arXiv subjects

Milos Cvetkovic

Publications and source records attributed to Milos Cvetkovic.

8 recordsLinked to original sources

arXiv2026

Technology configurations for decarbonizing residential heat supply through district heating and implications for the electricity network

District heating networks (DHNs) have significant potential to decarbonize residential heating and accelerate the energy transition. However, designing carbon-neutral DHNs requires balancing several objectives, including economic costs, social acceptance, long-term uncertainties, and grid-integration challenges arising from electrification. By combining modeling-to-generate-alternatives with power flow simulation techniques, we develop a decision-support method for designing carbon-neutral DHNs that are cost-effective, socially acceptable, and impose minimal impacts on the electricity grid. Applying our method to a Dutch case, we find substantial diversity in how carbon-neutral DHNs can be designed. The flexibility in technology choice, sizing, and location enables accommodating different real-world needs and achieving high electrification levels without increasing grid loading. For instance, intelligently located heat pumps and thermal storage can limit grid stress even when renewable baseload heat sources and green-fuel boilers are scarce. Using our method, planners can explore diverse carbon-neutral DHN designs and identify the design that best balances stakeholders' preferences.

eess.SY↗

arXiv2026

Generating EUPHEMIA-compatible bids for flexible demand under imperfect information

Electricity procurement constitutes a significant share of operational costs for large electricity consumers, and thus exposure to extreme prices poses a substantial financial risk. This paper proposes a method to generate EUPHEMIA-compatible bids for flexible demand to enable their participation in the European day-ahead electricity market while minimizing risks. Two strategies are considered, resulting in two bid formats: hourly bids (HBs), representing flexibility via marginal price responsiveness through price-quantity pairs, and exclusive-group bids (EBs), representing flexibility via mutually exclusive operational schedules submitted at opportunity cost. Our method is evaluated on a hypothetical electrolyzer system and a real-world steel plant under different market conditions. Results show that the economic performance of each strategy depends on the operational characteristics of the load and market conditions. Under volatile market conditions, highly flexible systems achieve better economic outcomes with EBs, while less flexible systems with stronger intertemporal constraints perform better with HBs.

econ.TH↗

arXiv2025

On the Smart Coordination of Flexibility Scheduling in Multi-carrier Integrated Energy Systems

Coordinating the interactions between flexibility assets in multi-carrier integrated energy systems (MIES) can lead to an efficient integration of variable renewable energy resources, and a cost-efficient energy transition. However, the proliferation of flexibility assets and their participation in active demand response increases the complexity of coordinating these interactions. This paper introduces different approaches to model the coordination of flexibility scheduling in MIES. We propose a market auction-inspired model coupling approach to address the challenges of preserving the autonomy and privacy of flexibility providers, and the issue of scalability. We benchmark our approach against co-optimization and an iterative price-response method by conducting experiments with varying problem sizes and computing infrastructure. We show that our approach scales well and is suitable for modeling flexibility in large-scale energy systems in a more realistic way. From an optimality standpoint, the flexibility dispatch schedules and electricity prices are ``near-optimal". Our methodology is implemented as a new open-source software, which offers several practical applications. For example, flexibility providers and network operators can couple their models to simulate the interaction between their systems without disclosing confidential information; policy regulators can use it to investigate new market design and regulations to optimize the utilization of flexibility in MIES.

eess.SY↗

arXiv2018

Directly Constraining Marginal Prices in Distribution Grids Using Demand-Side Flexibility

Recently, the volatility associated with marginal prices has increased due to large scale integration of renewable generation. Price volatility is undesirable from a consumer perspective. To address this issue, we present a framework for hedging that uses duality theory for quantifying the amount of demand-side flexibility required for constraining marginal prices to the consumers maximum willingness to pay for electricity. Using our formulation, we investigate the ability of an Energy Storage System (ESS), as a demand-side flexibility source, to hedge against electricity price volatility across a multi-time period horizon while accounting for its inter-temporal constraints. Additionally, we analyze the economical benefit that operating the ESS under information forecasts brings to the consumers.

math.OC↗

arXiv2018

Smart Grid Co-Simulation with MOSAIK and HLA: A Comparison Study

Evaluating new technological developments for energy systems is becoming more and more complex. The overall application environment is a continuously growing and interconnected cyber-physical system so that analytical assessment is practically impossible to realize. Consequently, new solutions must be evaluated in simulation studies. Due to the interdisciplinarity of the simulation scenarios, various heterogeneous tools must be connected. This approach is known as co-simulation. During the last years, different approaches have been developed or adapted for applications in energy systems. In this paper, two co-simulation approaches are compared that follow generic, versatile concepts. The tool mosaik, which has been explicitly developed for the purpose of co-simulation in complex energy systems, is compared to the High Level Architecture (HLA), which possesses a domain-independent scope but is often employed in the energy domain. The comparison is twofold, considering the tools' conceptual architectures as well as results from the simulation of representative test cases. It suggests that mosaik may be the better choice for entry-level, prototypical co-simulation while HLA is more suited for complex and extensive studies.

cs.OH↗

arXiv2018

The Role of Demand-Side Flexibility in Hedging Electricity Price Volatility in Distribution Grids

Locational Marginal Price (LMP) is a dual variable associated with supply-demand matching and represents the cost of delivering power to a particular location if the load at that location increases. In recent times it become more volatile due to increased integration of renewables that are intermittent. The issue of price volatility is further heightened during periods of grid congestion. Motivated by these problems, we propose a market design where, by constraining dual variables, we determine the amount of demand-side flexibility required to limit the rise of LMP. Through our proposed approach a price requesting load can specify its maximum willingness to pay for electricity and through demand-side flexibility hedge against price volatility. For achieving this, an organizational structure for flexibility management is proposed that exhibits the coordination required between the Distribution System Operator (DSO), an aggregator and the price requesting load. To demonstrate the viability of our proposed formulation, we run an illustrative simulation under infinite and finite line capacities.

math.OC↗

arXiv2017

Cyber Risk Analysis of Combined Data Attacks Against Power System State Estimation

Understanding smart grid cyber attacks is key for developing appropriate protection and recovery measures. Advanced attacks pursue maximized impact at minimized costs and detectability. This paper conducts risk analysis of combined data integrity and availability attacks against the power system state estimation. We compare the combined attacks with pure integrity attacks - false data injection (FDI) attacks. A security index for vulnerability assessment to these two kinds of attacks is proposed and formulated as a mixed integer linear programming problem. We show that such combined attacks can succeed with fewer resources than FDI attacks. The combined attacks with limited knowledge of the system model also expose advantages in keeping stealth against the bad data detection. Finally, the risk of combined attacks to reliable system operation is evaluated using the results from vulnerability assessment and attack impact analysis. The findings in this paper are validated and supported by a detailed case study.

cs.CR↗

arXiv2017

Data Attacks on Power System State Estimation: Limited Adversarial Knowledge vs. Limited Attack Resources

A class of data integrity attack, known as false data injection (FDI) attack, has been studied with a considerable amount of work. It has shown that with perfect knowledge of the system model and the capability to manipulate a certain number of measurements, the FDI attacks can coordinate measurements corruption to keep stealth against the bad data detection. However, a more realistic attack is essentially an attack with limited adversarial knowledge of the system model and limited attack resources due to various reasons. In this paper, we generalize the data attacks that they can be pure FDI attacks or combined with availability attacks (e.g., DoS attacks) and analyze the attacks with limited adversarial knowledge or limited attack resources. The attack impact is evaluated by the proposed metrics and the detection probability of attacks is calculated using the distribution property of data with or without attacks. The analysis is supported with results from a power system use case. The results show how important the knowledge is to the attacker and which measurements are more vulnerable to attacks with limited resources.

cs.CR↗