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Publications

Publications by CPES

2024

Long-term storage expansion planning considering uncertainty and intra-annual time series

Authors
Abreu, T; Carvalho, L; Miranda, V;

Publication
2024 IEEE PES INNOVATIVE SMART GRID TECHNOLOGIES EUROPE, ISGT EUROPE

Abstract
Long-term storage expansion planning has usually employed representative days and intra-annual time series aggregation methodologies to reduce the computation complexity. This paper proposes a shift on the approach to the economic evaluation of these systems by implementing an intra-annual time series cost evaluation that considers different uncertainty trajectories. This methodology aims to determine the best possible investment strategies for the available computational budget using strategy game-based decision-making models, as Monte Carlo tree search. The proof of concept is illustrated by a single-bus equivalent test system and compared to a deterministic evaluation for a limited uncertainty model.

2024

Impact of the C-rates and AC-AC RTE on the annual cycles and operation cost of different battery technologies that provide market services

Authors
Agamez Arias, P; Miranda, V;

Publication
2024 IEEE 22nd Mediterranean Electrotechnical Conference, MELECON 2024

Abstract
This paper aims to study battery response under two operation strategies to analyze the annual cycles and operation costs (revenues) via sensitivity analysis. A battery model that considers performance parameters (AC-AC RTE, DOD, and C-rates) for different technologies is approached to identify how these parameters influence battery behavior and revenue. Strategies refer to (A) energy arbitrage, EA, and (B) EA and the provision of tertiary reserve. Simulations conducted for real data from Portuguese electricity and regulation markets showed regardless of the strategy used, the annual cycles and revenue are dominated by the performance parameters, instead of price volatility. In addition, for batteries with higher C-rates, as the AC-AC RTE is reduced up to 80%, the annual cycles and revenues are significantly reduced to 50% and 45% respectively, regarding its ideal model (100% AC-AC RTE). For lower C-rates, the annual cycles and revenues are slightly reduced with AC-AC RTE reductions. Specifically, strategy B revealed that annual cycles and revenue could also be influenced by the capacity requirements and the control area where batteries are providing services. © 2024 IEEE.

2024

Virtual power plant optimal dispatch considering power-to-hydrogen systems

Authors
Rodrigues, L; Soares, T; Rezende, I; Fontoura, J; Miranda, V;

Publication
INTERNATIONAL JOURNAL OF HYDROGEN ENERGY

Abstract
Power-to-Hydrogen (P2H) clean systems have been increasingly adopted for Virtual Power Plant (VPP) to drive system decarbonization. However, current models for the joint operation of VPP and P2H often disregard the full impact on grid operation or hydrogen supply to multiple consumers. This paper contributes with a VPP operating model considering a full Alternating Current Optimal Power Flow (AC OPF) while integrating different paths for the use of green hydrogen, such as supplying hydrogen to a Combined Heat and Power (CHP), industry and local hydrogen consumers. The proposed framework is tested using a 37-bus distribution grid and the results illustrate the benefits that a P2H plant can bring to the VPP in economic, grid operation and environmental terms. An important conclusion is that depending on the prices of the different hydrogen services, the P2H plant can increase the levels of self-sufficiency and security of supply of the VPP, decrease the operating costs, and integrate more renewables.

2024

Public policies to foster green hydrogen seasonal storage: Portuguese study case model until 2040

Authors
Santos, BH; Lopes, JP; Carvalho, L; Matos, M; Alves, I;

Publication
ENERGY STRATEGY REVIEWS

Abstract
Portugal made a climate commitment when it ratified the Paris Climate Agreement in 2015. As a result, Portugal, along with other EU members, has created a national roadmap for the deployment of hydrogen as a crucial component of Portugal ' s energy transition towards carbon neutrality, creating synergies between the electric and gas systems. The increased variability of generation from variable renewable power sources will create challenges regarding the security of supply, requiring investment in storage solutions to minimize renewable energy curtailment and to provide dispatchability to the electric power system. Hydrogen can be a renewable energy carrier capable of ensuring not only the desired transformation of the infrastructures of the gas system but also an integrator of the Electric System, such as in Power -to -Power (P2P) systems. Hydrogen can be produced with a surplus of renewable electricity from wind and solar, allowing a long-term energy seasonal storage strategy, namely by using underground salt caverns, to be subsequently transformed into electricity when demand cannot be supplied due to a shortage of renewable generation from solar or wind. P2P investments are capital intensive and require the development of transitional regulation mechanisms to both create opportunities to market agents while fostering the energy surplus valuation and decreasing the energy dependency. In order to maintain the electric system ' s security of supply, the suggested methodology innovatively manages the importance of seasonal storage of renewable energy surplus using hydrogen in power systems. It suggests a novel set of regulatory strategies to foster the creation of a P2P solution that maintains generation adequacy while assisting in decarbonising the electric power industry. Such methodology combines long-term adequacy assessment with regulatory framework evaluation to evaluate the cost of the proposed solutions to the energy system. A case study based on the Portuguese power system outlook between 2030 and 2040 demonstrates that the considerable renewable energy surplus can be stored as hydrogen and converted back into electricity to assure adequate security of supply levels throughout the year with economic feasibility under distinct public policy models.

2024

Collective Asset Sharing Mechanisms for PV and BESS in Renewable Energy Communities

Authors
Guedes, W; Oliveira, C; Soares, TA; Dias, BH; Matos, M;

Publication
IEEE TRANSACTIONS ON SMART GRID

Abstract
The energy sector transition to more decentralized and renewable structures requires greater participation by local consumers, which may be enabled by innovative models such as the setup of renewable energy communities (RECs). To maximize the self-consumption of local renewable energy generated by assets normally connected to the low voltage distribution grid, these RECs typically involve jointly owned assets such as collective photovoltaic solar panels (CPVs) and collective energy storage systems (CESS). This work proposes a novel mathematical model for a REC, accounting for three distinct economic approaches to the redistribution of collective benefits among community members. The main objective of this study is to understand how the participation of community members in collective assets (CAs) can help increase the fairness and equity of RECs. An illustrative REC case comprising members with individual and collective ownership of the assets is used to assess the proposed economic approaches. Extracting several answers, among them that the most advantageous configuration comes from agents with quotas in the CESS and CPV. An important conclusion is that depending on the selected economic approach, the social welfare and agent's revenue vary significantly. In any case, CESSs increase equity among REC members.

2024

Data-driven Approach for High Loss Detection in LV Networks

Authors
Paulos, JP; Macedo, P; Bessa, R; Fidalgo, JN; Oliveira, J;

Publication
2024 IEEE PES INNOVATIVE SMART GRID TECHNOLOGIES EUROPE, ISGT EUROPE

Abstract
This article proposes a methodology for high loss detection in LV network, based on a very small set of commonly available data/metadata from networks connected to an MV/LV substation. The approach is based on a combination of predictors from several distinct categories, including network data, metadata, and measured smart meter data. Several independent groups of unranked real networks were simulated, and it was possible to find the top ten networks with the highest level of losses with a very satisfactory success rate (76% to 98%), depending on selected groupings folds. Due to the impracticability of analyzing all LV networks, the identification of the highest loss ones is essential for the definition of loss reduction planning since, with this list filtering, it is possible to determine with a good degree of certainty which networks require maintenance or upgrade.

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