Provision of secondary frequency regulation by coordinated dispatch of industrial loads and thermal power plants

Demand responsive industrial loads with high thermal inertia have potential to provide ancillary service for frequency regulation in the power market. To capture the benefit, this study proposes a new hierarchical framework to coordinate the demand responsive industrial loads with thermal power plants in an industrial park for secondary frequency control. In the proposed framework, demand responsive loads and generating resources are coordinated for optimal dispatch in two-time scales: (1) the regulation reserve of the industrial park is optimally scheduled in a day-ahead manner. The stochastic regulation signal is replaced by the specific extremely trajectories. Furthermore, the extremely trajectories are achieved by the day-ahead predicted regulation mileage. The resulting benefit is to transform the stochastic reserve scheduling problem into a deterministic optimization; (2) a model predictive control strategy is proposed to dispatch the industry park in real time with an objective to maximize the revenue. The proposed technology is tested using a real-world industrial electrolysis power system based upon Pennsylvania, Jersey, and Maryland (PJM) power market. Various scenarios are simulated to study the performance of the proposed approach to enable industry parks to provide ancillary service into the power market. The simulation results indicate that an industrial park with a capacity of 500 MW can provide up to 40 MW ancillary service for participation in the secondary frequency regulation. The proposed strategy is demonstrated to be capable of maintaining the economic and secure operation of the industrial park while satisfying performance requirements from the real world regulation market

Capturing Aggregate Flexibility in Demand Response

Flexibility in electric power consumption can be leveraged by Demand Response (DR) programs. The goal of this paper is to systematically capture the inherent aggregate flexibility of a population of appliances. We do so by clustering individual loads based on their characteristics and service constraints. We highlight the challenges associated with learning the customer response to economic incentives while applying demand side management to heterogeneous appliances. We also develop a framework to quantify customer privacy in direct load scheduling programs.Comment: Submitted to IEEE CDC 201

Sustainability in energy production

The requirement of energy in different human activities is continuously increasing; from the energetic production, chiefly by thermal systems, important and worrying environmental problems are generated: there are concerns about climate change, local air quality worsening, exhaustion of resources and land use change. To limit these negative aspects, policies of reduction in energy use must be first proposed; besides different technological, economic and planning solutions can be considered; their effect must be carefully assessed, as concerns effectiveness and practical implementation. The final political decision must consider the different tools that are at disposal, in order to define the best approach for the satisfaction of necessities with the minimum consequent impact

Sharpening the Cutting Edge: Corporate Action for a Strong, Low-Carbon Economy

Outlines lessons learned from early efforts to create a low-carbon economy, current and emerging best practices, and next steps, including climate change metrics, greenhouse gas reporting, effective climate policy, and long-term investment choices

Residential demand management using individualised demand aware price policies

This paper presents a novel approach to Demand Side Management (DSM), using an “individualised” price policy, where each end user receives a separate electricity pricing scheme designed to incentivise demand management in order to optimally manage flexible demands. These pricing schemes have the objective of reducing the peaks in overall system demand in such a way that the average electricity price each individual user receives is non-discriminatory. It is shown in the paper that this approach has a number of advantages and benefits compared to traditional DSM approaches. The “demand aware price policy” approach outlined in this paper exploits the knowledge, or demand-awareness, obtained from advanced metering infrastructure. The presented analysis includes a detailed case study of an existing European distribution network where DSM trial data was available from the residential end-users

Bus rapid transit

Effective public transit is central to development. For the vast majority of developing city residents, public transit is the only practical means to access employment, education, and public services, especially when such services are beyond the viable distance of walking or cycling. Unfortunately, the current state of public transit services in developing cities often does little to serve the actual mobility needs of the population. Bus services are too often unreliable, inconvenient and dangerous. In response, transport planners and public officials have sometimes turned to extremely costly mass transit alternatives such as rail-based metros. Due to the high costs of rail infrastructure, cities can only construct such systems over a few kilometres in a few limited corridors. The result is a system that does not meet the broader transport needs of the population. Nevertheless, the municipality ends up with a long-term debt that can affect investment in more pressing areas such as health, education, water, and sanitation. However, there is an alternative between poor public transit service and high municipal debt. Bus Rapid Transit (BRT) can provide high-quality, metro-like transit service at a fraction of the cost of other options. This document provides municipal officials, non-governmental organizations, consultants, and others with an introduction to the concept of BRT as well as a step-by-step process for successfully planning a BRT system

A dynamic simulation of low-carbon policy influences on endogenous electricity demand in an isolated island system

This paper considers the dynamics of electricity demand in response to changes arising from low-carbon policies and socio-economic developments. As part of an investigation into the evolution of such systems on small economically-developed islands, endogenous electricity demand and associated policies are studied for the Azorean island of São Miguel. A comprehensive System Dynamics (SD) model covering the period 2005 − 2050 is presented which captures both historical behaviours and real-world influences on the endogenous demand dynamics of an island-based electricity system. The impact of tourism, energy efficiency and electric vehicles (EV) expansion allied with associated policy options, are critically evaluated by the SD model using a series of scenarios. The model shows that energy efficiency measures exhibit the most significant long-term impact on electricity demand, while in contrast, policies to increase tourism have a much less direct impact and EV expansion has thought-provoking impacts on the long-term demand, although this is not as influential as energy efficiency measures

The Flowchart Model of Cluster Policy: The Automobile Industry Cluster in China

This paper proposes a general model of the flowchart approach to industrial cluster policy and applies this model to Guangzhou's automobile industry cluster. The flowchart approach to industrial cluster policy is an action plan for prioritizing policy measures in a time-ordered series. We reached the following two conclusions. First,we clarified the effects of Honda, Nissan, and Toyota on agglomeration in Guangzhou's automobile industry cluster. Second, we established that local governments play a crucial role in successful industrial cluster policy, and that the mayor of the local government should be offered incentives in order to target industrial clustering and implement cluster policy.Prioritization of cluster policy, Linearization of policy measures, Flowchart model, Inductive method, Anchor firm, Capacity, China, Industrial estates, Industrial policy, Automobile industry

CleanTX Analysis on the Smart Grid

The utility industry in the United States has an opportunity to revolutionize its electric grid system by utilizing emerging software, hardware and wireless technologies and renewable energy sources. As electricity generation in the U.S. increases by over 30% from today’s generation of 4,100 Terawatt hours per year to a production of 5,400 Terawatt hours per year by 2030, a new type of grid is necessary to ensure reliable and quality power. The projected U.S. population increase and economic growth will require a grid that can transmit and distribute significantly more power than it does today. Known as a Smart Grid, this system enables two- way transmission of electrons and information to create a demand-response system that will optimize electricity delivery to consumers. This paper outlines the issues with the current grid infrastructure, discusses the economic advantages of the Smart Grid for both consumers and utilities, and examines the emerging technologies that will enable cleaner, more efficient and cost- effective power transmission and consumption.IC2 Institut