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This article explores the impact of electric vehicle (EV) charging on power systems and emphasizes the importance of careful analysis and planning. It discusses various topics related to EV charging, including EV hosting capacity, optimal placement of EVs and charging stations, technical impacts of Vehicle-to-Grid (V2G) technology, shared vehicle rental, decentralised collaboration frameworks, intelligent energy management schemes, EV demand response, and optimal sizing and siting of public EV charging stations. The article provides valuable insights and solutions for utilities, academia, and policymakers to address the challenges and opportunities associated with EV charging. Additionally, the article introduces a new approach for determining the limits of transformers and overhead lines in relation to EV charging, using Monte Carlo simulations and proposing new parameters for evaluating maximum demands. The authors stress the need for further analysis and attention to the impact of EVs on power systems. [Extracted from the article]

System operators still rely on deterministic criteria such as the N−1 (i.e. the system would be able to withstand the outage of any single component without any load shedding) to hedge the system against contingencies. While simple and practical, this criterion miscalculates the actual amount of reserve required since it ignores the probability of contingency occurrence. Therefore, this criterion may lead to suboptimal reserve procurement and economic performance of the system. This study presents a multiperiod probabilistic security‐constrained unit commitment (UC) model that includes the probabilities of generation and transmission contingencies for optimal reserve sizing, sourcing, allocation, and timing. The ability of energy storage systems (ESS) to provide contingency reserve is explicitly modelled. Benders' decomposition and linearisation techniques are applied to solve the proposed probabilistic UC, which would be intractable otherwise. The impact of ESS on the contingency reserve procurement and deployment in post‐contingency states are analysed on a modified version of the IEEE One‐Area Reliability Test System. [ABSTRACT FROM AUTHOR]

The massive development of energy storage systems (ESSs) may significantly help in the supply--demand balance task, especially under the existence of uncertain and intermittent sources of energy, such as solar and wind power. Using ESSs as complements of renewable generation has technical and economic consequences in both the short-term operation and the long-term expansion planning of the grid. The authors propose a transmission expansion planning model that incorporates decisions about the expansion of generic ESS units in order to study the interaction between the penetration and location of ESSs and the transmission investment decisions. The problem is formulated as a mixed-integer linear programming model and considers different demand blocks and their correlation with renewable generation, to account for the distinct features of the system over time. The authors' results show that ESSs are not only substitutes of transmission assets, but they may also be complemented with transmission assets depending on the power system characteristics. They use a 27-bus representation of the main Chilean network to illustrate the model proposed and to highlight some interesting results about the potential complementarity of ESSs and transmission expansion. [ABSTRACT FROM AUTHOR]

Stochastic security constrained unit commitment (SSCUC) based on a DC model could be problematic in AC networks because the DC model is potentially inaccurate. However, solving SSCUC problems using an AC model is still very challenging. Accordingly, an improved linearised AC optimal power flow (ILACOPF) model is provided in order to optimise the SSCUC problem. The proposed SSCUC model includes a linear representation of network losses and reactive power and bus voltage magnitudes. Moreover, in this study, transmission switching (TS), a powerful tool for grid side flexibility, is introduced and utilised to facilitate the mitigation of the uncertainty of wind power generation. Nevertheless, solving the SSCUC problem with TS in a full AC network is still one of the challenges in practical implementation, which is facilitated by the proposed ILACOPF model. Additionally, the aim of this study is to develop a more accurate power flow model to obtain a more realistic SSCUC solution using TS. The proposed ILAC‐SSCUC model using TS is formulated as a mixed‐integer linear programme, being solved by the proposed effective solution approach based on Benders' decomposition. Numerical simulations on a 6‐bus and IEEE 118‐bus systems have been performed to evaluate the effectiveness of the method. [ABSTRACT FROM AUTHOR]

This study presents a risk-assessment approach to the reactive power planning problem. Chance-constrained programming is used to model the random equivalent availability of existing reactive power sources for a given confidence level. Load shedding because of random equivalent availability of those reactive power sources is implemented through conditional-value-at-risk. Tap settings of under-load tap-changing transformers are considered as integer variables. Active and reactive demands are considered as probability distribution functions. The proposed mathematical formulation is a two-stage stochastic, multi-period mixed-integer convex model. The tradeoff between risk mitigation and investment cost minimisation is analysed. The proposed methodology is applied to the CIGRE-32 electric power system, using the optimisation solver CPLEX in AMPL. [ABSTRACT FROM AUTHOR]

This study presents a multiobjective tabu search algorithm to solve the multistage planning problem of a distribution system formulated as a multiobjective dynamic mixed integer non‐linear programming problem. Multiobjective problems do not have a specific solution, but a set of solutions that allows us to observe the trade‐off among the analysed objectives. Taking into account this concept, the objective functions of the model proposed in this study are: costs (investment and operational) and reliability. The actions deemed in this model for each period of the planning horizon are: increase in the capacity of existing substations (or construction of new ones), exchange of cables in existing lines (and construction of new feeders), reconfiguration of the network, allocation of sectionalising switches and construction of tie lines. The system's reliability is evaluated by means of the non‐supplied energy under contingencies using the n − 1 criterion. By line switching and the use of tie lines, part of the loads affected by a contingency can be restored, thus, the non‐supplied energy can be evaluated by solving a distribution network restoration problem. Numerical results are presented for a 54‐bus system. [ABSTRACT FROM AUTHOR]

In this study, a novel approach for the optimal location and contract pricing of distributed generation (DG) is presented. Such an approach is designed for a market environment in which the distribution company (DisCo) can buy energy either from the wholesale energy market or from the DG units within its network. The location and contract pricing of DG is determined by the interaction between the DisCo and the owner of the distributed generators. The DisCo intends to minimise the payments incurred in meeting the expected demand, whereas the owner of the DG intends to maximise the profits obtained from the energy sold to the DisCo. This two‐agent relationship is modelled in a bilevel scheme. The upper‐level optimisation is for determining the allocation and contract prices of the DG units, whereas the lower‐level optimisation is for modelling the reaction of the DisCo. The bilevel programming problem is turned into an equivalent single‐level mixed‐integer linear optimisation problem using duality properties, which is then solved using commercially available software. Results show the robustness and efficiency of the proposed model compared with other existing models. As regards to contract pricing, the proposed approach allowed to find better solutions than those reported in previous works. [ABSTRACT FROM AUTHOR]