AC-feasible Local Flexibility Market with Continuous Trading

This paper proposes a novel continuous Local Flexibility Market where active power flexibility located in the distribution system can be traded. The market design engages the Market Operator, the Distribution System Operator and Market Participants with dispatchable assets. The proposed market operates in a single distribution system and considers network constraints via AC network sensitivities, calculated at an initial network operating point. Trading is possible when AC network constraints are respected and when anticipated network violations are alleviated or resolved. The implementation allows for partial bid matching and is computationally light, therefore, suitable for continuous trading applications. The proposed design is thoroughly described and is demonstrated in a test distribution system. It is shown that active power trading in the proposed market design can lead to resolution of line overloads.Comment: In proceedings of the 11th Bulk Power Systems Dynamics and Control Symposium (IREP 2022), July 25-30, 2022, Banff, Canad

Review of Methodologies for the Assessment of Feasible Operating Regions at the TSO–DSO Interface

The Feasible Operating Region (FOR) is defined as a set of points in the PQ plane that includes all the feasible active and reactive power flows at the Transmission System Operator (TSO)–Distribution System Operator (DSO) interconnection. Recent trends in power systems worldwide increase the need of cooperation between the TSO and the DSO for flexibility provision. In the current landscape, the efficient and accurate estimation of the FOR could unlock the potential of the DSO to provide flexibility to the TSO. To that end, much existing research has tackled the problem of FOR estimation, which is a challenging problem. However, no research that adequately organizes the literature exists. This work aims to fill this gap. Three categories of FOR estimation methods were identified: Geometric, Random Sampling, and Optimization-Based methods. The basic principles behind each method are analyzed and the most significant works involving each method are presented. For the reviewed works, we focus on the types of flexibility providing units included in the FOR estimation, the examination of time dependence, and the monetization of the FOR. Finally, the strengths and weaknesses of each category of methods are compared, providing a holistic review of the available FOR estimation methods

Capacity Mechanisms in Europe and the US: A Comparative Analysis and a Real-Life Application for Greece

This paper presents a comparative analysis of various capacity mechanisms that are either in force or under approval in key countries/regions in Europe and the US. A detailed analysis on the necessities that led to the establishment of the capacity mechanisms, along with various fundamental technical and operational features associated with the design and operation of different capacity mechanisms, mainly in Europe (Italy, France, Germany, Belgium, Poland, Great Britain, Ireland, Cyprus) and complementarily in the US (PJM, New England), are presented. This analysis is complemented by a real-life application regarding the long-term capacity remuneration mechanism that is expected to be established in Greece in the near future. A detailed simulation of the envisaged capacity mechanism auctions under differentiated scenarios has been performed, regarding the future Greek power system operating conditions during the forthcoming decade (2022–2031). Test results illustrate that the outcome of the auctions is heavily dependent on the future energy generation mix and the market participants’ bidding strategy. Whereas, the total cost that will have to be undertaken by the electricity supply companies and, ultimately, by the end-consumers for the financing of the proposed capacity mechanism lies in the range of 5.5–8.7 €/MWh for the entire study period

Modeling Framework Simulating the TERRE Activation Optimization Function

The Trans-European Replacement Reserve Exchange (TERRE) project is the European implementation project for exchanging Balancing Energy (BE) from Replacement Reserves (RR). Its main objective is to operate a common European platform that gathers all RR Balancing Energy Orders (BEOs) from Transmission System Operators’ (TSOs) local BE markets into a Common Merit Order List (CMOL). It provides an optimized allocation of RR, covering all TSOs’ RR BE needs, by executing the Activation Optimization Function (AOF). In this paper, the mathematical formulation of the AOF is presented, which explicitly incorporates all standard products and constraints that are provisioned in the approved implementation framework. The clearing problem is formulated as a Mixed Integer Linear Programming model and solved within an iterative algorithm for the handling of Paradoxically Accepted Orders (PAOs). The modeling framework allows the coordination of two distinct market setups, i.e., the self-dispatch and central dispatch. To this end, a BEO conversion pre-process is executed for markets applying the central-dispatch setup, in order to attain the BE quantities for inclusion in the CMOL. The proposed model is evaluated using a test case including six countries that participate in the TERRE project (Portugal, Spain, France, Great Britain, Switzerland, Italy) as well as Greece

Manual Frequency Restoration Reserve Activation Clearing Model

The integration of the European markets has started with the successful coupling of spot markets (day-ahead and intra-day) and is expected to continue with the coupling of balancing markets. In this paper, the optimization model for the activation of manual frequency restoration reserve (mFRR) is presented. The model incorporates all order types agreed among the European transmission system operators (TSOs) to be included in the Manually Activated Reserves Initiative (MARI) project. Additionally, the model incorporates the buying curve (demand) of mFRR with the possible tolerance band defined by the TSOs, order clearing constraints and the cross-zonal capacity (CZC) constraints, forming a mixed integer linear programming model. The methodology employs two distinct steps: In the first step, an order conversion process is employed for the markets applying the central-scheduling scheme, and in the second step, the mFRR activation process is executed by solving the presented model. The whole process is tested using a case, including twenty-five European control areas. The attained clearing results indicate that price convergence is achieved among the involved control areas, along with a reduction in the overall balancing costs mainly due to the imbalance netting that is implicitly performed during the joint mFRR balancing energy (BE) clearing process and due to the cross-border exchange of mFRR BE

Linearized model for optimization of coupled electricity and natural gas systems

Abstract In this paper a combined optimization of a coupled electricity and gas system is presented. For the electricity network a unit commitment problem with optimization of energy and reserves under a power pool, considering all system operational and unit technical constraints is solved. The gas network subproblem is a medium-scale mixed-integer nonconvex and nonlinear programming problem. The coupling constraints between the two networks are nonlinear as well. The resulting mixed-integer nonlinear program is linearized with the extended incremental method and an outer approximation technique. The resulting model is evaluated using the Greek power and gas system comprising fourteen gas-fired units under four different approximation accuracy levels. The results indicate the efficiency of the proposed mixed-integer linear program model and the interplay between computational requirements and accuracy

Stochastic and Deterministic Unit Commitment Considering Uncertainty and Variability Reserves for High Renewable Integration

The uncertain and variable nature of renewable energy sources in modern power systems raises significant challenges in achieving the dual objective of reliable and economically efficient system operation. To address these challenges, advanced scheduling strategies have evolved during the past years, including the co-optimization of energy and reserves under deterministic or stochastic Unit Commitment (UC) modeling frameworks. This paper presents different deterministic and stochastic day-ahead UC formulations, with focus on the determination, allocation and deployment of reserves. An explicit distinction is proposed between the uncertainty and the variability reserve, capturing the twofold nature of renewable generation. The concept of multi-timing scheduling is proposed and applied in all UC policies, which allows for the optimal procurement of such reserves based on intra-hourly (real-time) intervals, when concurrently optimizing energy and commitments over hourly intervals. The day-ahead scheduling results are tested against different real-time dispatch regimes, with none or limited look-ahead capability, or with the use of the variability reserve, utilizing a modified version of the Greek power system. The results demonstrate the enhanced reliability achieved by applying the multi-timing scheduling concept and explicitly considering the variability reserve, and certain features regarding the allocation and deployment of reserves are discussed