This paper presents an integrated distribution locational marginal pricing (DLMP) method designed to alleviate congestion induced by electric vehicle (EV) loads in future power systems. In the ...proposed approach, the distribution system operator (DSO) determines distribution locational marginal prices (DLMPs) by solving the social welfare optimization of the electric distribution system which considers EV aggregators as price takers in the local DSO market and demand price elasticity. Nonlinear optimization has been used to solve the social welfare optimization problem in order to obtain the DLMPs. The efficacy of the proposed approach was demonstrated by using the bus 4 distribution system of the Roy Billinton Test System (RBTS) and Danish driving data. The case study results show that the integrated DLMP methodology can successfully alleviate the congestion caused by EV loads. It is also shown that the socially optimal charging schedule can be implemented through a decentralized mechanism where loads respond autonomously to the posted DLMPs by maximizing their individual net surplus.
This paper proposes a sufficient condition for the convex relaxation of ac optimal power flow (OPF) in radial distribution networks as a second order cone program (SOCP) to be exact. The condition ...requires that the allowed reverse power flow is only reactive or active, or none. Under the proposed sufficient condition, the feasible sub-injection region (power injections of nodes excluding the root node) of the ac OPF is convex. The exactness of the convex relaxation under the proposed condition is proved through constructing a group of monotonic series with limits, which ensures that the optimal solution of the SOCP can be converted to an optimal solution of the original ac OPF. The efficacy of the convex relaxation to solve the ac OPF is demonstrated by case studies of an optimal multi-period planning problem of electric vehicles in distribution networks.
This paper presents the distribution locational marginal pricing (DLMP) method through quadratic programming (QP) designed to alleviate the congestion that might occur in a distribution network with ...high penetration of flexible demands. In the DLMP method, the distribution system operator (DSO) calculates dynamic tariffs and publishes them to the aggregators, who make the optimal energy plans for the flexible demands. The DLMP through QP instead of linear programing as studied in previous literatures solves the multiple solution issue of the aggregator optimization which may cause the decentralized congestion management by DLMP to fail. It is proven in this paper, using convex optimization theory, the aggregator's optimization problem through QP is strictly convex and has a unique solution. The Karush-Kuhn-Tucker (KKT) conditions and the unique solution of the aggregator optimization ensure that the centralized DSO optimization and the decentralized aggregator optimization converge. Case studies using a distribution network with high penetration of electric vehicles (EVs) and heat pumps (HPs) validate the equivalence of the two optimization setups, and the efficacy of the proposed DLMP through QP for congestion management.
This paper proposes a dynamic tariff-subsidy (DTS) method for congestion management in distribution networks with high penetration of photovoltaics (PV), heat pumps and electric vehicles (EVs) with ...vehicle-to-grid (V2G) function. The DTS method is an extension of the dynamic tariff method proposed in the previous study. With the DTS, the regulation prices can be positive (tariff) or negative (subsidy). The study shows that the negative regulation price is necessary and very effective to solve congestion due to feed-in power flows, such as PVs and EVs in the V2G mode. In the study, dual decomposition of a convex quadratic model is proposed in addition to a conventional method for the DTS calculation. The case studies on the Roy Billinton test system demonstrate the efficacy of the DTS method for congestion management in distribution networks.
With the development of smart grid technologies, some of the electric demands which are traditionally considered fixed and inflexible will become promising distributed energy resources in future ...power systems. However, the participation of small scale or household energy sources into balancing power might challenge the operation of electric distribution systems and cause congestions. This paper presents a distribution congestion price (DCP) based market mechanism to alleviate possible distribution system congestions. By employing the locational marginal pricing model, the proposed DCPs are able to reflect the real congestion cost and further direct the schedule of the responses of electric demands. Based on the NordPool Spot market structure, the interactions between aggregators and the distribution system operator are discussed, and the procedure for calculating DCPs is proposed. Finally, a practical Danish 60kV/10.5kV distribution system is employed as the test case to verify the proposed method for mitigating congestion.
This paper presents a distribution locational marginal pricing (DLMP) method through chance constrained mixed-integer programming (MIP) designed to alleviate the possible congestion in the future ...distribution network with high penetration of electric vehicles (EVs). In order to represent the stochastic characteristics of the EV driving patterns, a chance constrained optimization of the EV charging is proposed and formulated through MIP. With the chance constraints in the optimization formulations, it guarantees that the failure probability of the EV charging plan fulfilling the driving requirement is below the predetermined confidence parameter. The efficacy of the proposed approach was demonstrated by case studies using a 33-bus distribution system of the Bornholm power system and the Danish driving data. The case study results show that the DLMP method through chance constrained MIP can successfully alleviate the congestion in the distribution network due to the EV charging while keeping the failure probability of EV charging not meeting driving needs below the predefined confidence.
Electric vehicles (EVs) has tiny environmental impact and will constitute a major mean of urban transportation in the future. Shared EV is quickly becoming a new business model under the sharing ...economy initiatives, providing easy access for commuters who possess no private cars. In this paper, we consider a carsharing company that owns EVs and some parking lots. Passengers can hire an EV at one parking lot and drive it to another one and pay for the service at a certain price determined by the company. A dedicated EV mobility model is proposed to capture the spatial transportation of energy without tracking every single vehicle. Price elasticity is described by a linear demand-price function. The company schedules the aggregated charging of unoccupied EVs in each parking lot, aiming at maximizing the total profit. Parking lots possess relatively large capacity and have to participate in a distribution power market; energy consumption is paid at the locational marginal price. The decision-making problem of the company is formulated as a bilevel program. The lower level simulates the distribution market clearing, and the upper level represents the pricing and charging scheduling problem faced by the company. Starting from a global polyhedral approximation of the power flow model, we develop an equivalent mixed-integer program based on primal-dual optimality condition and integer algebra technique, together with a warm-start strategy which accelerates computation remarkably. Case studies demonstrate that the proposed business model can reshape the load profile by shaving the peaking and filling the valley without harming the profit of the company.
In this paper, we review the emerging challenges and research opportunities for voltage control in smart grids. For transmission grids, the voltage control for accommodating wind and solar power, ...fault-induced delayed voltage recovery, and measurement-based Thévenin equivalent for voltage stability analysis are reviewed. For distribution grids, the impact of high penetration of distributed energy resources is analyzed, typical control strategies are reviewed, and the challenges for local inverter Volt-Var control is discussed. In addition, the motivation, state-of-the-art, and future directions of the coordination of transmission system operators (TSO) and distribution system operators (DSO) are also thoroughly discussed.
As a result of small fault current, high level of noise and a large penetration of distributed generators (DG), in the neutral non-effectively grounded medium-voltage (MV) distribution networks, it ...is quite difficult to locate the faulted line section for single phase to ground faults. In this paper, using a technique based on synchronized measurements in distribution networks, a fault location method based on the analysis of the energy of the transient zero-sequence current in the selected frequency band (SFB) is proposed. The equivalent impedance of the distribution network with lateral branches is studied with an equivalent network, and the phase-frequency characteristics of the equivalent impedance are analyzed. The SFB, within which the transient energy of the faulty line section is larger than that of the healthy line sections is determined. A combined fault-section location criterion is proposed and the implementation scheme is illustrated with the distribution level phasor measurement units. Numerical simulations of the IEEE 34 node system and the field experiments of a 10kV distribution network validate the feasibility and effectiveness of the proposed method.
This paper proposes a combined wind farm controller based on Model Predictive Control (MPC). Compared with the conventional decoupled active and reactive power controls, the proposed control scheme ...considers the significant impact of active power on voltage variations due to the low X/R ratio of wind farm collector systems. The voltage control is improved. Besides, by coordination of active and reactive powers, the Var capacity is optimized to prevent potential failures due to Var shortage, especially when the wind farm operates close to its full load. An analytical method is used to calculate the sensitivity coefficients to improve the computation efficiency and overcome the convergence problem. Two control modes are designed for both normal and emergency conditions. A wind farm with 20 wind turbines was used to verify the proposed combined control scheme.
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