2-[1-(3-{2-[(2-Hy­droxy­benzyl­idene)amino]­phen­oxy}prop­yl)-1H-1,3-benzodiazol-2-yl]phenol

In the title compound, C29H25N3O3, the imine double bond has an E configuration. The dihedral angle between the hy­droxy­phenyl and benzene rings in the imine moiety is 26.95 (9)°, and the dihedral angle between the hy­droxy­phenyl and benzimidazole rings in the other moiety is 14.83 (9)°. These angles are probably limited to small values as a consequence of two strong intra­molecular O—H⋯N hydrogen bonds formed between the hy­droxy groups and the imine and imidazole N atoms. The aliphatic chain linking the two ring systems has a gauche conformation, as reflected in C—C—C—O torsion angle of 70.9 (2)°

Stochastic optimization for retailers with distributed wind generation considering demand response

Abstract In this paper, a multi-stage stochastic model is presented for a renewable distributed generation (RDG)-owning retailer to determine the trading strategies existing in a competitive electricity market. Uncertainties associated with wholesale electricity market price, clients’ consumption and power output of wind resources are considered through auto regressive integrated moving average (ARIMA) approach. In the proposed method, three trading floors are addressed for the retailer to hedge against the uncertainties. In the first stage, the retailer participates in day-ahead market to supply the clients and in the second stage, intraday market is addressed to allow the retailer to modify the schedule of its clients’ consumption/RDG production. Due to unfavorable uncertainties, especially in renewable power production, real-time market is considered in the third stage to diminish the uncertainty at power delivery time. Cost function of wind resources considering capital, operation and maintenance (O&M) cost is incorporated in the objective function to increase the applicability of the mechanism. The proposed approach is formulated for risk-averse and risk-taker retailer through conditional value at risk (CVaR) approach. In order to study the impact of retail strategies on consumption pattern and consumers’ electricity bills, time-of-use (TOU) demand response programs are discussed in this paper. Formulating the problem, the mixed integer non-linear programming (MILNP) problem is transformed into mixed integer linear programming (MILP) by jointly using decomposition and disjunctive constraints. Finally, a case study containing wind power resources, energy storage system and retailer is considered to analyze the proficiency of the proposed approach

Joint investment of community energy storage systems in distribution networks using modified Nash bargaining theory

•A joint investment plan for community energy storage systems is proposed.•A novel linearized lifetime model for lead acid batteries is implemented.•Two distinctive cases of non-cooperation and cooperation for the expansion problem are proposed.•The benefit of participating in the joint investment of the assets for all players is numerically verified. The emergence of renewable energy technologies in distribution networks and microgrids has raised the importance of integrating energy storage systems into these grids. However, their high investment costs deter decision makers from effectively expanding these assets. In this paper, a cooperative community storage expansion plan is proposed as a bargaining problem between distribution company and private microgrids to jointly invest in energy storage systems. By doing so, each party takes a quota of shared investment costs and thus the burden of high investment costs is alleviated. A modified version of the Nash bargaining theory approach is proposed to implement the cooperative framework in a fair manner. Two cases of non-cooperation and cooperation are distinctively defined and the merits of cooperation are illustrated. The lead acid battery is considered as the storage candidate, for which a novel linearized lifetime model and replacement approach is also proposed. The bargaining results presented on a distribution network test case indicate that through the proposed cooperation, all players receive positive surpluses by decreasing their costs or increasing their revenues. Thus, both distribution company and microgrids would have incentives to participate in the proposed cooperation. Moreover, the superiority of the proposed modified Nash bargaining theory compared to conventional Nash bargaining theory in terms of cooperation fairness is illustrated. Finally, the ability of the proposed cooperative community storage expansion plan to effectively manage cooperative storage installations and replacements is demonstrated

Voltage distribution indices method to analyse the performance of various structures of stray current collectors in direct current transit lines

Abstract The stray current produced by a direct current (DC) transit system leads to the corrosion of rails and metallic structures buried under and around the metro line. One practical approach to diminish current injection into buried structures is to implement stray current collectors underneath the rail. An analytical method is proposed herein using voltage distribution indices (VDIs) to calculate the voltage and current collection level of each collector located under the rail soil, and the solutions are validated by comparing with modelling results. The proposed method helps to achieve the voltage of different points under the ground and the current reaching the collectors using a circuit model, without facing the limitations of practical methods, as a supplementary study for experimental tests. Moreover, the effect of different arrangements of collectors under running rails is modelled. The analytical method is deployed considering two objectives, that is stray current collection by the conductors and a reduction in the installation cost of the conductors. Various arrangements of stray current collectors are compared and evaluated. Using integral and matrix equations, current density and potential at different points under the soil are calculated and the obtained results are compared with European (EN) standards

Electricity Demand Response Optimum Planning Based on Economic Modeling Demand with Whe Fexible Elasticity of Demand Function in Iran

In recent years, extensive researches have been conducted on implementation of demand response programs (DRPs), aimed to electricity price reduction, transmission lines congestion resolving, security enhancement and improvement of market liquidity. Basically, DRPs are divided into two main categories namely, incentive-based programs (IBPs) and time-based rate programs (TBRPs). An economic model of price /incentive demand response is derived based on the concept of flexible price elasticity of demand and customer utility function. In this paper has been shown that the customers’demand depends on different decision signals like the electricity price, participation level of customers, incentive and the penalty values determined for DRPs. By using the proposed economic model, the behavior of customers for different electricity prices, incentives, penalties and participation level of customers in DRPs was simulated with MATLAB. Then the performance of the proposed model was investigated through numerical study using Iranian network load profile on the annual peak day of the year 2007