System and Market-Wide Impact Analysis of Coordinated Demand Response and Battery Storage Operation by a Load-Serving Entity

Because of electricity markets, environmental concerns, transmission constraints, and variable renewable energy sources (VRES), coordinated operation of demand response (DR) and battery energy storage systems (BESS) has become critical. In turn, the optimal coordinated operation of DR and BESS by an entity can affect overall electricity market outcomes and transmission network conditions. The coordinated operation is desirable for the profit-seeking entity, but it may adversely affect the cost and revenues of other market participants or cause system congestion. Though few coordinated operation models already exist, our aim in this research is to provide a novel multi-objective optimization-based methodology for the coordinated operation of DR and BESS to boost market profit. Moreover, another goal is to simultaneously study the combined effects of such coordinated models on transmission networks and electricity markets for the first time. This paper has proposed a new method for coordinated DR and BESS utilization by a load-serving entity (LSE) to increase its profit. Moreover, it has employed agent-based modeling of the electricity systems (AMES) for testing our coordinated DR and BESS method under day-ahead market and transmission system conditions. Simulation results of case studies indicate that the operating costs of all LSEs decreased, and there was as much as 98,260 $/day in cost savings for BESS deploying LSE1. Although revenues of cheaper generation companies (GenCos) decreased, those of expensive GenCos increased or showed mixed trends. For example, GenCo 3 exhibits an 8765$/day decrease in revenue for 25% BESS capacity, whereas a 6328 $/day increase in revenue for 37.5% BESS capacity. The variance of LMPs, widely used as a risk index, greatly decreased for the LSE utilizing the coordinated methodology, somewhat decreased for other LSEs but increased for cheaper GenCos with no LSE at the local node. Since BESS deployment decisions of an LSE can have system-wide or market-wide consequences, simulation analysis before deployment can help reduce market distortions or system congestions

System and Market-Wide Impact Analysis of Coordinated Demand Response and Battery Storage Operation by a Load-Serving Entity

Because of electricity markets, environmental concerns, transmission constraints, and variable renewable energy sources (VRES), coordinated operation of demand response (DR) and battery energy storage systems (BESS) has become critical. In turn, the optimal coordinated operation of DR and BESS by an entity can affect overall electricity market outcomes and transmission network conditions. The coordinated operation is desirable for the profit-seeking entity, but it may adversely affect the cost and revenues of other market participants or cause system congestion. Though few coordinated operation models already exist, our aim in this research is to provide a novel multi-objective optimization-based methodology for the coordinated operation of DR and BESS to boost market profit. Moreover, another goal is to simultaneously study the combined effects of such coordinated models on transmission networks and electricity markets for the first time. This paper has proposed a new method for coordinated DR and BESS utilization by a load-serving entity (LSE) to increase its profit. Moreover, it has employed agent-based modeling of the electricity systems (AMES) for testing our coordinated DR and BESS method under day-ahead market and transmission system conditions. Simulation results of case studies indicate that the operating costs of all LSEs decreased, and there was as much as 98,260 $/day in cost savings for BESS deploying LSE1. Although revenues of cheaper generation companies (GenCos) decreased, those of expensive GenCos increased or showed mixed trends. For example, GenCo 3 exhibits an 8765$/day decrease in revenue for 25% BESS capacity, whereas a 6328 $/day increase in revenue for 37.5% BESS capacity. The variance of LMPs, widely used as a risk index, greatly decreased for the LSE utilizing the coordinated methodology, somewhat decreased for other LSEs but increased for cheaper GenCos with no LSE at the local node. Since BESS deployment decisions of an LSE can have system-wide or market-wide consequences, simulation analysis before deployment can help reduce market distortions or system congestions

Correction: Kazmi, S.A.A.; Janjua, A.K.; Shin, D.R. Enhanced Voltage Stability Assessment Index Based Planning Approach for Mesh Distribution Systems. Energies 2018, 11, 1213

The authors wish to make the following corrections to their paper [...

Enhanced Voltage Stability Assessment Index Based Planning Approach for Mesh Distribution Systems

This paper offers an enhanced voltage stability assessment index (VSAI) and loss minimalize condition (LMC) centered integrated planning approach. The proposed method aims at the simultaneous attainment of voltage stability, loss minimizations and various other related objectives with the employment of multiple distributed generation (DG) units, in mesh distribution systems (MDS). The approach presents two enhanced VSAI expressions based on a multiple-loops configured equivalent MDS model. The main objective of each VSAI expression is to find the weakest buses as potential candidates for single and multiple DG placements with initial optimal DG sizes for aimed objectives attainment in MDS. Later, mathematical expressions for LMC have been presented, based on equivalent MDS model. The LMC aims to achieve significant loss minimization with optimal DG sizes and attain negligible voltage difference across tie-line branches via reduction of respective loop currents. The proposed integrated VSAI-LMC based planning approach is employed with two computation variants and tested on two well-known, 33-Bus and 69-Bus, test distribution systems (TDS). The performance analysis of each TDS is conducted with two cases and respective scenarios, across various performance evaluation indicators (PEIs). The paper also offers a comparative analysis of achieved numerical outcomes of the proposed planning approach with the available research works found in the literature. The numerical results attained have better performance in comparison with the presented literature data and thus shows the effectiveness and validity of the proposed planning approach

Investigation of a Battery Storage System Aimed at Demand-Side Management of Residential Load

In this paper, an approach is presented for the demand-side management of residential loads in the urban areas of Pakistan using a battery storage system at the feeder level. The proposed storage system will be installed by a private distributor to supply affordable electricity during peak hours. The experimental data used to carry out this research work are the Pakistan Residential Energy Consumption (PRECON) data set. The households of the data set are categorized based on electric power usage through K-means clustering. The clusters are expanded for feeder synthesis to represent small-scale, medium-scale, and large-scale consumption. This expansion is performed through uniform distribution in a Monte Carlo simulation. The techno-economic analysis for the installation of a battery storage system is carried out for each feeder using SAM. The results of the research project elucidated that the load factors of the feeders representing small-scale, medium-scale, and large-scale consumption improved by 1%, 6%, and 7% by using the optimally sized batteries of 50 kW (670 kWh), 90 kW (1207 kWh), and 100 kW (1360 kWh), respectively. The distributor profit and the consumer utility bill savings ranged from US$12 k to US$25 k. The results proved the validity of the used approach to simultaneously reduce the consumer bill, maximize the distributor profit, and improve the feeder load factor. The novelty of this work lies in the location and in the way the system modeling has been performed with limited data

A Noise-Tolerant Audio Encryption Framework Designed by the Application of S8 Symmetric Group and Chaotic Systems

The recent decade has witnessed an exponential surge of digital content, especially multimedia and its applications. The security requirements of these innovative platforms necessitate the significance of enhancing advanced encryption schemes. In this paper, a novel encryption scheme is presented for real-time audio applications. The framework of the proposed scheme is grounded on the principles of confusion and diffusion. The confusion incorporates nonlinearity by the application of Mordell elliptic curves (MEC) and a symmetric group of permutations S8. The endurance of the proposed scheme is further enriched through the application of chaotic maps. The proposed scheme is intended to cater requirements of real-time voice communications in defense applications particularly warzones. The adoption of a modular design and fusion of chaotic maps makes the algorithm viable for numerous real-time audio applications. The security can further be enriched by incorporating additional rounds and number of S-boxes in the algorithm. The security and resistance of the algorithm against various attacks are gaged through performance evaluation and security measurements. The audio encryption scheme has the ability to tolerate noise triggered by a channel or induced by an invader. The decryption was successful and the resultant output was audible for noisy data. The overall results depict that the proposed audio encryption scheme contains an excellent cryptographic forte with the minimum computational load. These characteristics allow the algorithm to be a hotspot for modern robust applications