• Energy Research

Electric vehicles (EVs) charging demand is projected to be considerable in the future and imposes considerable impacts to the LV power network. However, how to forecast EV demand and assess the adverse charging effects like lower power quality and higher line loadings are still to be determined, which are crucial to economic power system operation and planning. In this research, by analysing the driving patterns of EVs, EV charging procedure is classified into 4 categories: residential slow charging (SC), workplace SC, fast charging (FC) and ultrafast charging (UC). The analysis criteria are mainly considering travelling distance, destination and vehicle idle time. Beta distribution function and double Gaussian distribution function are utilized to fit state of charge (SOC) and start charging time (SCT) functions of EV charging, from which the charging demand model of each EV charging type is given. Finally, time series power flow analysis is carried out to examine the adverse effects from EV charging demand in a test LV system.

The water system management problem has been widely investigated. However, the interdependencies between water and energy systems are significant and the effective co-optimization is required considering strong interconnections. This paper proposes a two-stage distributionally robust operation model for integrated water-energy nexus systems including power, gas and water systems networked with energy hub systems at a distribution level considering wind uncertainty. The presence of wind power uncertainty inevitably leads to risks in the optimization model. Accordingly, a coherent risk measure, i.e., conditional value-at-risk, is combined with the optimization objective to determine risk-averse operation schemes. This two-stage mean-risk distributionally robust optimization is solved by Bender's decomposition method. Both the day-ahead and real-time operation cost are minimized with an optimal set of scheduling the multi-energy infrastructures. Case studies focus on investigating the strong interdependencies among the four interconnected energy systems. Numerical results validate the economic effectiveness of IES through optimally coordinating the multi-energy infrastructures. The proposed model can provide system operators a powerful two-stage operation scheme to minimise operation cost under water-energy nexus considering risk caused by renewable uncertainties, thus benefiting customers with lower utility bills.

The increasing penetration of intermittent, low carbon generation poses a major threat to transmission system frequency stability. To mitigate this issue, future system frequency response can be provided by not only the generation side, such as from large, synchronous generators, but also by the customer side, such as from flexible technologies. This paper develops a novel model to evaluate the contribution from domestic Combined Heat and Power (CHP) plants to system frequency in the GB power system. This is achieved by controlling the electricity production from CHPs in response to significant fluctuations in system frequency. The results show that domestic CHP could increase system frequency stability with minimal adverse impact on the customers.

This paper develops a novel two-stage coordinated volt-pressure optimization (VPO) for integrated energy systems (IES) networked with energy hubs considering renewable energy sources. The promising power-to-gas (P2G) facilities are used for improving the interdependency of the IES. The proposed VPO contains the traditional volt-VAR optimization functionality to mitigate the voltage deviation while ensuring a satisfying gas quality due to the hydrogen mixture. In addition to the conventional voltage regulating devices, i.e., on-load tap changers and capacitor banks, P2G converter and gas storage are used to address the voltage fluctuation problem caused by renewable penetration. Moreover, an effective two-stage distributionally robust optimization (DRO) based on Wasserstein metric is utilized to capture the renewable uncertainty with tractable robust counterpart reformulations. The Wasserstein-metric based ambiguity set enables to provide additional flexibility hedging against renewable uncertainty. Extensive case studies are conducted in a modified IEEE 33-bus system connected with a 20-node gas system. The proposed VPO provides a voltage-regulated economic operation scheme with gas quality ensured that contributes to high-quality but low-cost multi-energy supply to customers.

This paper proposes a new problem formulation to simplify the mathematical representation for a hybrid ac/dc domestic energy system. Instead of building the formulation from a component level, the new formulation is built at the whole system level such that all power transfers between ac/dc or dc/ac are reflected in the ac power drawn from the main grid. This is achieved by assigning the ac power drawn from the grid as a piecewise function of local dc power, each slope in the function represents the conversion efficiency, making it flexible to consider a wide range of conversion efficiencies for different system components. The new formulation substantially reduces the number of variables/constraints, improves efficiency modelling accuracy and increases the search efficacy. The piecewise functions are directly solved by a mixed integer linear programming (MILP). The performance of the proposed formulation is illustrated by the hybrid ac/dc energy systems at a primary school in the U.K. The results show that the proposed problem formulation and the MILP solution method provide an effective optimal control strategy for a mixed ac/dc domestic energy system in the presence of variable tariffs and differing conversion efficiency, achieved a cost saving of 24% increase in energy bills compared with the traditional approach.

Abstract Peer to Peer (P2P) Energy trading in a lower voltage distribution system is one of the effective approaches to increase renewable energy penetration from decentralized generators (DG). In this paper, an energy auction is proposed as a marketplace and mechanism of the market design is established to ensure a fair and efficient bidding in the auction. An optimal bidding strategy is very important to the energy auction. To solve this problem, the Bayesian Game Theory is adopted as the strategy in the energy auction to enable efficient and cost-effective bidding for each buyer. This paper proposes a procedure for the energy auction to ensure that the power losses are within acceptable range. An algorithm to transform the power loss issue to become part of bidding strategy of Bayesian Game Theory. The proposed method is showed that it has maximized the utility for prosumer on a typical distribution network.

Many problems in power systems depend on parameters, which could be stochastic variables or deterministic system control variables practically, e.g., generation outputs, nodal voltages, etc. Due to the nonlinearity of power systems, the analytical relation between system states and parameters cannot be obtained directly. Using the sampling method to evaluate the influence of parameters on system states is very powerful but time-consuming. One feasible approach is to use polynomial approximations, where the system states are approximately expressed in the form of polynomials in terms of parameters. Galerkin method can be used to identify the approximate solution with high accuracy by solving high-dimensional equations. However, if a large number of parameters are involved, solving these high-dimensional equations becomes a serious challenge. This paper proposes an innovative method for resolving these high-dimensional equations in power systems, which constructs a sequence of decoupled equations to determine the polynomial expansion coefficients. This new approach can provide a local approximation in the form of Taylor expansion at a given operation point. Although the method is general, for simplicity and good readability, we introduce the detailed process in its application to load flow problems. Case studies from 6-, 118-, and 1648-bus system show that the proposed method provides approximation more efficiently than traditional Galerkin method does, and 3-order polynomials can give very accurate results.

Torsional vibrations present in the drivetrain excited by turbulent winds or grid disturbances (often manifesting as voltage sags) can produce severe stresses on the components of wind turbines. Th...