜o para a Ciˆencia e Tecnologia within the R&D Units Project Scope: UIDB/00319/2020

Future pathways for energy networks: A review of international experiences in high income countries

Energy networks are the systems of pipes and wires by which different energy vectors are transported from where they are produced to where they are needed. As such, these networks are central to facilitating countries’ moves away from a reliance on fossil fuels to a system based around the efficient use of renewable and other low carbon forms of energy. In this review we highlight the challenges facing energy networks from this transition in a sample of key high income countries. We identify the technical and other innovations being implemented to meet these challenges and describe some of the new policy and regulatory developments that are incentivising the required changes. We then review evidence from the literature about the benefits of moving to a more integrated approach based on the concept of a Multi-Vector Energy Network (MVEN). Under this approach the different networks are planned and operated together to achieve greater functionality and performance than simply the sum of the individual networks. We find that most studies identify a range of benefits from an MVEN approach, but that these findings are based on model simulations. Further work is therefore needed to verify whether the benefits can be realised in practice and to identify how any risks can be mitigated