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Nandor Verba

Publications and source records attributed to Nandor Verba.

4 recordsLinked to original sources

Hidden Degradation Costs in Energy-Cost-Only HEMS Optimisation: Study on Battery and PV Sensitivity

Residential battery energy storage systems (BESS) are increasingly deployed alongside photovoltaic (PV) generation to reduce household energy costs under volatile time-of-use (TOU) tariffs. Model predictive control (MPC) is a widely adopted optimisation strategy for home energy management systems (HEMS), typically formulated to minimise net energy cost, subject to physical and operational constraints. However, battery degradation is rarely embedded in the optimisation objective, meaning its cost is unquantified and aggressive; high-cycle-count strategies could incur significant losses once deployed to physical systems. This paper presents a receding-horizon mixed-integer linear programming (MILP) baseline for a UK residential HEMS, using demand data from the REFIT dataset. A 3 by 3 sensitivity study is conducted across three battery sizes and three PV array sizes, with post-hoc degradation cost estimated using the Naumann stress model and rainflow cycle counting. Results show that degradation remains constant for each battery size and can exceed energy cost savings by up to 1,060 %. These results demonstrate that energy-cost-only optimisation systematically underestimates the true system cost, motivating a degradation-aware control formulation.

cs.NI

Cyber-physical components of an autonomous and scalable SLES

Adding renewable energy sources and storage units to an electric grid has led to a change in the way energy is generated and billed. This shift cannot be managed without a unified view of energy systems and their components. This unified view is captured within the idea of a Smart Local Energy System (SLES). Currently, various isolated control and market elements are proposed to resolve network constraints, demand side response and utility optimisation. They rely on topology estimations, forecasting and fault detection methods to complete their tasks. This disjointed design has led to most systems being capable of fulfilling only a single role or being resistant to change and extensions in functionality. By allocating roles, functional responsibilities and technical requirements to bounded systems a more unified view of energy systems can be achieved. This is made possible by representing an energy system as a distributed peer-to-peer (P2P) environment where each individual demand energy resource (DER) on the consumer's side of the meter is responsible for their portion of the network and can facilitate trade with numerous entities including the grid. Advances in control engineering, markets and services such as forecasting, topology identification and cyber-security can enable such trading and communication to be done securely and robustly. To enable this advantage however, we need to redefine how we view the design of the sub-systems and interconnections within smart local energy systems (SLES). In this paper we describe a way in which whole system design could be achieved by integrating control, markets and analytics into each system. We propose the use of physical, control, market and service layers to create system of systems representation.

cs.NI

Incorporating forecasting and peer-to-peer negotiation frameworks into a distributed model predictive control approach for meshed electric networks

Continuous integration of renewable energy sources into power networks is causing a paradigm shift in energy generation and distribution with regards to trading and control; the intermittent nature of renewable sources affects pricing of energy sold or purchased; the networks are subject to operational constraints, voltage limits at each node, rated capacities for the power electronic devices, current bounds for distribution lines. These economic and technical constraints coupled with intermittent renewable injection may pose a threat to system stability and performance. We propose a novel holistic approach to energy trading composed of a distributed predictive control framework to handle physical interactions, i,e., voltage constraints and power dispatch, together with a negotiation framework to determine pricing policies for energy transactions. We study the effect of forecasting generation and consumption on the overall network's performance and market behaviours. We provide a rigorous convergence analysis for both the negotiation framework and the distributed control. Lastly, we assess the impact of forecasting in the proposed system with the aid of testing scenarios.

eess.SY

The energy revolution: cyber physical advances and opportunities for smart local energy systems

We have designed a two-stage, 10-step process to give organisations a method to analyse small local energy systems (SLES) projects based on their Cyber Physical System components in order to develop future-proof energy systems. SLES are often developed for a specific range of use cases and functions, and these match the specific requirements and needs of the community, location or site under consideration. During the design and commissioning, new and specific cyber physical architectures are developed. These are the control and data systems that are needed to bridge the gap between the physical assets, the captured data and the control signals. Often, the cyber physical architecture and infrastructure is focused on functionality and the delivery of the specific applications. But we find that technologies and approaches have arisen from other fields that, if used within SLES, could support the flexibility, scalability and reusability vital to their success. As these can improve the operational data systems then they can also be used to enhance predictive functions If used and deployed effectively, these new approaches can offer longer term improvements in the use and effectiveness of SLES, while allowing the concepts and designs to be capitalised upon through wider roll-out and the offering of commercial services or products.

eess.SY