Optimal DR and ESS Scheduling for Distribution Losses Payments Minimization Under Electricity Price Uncertainty (original) (raw)
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Renewable Energy
The distribution network operator is usually responsible for improvement of efficiency and reliability of the network. This paper proposes a framework to demonstrate the impact of renewable energy sources (RESs), energy storage systems (ESSs), demand response (DR) and reconfiguration on the optimal sharing of energy. The proposed model determines the optimal locations of RESs, ESSs and DR in the distribution network to minimize simultaneously the cost of energy procurement and energy not supplied. A multiobjective optimization problem is formulated with a mixed-integer second-order cone programming model and ε-constraint method is used to generate Pareto optimal solutions. The network reconfiguration is also considered to optimize the power flow by changing the network topology. The proposed model is implemented on the IEEE standard 33-bus radial test system, and solved by General Algebraic Modeling System (GAMS) optimization software. According to the simulation results, the proposed framework is beneficial both from the reliability and economic perspectives.
2014 IEEE Conference on Technologies for Sustainability (SusTech), 2014
This paper focuses on the problem of the probabilistic optimal day-ahead scheduling of energy resources in Active Distribution Networks (ADNs). These resources include both dispersed energy storage systems (DESSs) and volatile renewable embedded generators. Technical constraints related to both energy resources and electrical network are modeled and taken into account in the proposed optimization problem. The paper first proposes a convex formulation of a specific optimal power flow (OPF) used to compute the resources schedule. Its objective function aims at achieving the minimum of the following quantities: network and DESSs losses, energy cost imported from the external grid, and deviations from the day-ahead scheduled power flow with the same external grid. In addition, the ability of using the substation transformer tap-changer is incorporated into the problem with a suitable cost function. The initial OPF formulation is then enhanced thanks to the use of the Mixed Integer Second Order Cone Programming approach in order to formulate a stochastic AC-OPF. The uncertainties of the problem are due to the forecast errors of the PV generation, load consumption and energy prices. The applicability and the effectiveness of the proposed scheduling approach are tested by using a modified version of the IEEE 34 buses test feeder.
Time-varying Cost of Loss Evaluation in Distribution Networks Using Market Marginal Price
In the electric power system planning process, engineers seek to identify the most cost-effective means of serving the load within reliability and power quality criteria. In order to accurately assess the cost of a given project, the feeder losses must be calculated. In the past, it was necessary to estimate the feeder losses based upon the peak load and a calculated load factor for the year. The cost of these losses would then be calculated based upon an expected, fixed per-kW h generation cost. This paper presents a more accurate means of calculating the cost of losses, using hourly feeder load information and time-varying electric energy cost data. This paper attempts to quantify the improvement in accuracy and presents an example where the economic evaluation of a planning project requires the more accurate loss calculation.
Distribution loss allocation methods assessment under electricity market environment
2005 IEEE Russia Power Tech, 2005
Under real-time or day-ahead pool-based electricity markets, the implementation of the distribution loss allocation procedures implies an access-pricing framework based on halfhour or hour locational prices. For each consumer and distributed generator it is required to apply an additional charge in the energy price in order to cover the cost of active losses. Since every allocation procedure modifies the locational prices in a different way, the initial market equilibrium point is altered and some form of cross-subsidies appears among market agents affecting the net social welfare and the network remuneration. The regulator should address the economical impact of each allocation method in order to ensure a non-discriminatory access to the network and guarantee revenue reconciliation of losses. This paper contributes to regulator assessment introducing a novel analysis of the impact of each loss allocation procedure based on the social welfare theory and explicitly considering the price elasticity of demand. The methodology was tested in two distribution test systems. 1
Loss allocation in distribution network including distributed energy resources (DERs)
International Transactions on Electrical Energy Systems, 2018
In recent years due to the high penetration of distributed generation (DG) in the network, the importance of distribution loss allocation (LA) has increased. Evaluation and allocation of the system losses to suppliers and consumers in presence of DGs are key issues that to be addressed. This paper presents a new algorithm for LA in distribution systems including DG units. This algorithm is based on the injected power into network lines and considers each line's active and reactive power flows for LA. At first, regardless of the suppliers, the contribution of each load in the loss of each line is obtained. In the next step, the contribution of each supplier (DGs) in the loss of each line is calculated. Finally, a normalization factor is introduced and the contributions of each load and each DG in the loss of each line have been calculated separately. The proposed algorithm is simple and easy to implement on the large-scale distribution systems. This algorithm has been applied on 2 distribution systems, and the results are compared with other LA methods.
Optimal Dispatch of the Energy Demand in Electrical Distribution Grid with Reserve Scheduling
Environmental and Climate Technologies
The operation of the electrical systems is a major problem for electrical companies’ subject to uncertainties threatening. In this study, the optimal management of the energy demand in the electrical distribution grid is done by interval optimization approach under electrical price uncertainty. The management of the energy demand is implemented via incentive-based modelling of the demand response programs (DRPs). The incentive-based modelling as reserve, and based on bid price for reduction of the electrical demand at peak hours is proposed. The interval optimization approach is used for the minimization of the electrical price uncertainty effects. The main objective in the proposed approach is minimizing operation cost; epsilon-constraint method is utilized to solve the problem. Finally, an electrical distribution grid has been used at various case studies to numerical simulation results and positive effects of the proposed modelling under uncertainties.
Electric Power Systems Research, 2013
The evolution of distribution automation technologies and the advances in distribution system optimisation studies are enabling the implementation of network configurations that are variable in time, with a limited number of configuration changes per day. The first part of this paper addresses the definition of pseudo-optimal intra-day distribution system configurations based on multi-scenario analysis handled with decision theory concepts. The resulting configurations are then used to formulate a demand response scheme for a given time period, aimed at procuring demand reductions to further decrease the distribution system losses. This scheme is driven by the calculation of the marginal loss coefficients and by the customers' willingness to participate in the demand response action. A dedicated offer scheme to be introduced in a benefit-based mechanism for optimal demand procurement is formulated and discussed.
Optimal Operation Strategy with using BESS and DGs in Distribution System
Journal of International Council on Electrical Engineering, 2012
This paper proposes a methodology for distribution system operation using battery energy storage system (BESS), interfaced inverter with DGs and existing voltage control devices. The proposed method decides the optimal operation schedule of each control device by optimal calculation. Optimal calculation uses a forecast information for a next day photovoltaic generator output and load demand. As a result, the proposed method achieves a voltage control for each of the node within the acceptable range, smoothing an interconnection point power flow and reducing of total distribution loss. The effectiveness of the proposed method is verified by using MATLAB.
Optimal Scheduling for Energy Storage Systems in Distribution Networks
2020
Distributed energy storage may play a key role in the operation of future low-carbon power systems as they can help to facilitate the provision of the required flexibility to cope with the intermittency and volatility featured by renewable generation. Within this context, this paper addresses an optimization methodology that will allow managing distributed storage systems of different technology and characteristics in a specific distribution network, taking into account not only the technical aspects of the network and the storage systems but also the uncertainties linked to demand and renewable energy variability. The implementation of the proposed methodology will allow facilitating the integration of energy storage systems within future smart grids. This paper’s results demonstrate numerically the good performance of the developed methodology.
2017
Variations in solar irradiance and wind speed cause fluctuations in voltage of distribution networks. Battery energy storage systems (BESSs) are usually installed in the distribution networks to mitigate the effects of these voltage fluctuations. The lifespan of a BESS-battery is affected by various factors such as the operating temperature, the level of depth of discharge and the magnitude of charging and discharging currents. In this paper, a new methodology is proposed in which the factors affecting the lifespan of the battery are modelled to find the optimal location and size of BESSs. The problem is formulated as a multi-objective optimization problem. The first objective function represents total energy losses of a distribution network, whereas the second objective function contains total investment cost associated with the installation of a BESS. Moreover, voltage regulation is carried out with the BESS. An IEEE 906 bus test feeder is used for the simulations, and both wind a...