Cyber-physical-social systems and constructs in electric power engineering

Cyber-physical-social systems (CPSS) integrate computing, physical assets and human networks. Divided into four application areas to the electric grid, this book describes state-of-the-art CPSS in electric power systems, including detailed approaches on social constructs which are a critical aspect of the end-user realm

Simulation Studies to Quantify the Impact of Demand Side Management on Environmental Footprint

The increased use of energy leads to increased energy-related emissions. Demand side management (DSM) is a potential means of mitigating these emissions from electric utility generating units. DSM can significantly reduce emissions and provide economic and reliability benefits. This work presents some DSM techniques, such as load shifting, energy conservation, and valley filling. Furthermore, this work explains the most common DSM programs. To quantify the effect of DSM in diminishing carbon footprint, this paper performs power flow analysis on a yearly load profile corresponding to Fort Collins, Colorado, U.S. This work used the IEEE 13-node test system to simulate several scenarios from the multi-criteria decision-making (MCDM) alternatives, both individually and integrated. For the base case, emissions decrease by 16% from the 2005 level. The “energy conservation” option achieved a 20% reduction in emissions, integrating both alternatives increased the emissions mitigation up to 22%. Simulation of the residential sector shows the “communication and intelligence” option reduces emissions about 14% from the 2005 level. A scenario that combines “electric stationary storage” with “communication and intelligence” diminishes the emissions by more than 15%. The last scenario examined all MCDM alternatives combined into one option, resulting in a 20% emissions reduction. We also conducted a cost benefit analysis (CBA) to investigate economic, technical, and environmental costs and benefits associated with each alternative. The economic evaluation shows that “electric stationary storage” is the best option since it charges during lower electricity prices and discharges during peaking demand. The economic analysis presents a trade-off chart, so the decision maker can select the alternative based on their preference

A Performance Metric for Co-optimization of Day-Ahead Dispatch and Reserves in Electric Microgrids

International audienceWe present a new performance metric for co-optimization of dispatch and reserves in microgrids. A metric based on NERC criteria is used for each asset to quantity its reliability-based value. A system level metric is obtained through the individual performance metrics, dispatched capacity, and net dispatchable capacity available as reserve. Simulations are performed on a notional microgrid with a dispatchable and a non-dispatchable distributed energy resource to demonstrate the calculation of the metric

Risk assessment in planning high penetrations of solar photovoltaic installations in distribution systems

The stochastic nature of several renewable energy resources adds a layer of complexity to the planning of the distribution networks. Distributed energy storage is a potential solution for buffering the intermittent supply of energy from such stochastic resources and increasing reliability. This paper quantifies the benefit of investing in battery energy storage systems (BESS) along with relatively high solar photovoltaic (PV) penetrations to defer capital-intensive investments in distribution system assets. Uncertainties in the load growth and the solar PV generation are considered in the assessment of risk by using modified risk-adjusted cost ratios. Furthermore, the size and allocation of BESS in the network system are optimized by applying a heuristic algorithm. The results are demonstrated via simulations on a typical Latin American distribution network. Simulation results indicate that the flexibility of BESS for distribution planning lies in closely accommodating the growth demand and distributed PV integration.Fil: Samper, Mauricio Eduardo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Juan. Instituto de Energía Eléctrica. Universidad Nacional de San Juan. Facultad de Ingeniería. Instituto de Energía Eléctrica; ArgentinaFil: Eldali, Fathalla A.. State University of Colorado - Fort Collins; Estados UnidosFil: Suryanarayanan, Siddharth. State University of Colorado - Fort Collins; Estados Unido

Some Characteristics of Emerging Distribution Systems Considering the Smart Grid Initiative

Modernization of the electric power system in the United States is driven by the Smart Grid Initiative. Many changes are planned in the coming years to the distribution side of the U.S. electricity delivery infrastructure to embody the idea of "smart distribution systems." However, no functional or technical definition of a smart distribution system has yet been accepted by all.

Quantifying the Impact of Solar Photovoltaic and Energy Storage Assets on the Performance of a Residential Energy Aggregator

International audienceDemand response (DR) and renewable energy sources have opened new avenues for end-users to lower their energy expenses via energy management systems. Aggregators facilitate the participation of end-users by acting on their behalf and interacting with bulk electricity markets. In this paper, an energy management algorithm is presented to investigate the impact of distributed photovoltaic (PV) and central energy storage system (ESS) assets on the economic performance of an energy aggregator in the residential sector. To enable DR, the aggregator provides a competitive incentive price to end-users, and centrally optimizes the central ESS assets and schedule of committed customer elastic loads. Thus, customers reduce their daily electricity bill while the aggregator decreases the aggregated peak consumption and earns profits as a return for providing DR services. The scope of this paper pertains to the economic impact of distributed PV and central ESS assets on aggregator profits and customer savings resulting from DR, including ESS degradation. Simulation results showed that the central ESS increases the income of the aggregator, while residential PV reduces the impact of DR

A Hybrid Hilbert-Huang Method for Monitoring Distorted Time-Varying Waveforms

The electric power systems together with the entire energy sector are rapidly evolving towards a low-carbon, secure, and competitive economy facing revolutionary transformations from technical structure to economic value chain. Pathways to achieve sustainability led to the development of new technologies, accommodation of larger shares of unpredictable and stochastic electricity transfer from sources to end-users without loss of reliability, new business models and services, data management, and so on. The new technologies and incentives for local energy communities along with large development of microgrids are main forces driving the evolution of the low voltage energy sector changing the context and paradigm of rigid contractual binding between utilities and end-user customers (now progressing to flexible prosumers with generation and storage capabilities). The flexibility and operation of a prosumer can be enhanced by a non-intrusive time-frequency analysis of distorted power quality waveforms for both generation and demand at the point of common connection. Therefore, it becomes of importance to discriminate among successive quasi-steady-state operation of a given local system using only the aggregated waveforms information available in the PCC. This paper focuses on the Hilbert–Huang method with modifications such as empirical mode decomposition improved with masking signals based on the Fast Fourier Transform, Hilbert spectral analysis, and a post-processing method for separating components and their amplitudes and frequencies within distorted power signals for a low-voltage prosumer operation. The method is used for a time-frequency-magnitude representation with promising localization capabilities enabling efficient operation for prosumers