Program Topic: Energy Efficiency, Demand Response, & Energy Markets

T2-2Thursday 11:00-12:20

11:00 Estimated Economic Load Dispatch Based on Real Operation Logbook

Ali Al-Roomi (Dalhousie University, Canada); Mohamed El-Hawary (Dalhousie University, Canada)

The economic load dispatch (ELD) problem of electric power systems has been solved by various types of techniques including traditional and modern optimization algorithms. The main problem of achieving this stiff task is that all the exact specifications of the generating machines are required. Also, from a practical side, many of the power plants are operated without considering the ELD strategy because of the lack of experience to deal with this part, which is embedded as a package in the energy management system (EMS), and/or the hardness to construct precise constrained objective function matched with the real generating machines. Based on a fact that most of the power stations have their daily records, the estimated economic load dispatch (EELD) can be determined by using these recorded datasheets. This novel method can be applied without using any special software, and it is an optimization free technique. Moreover, this technique does not require to determine any parameter nor constraint on the generating machines, and all the candidate solutions are practical and feasible. The proposed method is tested with a real power station and it shows encouraging results.

11:20 The Impact of Essentials of Application Engineering on Conservation and Energy Efficiency Projects

Constantin Pitis (Powertech Labs Inc., Canada)

Energy conservation measures (ECMs) become a topic of increasing technical and economic importance. The objective is fulfilled by utility and government programs as part of demand-side management (DSM). The programs are designed to achieve corporate objectives by deferring the need for new power generation projects, reducing overall emission of greenhouse gases, improving efficiencies of the equipments and processes. There is a natural tendency of reducing the costs of Energy Studies on Conservation and Energy Efficiency Projects (CEEP) – as part of program expenses, in order to minimize the projects pay-back period. As a result, after CEEP commissioning undesired collateral effects might be present resulting in reduced amount of expected energy savings and sometime even financial losses. Subsequently these may reduce the impact of conservation programs at customer level. The root-cause analyze of such CEEP conducted to conclusion that some of consultants failing to consider a holistic approach methodology. Based on experience resulted from CEEP review activity, the author presents a unified mode of approaching CEEP by using the concept of 5 (five) Essentials of Application Engineering (5EAE). Paper presents fundamentals of new 5EAE concept enabling consultants, designers, manufacturers, and end-users to consistently design and evaluate new projects or retrofits of power converters (PC) and/or any industrial system drives (ISD). Application of 5 EAE concepts is relatively limited on American continent. To date there are no specific references on this subject. The concept is focused on specific ways to think outside the box in designing and/or assessing existent components of ISD. Case studies are used to prove the impact of using 5EAE on CEEP.

11:40 Evaluating Factors Responsible for Energy Consumption: Connection Weight Approach

Oludolapo Olanrewaju (University of Johannesburg, South Africa); Charles Mbohwa (University of Johannesburg, South Africa)

Various governments and stakeholders are established across the globe to respond to various energy challenges that has led to one or more energy policy development. A proper analysis of what contributes to energy consumption will assist in the development of policies needed for the conservation of energy consumption. This study made use of the connection weight approach as an instrument of the Artificial Neural Network (ANN) to evaluate the contributions of activity, structure and intensity factors to energy consumption in the Canadian industrial sector. From the evaluation, intensity contributed 46.5 %, whereas activity and structure contributed 32.6 % and 20.9 %. This is an indication that policies and strategies should be developed more on intensity to achieve energy saving.

12:00 Multi-market Bidding Strategy Considering Probabilistic Real Time Ancillary Service Deployment

Jie Li (Clarkson University, USA); Zuyi Li (Illinois Institute of Technology, USA)

Generation companies (GENCOs) are seeking for maximum economical profits in both energy and ancillary service (AS) markets. This paper proposes a methodology for obtaining the optimal bidding strategy for GENCOs in multiple electricity markets. Step-wise Supply function like bid curve with strategical bidding prices is used for the day-ahead multi-market auction. Probabilistic real time deployment of ancillary services is considered. Competition among GENCOs in such multi-market is modeled as a non-cooperative complete information game. A two-layer optimization problem is modeled, with the upper layer representing the GENCO’s profit maximization subproblem and the lower layer representing the ISO’s simultaneous multi-market clearing subproblem. Illustrative examples show advantages of considering probabilistic real time ancillary services deployment and simultaneously participating multi-market for a GENCO’s profit seeking purpose.

T3-2Thursday 13:20-15:00

13:20 Fuzzy Predictive Filtering in Nonlinear Economic Model Predictive Control for Demand Response

Rui Santos (Instituto Superior Técnico, Portugal); Yi Zong (Technical University of Denmark, Denmark); João Sousa (IDMEC, Instituto Superior Técnico, Universidade de Lisboa, Portugal); Luís Mendonça (Escola Superior Náutica Infante D. Henrique, Portugal); You Shi (Technical University of Denmark, Denmark); Lucian Mihet-Popa (Oestfold University College & Politehnica University of Timisoara, Norway)

The performance of a model predictive controller (MPC) is highly correlated with the model’s accuracy. This paper introduces an economic model predictive control (EMPC) scheme based on a nonlinear model, which uses a branch-and-bound tree search for solving the inherent non-convex optimization problem. Moreover, to reduce the computation time and improve the controller’s performance, a fuzzy predictive filter is introduced. With the purpose of testing the developed EMPC, a simulation controlling the temperature levels of an intelligent office building (PowerFlexHouse), with and without fuzzy filtering, is performed. The results show that the controller achieves a good performance while keeping the temperature inside the predefined comfort limits. Fuzzy predictive filtering has shown to be an effective tool which is capable of reducing the computational burden and increasing the performance level of the control algorithm.

13:40 Transmission Expansion for Profit Maximization of Generators in a Decentralised Market Structure

Harivina Gunnaasankaraan (University of Newcastle, Singapore); Aparna Viswanath (University of Newcastle, Singapore); Kaushik Mahata (University of New Castle, Australia)

This paper presents a transmission expansion formulation that maximizes the profits of the generators in a decentralized market structure. Transmission expansion of congested lines increases the dispatch by the generators and hence the generator surplus. The generators profit is the difference in surplus and the transmission congestion charges. Previous work on profit maximization was a simple quadratic formulation as the transmission charges were taken as fixed investment costs. In this paper, transmission congestion charges are based on the difference in spot market locational marginal prices. To ensure that transmission merchants always profits from expansion, the transmission congestion charges are modeled as several blocks of congestion prices and transmission capacities. The profitable transmission expansion for generators is thus formulated as a mixed integer (0-1) quadratic programming problem. Examples are provided to explain the method.

14:00 A Review of the Mexican Power System Market Policies for Competiveness and a More Diverse Generation Portfolio

Pedro Hernandez (WSU & WSU, Sweden)

After more than five decades of state monopoly, Mexican Power Market has been restructured and wholesale transactions started in January 1st, 2016. This paper discusses the market design features, its goals and challenges. Since deregulated market transactions and clean energy oriented policies are new to Mexican grid operations, a transition ensuring a successful establishment of the market design should be assessed in order to verify that ongoing transformation can lead to the accomplishment of its economic and environmental targets. The expected outcomes are underlined based on the impact that applied policies have had in the North American context.

14:20 The Smart Grid Impact on the Danish DSOs’ Business Model

Zheng Ma (Center for Energy Informatics & University of Southern Denmark, Denmark); Simon Sommer (Center for Energy Informatics, Denmark); Bo Jorgensen (University of Southern Denmark, Denmark)

The transformation progress of the smart grid challenges the market players’ business models. One of those market players is the Distribution System Operators (DSOs). This paper aims to elaborate how smart grid influences the DSOs’ business models with case studies of two Danish DSOs – EnergiFyn and TREFOR. The main findings indicate that the Danish smart grid transformation process influences the Danish DSOs’ business models via four smart grid related factors: (1) smart meters, (2) Distributed Energy Resources (DERs), (3) Bidirectional electricity flow, and (4) R&D. Therefore, The results show that the smart grid incrementally not revolutionary influences the Danish DSOs’ business models, and the transformation progress of the Danish smart grid is slower than the agenda of the official Danish smart grid development strategy.

14:40 Intelligent Management of Baseboard Heaters to Level Peak Demand

Ajit Pardasani (National Research Council Canada, Canada); Marianne Armstrong (National Research Council Canada, Canada); Guy Newsham (National Research Council Canada, Canada); Brody Hanson (Siemens Canada Ltd, Canada)

This paper presents results from an evaluation of a demand response (DR) strategy applied to residential electric baseboard heating loads. The underlying principle is based on storing electricity as thermal energy in the building envelope and household contents before the peak period and then discharging that stored energy to maintain conditions for thermal comfort during the peak period. Five different variations of the strategy were tested at the twin houses of Canadian Centre for Housing Technology (CCHT) for a four weeks period in the winter of 2015 using a side-by-side comparative assessment. The tests showed that a load shift up to 4 kW for the first 30 minutes and a total shift up to 5.7 kWh during the 2-hour period was possible, depending on the outdoor temperature. The approach holds significant potential for shifting peaks loads in locations where electricity is a major source of energy for space heating.

T4-2Thursday 15:20-17:00

15:20 New Approach on Energy Conservation Measures Types Applied in Mining Industry

Constantin Pitis (Powertech Labs Inc., Canada)

Some Energy Efficiency Programs (EEP) considers Energy Use Intensity (EUI) as an unreliable indicator due to its variation, i.e. the EUI values are dropping when production increases. Currently used Energy Conservation Measures – ECMs (supported by governmental and utility programs) are proven by energy savings (ES) recorded at revenue meter (or system boundary meter) considering energy use or energy recorded at revenue meter as a whole. The author proposed a novel concept of splitting the energy in 2 (two) specific components: Productive Energy and Non-Productive Energy followed by definition of new EUI type: Productive Energy Use Intensity (PEUI). The concept, applied to metal mines, made a breakthrough in EEP, enabling new ECM types applicable in Mining Industry. Case studies with verification & validation activities are provided.

15:40 The Impact of Intermittent Renewables on the Resource Adequacy in Electricity Markets

Hamid Aghaie (AIT Austrian Institute of Technology, Austria)

This paper analyzes the impact of renewables on the resource adequacy in German electricity market. A system dynamic model is proposed to model the electricity market by considering the uncertainty of renewable generation. The aim is to investigate the impact of the increasing renewables generation and its intermittency on the profitability of new installed capacity and long term investment decisions in an electricity market with a very tight reserve margin. It is assumed that the share of renewables generation will increase up to 60% in 2050. The results show that the investment in new conventional capacity will be profitable if the share of intermittent generation by solar and wind is at least 12% of total renewable generation in each year. The reason is that higher intermittency of renewables leads to more frequent scarcity situation and more profit for new capacity. The results prove that higher share of renewables leads to higher mean and variance of loss of load. Also, increasing share of renewables could result either ascending or descending average prices and it depends on the intermittency percentage of renewables’ generation. Increasing share of renewables leads to a higher price variance and higher intermittency results a steeper increase of price variance.

16:00 Economic Dispatch At Peak Load Using Load Reduction for Smart Grid

Zakareya Hasan (Dalhousie University, Canada); Mohamed El-Hawary (Dalhousie University, Canada)

This paper proposes a future economic dispatch problem for smart grid network (SGED) at peak time using demand side management (DSM) methods. The aim is to model the SGED problem at peak hours and solve it by finding an economic and reliable method of allocating the load on available generation units and choose the least expensive area or consumers to apply the DSM measures while satisfying the problem different constraints. Differential evolution is used to solve the SGED problem for two Test systems: three generation units with valve point effect and six generation units with prohibited operation zone and ramp rate limits.

16:20 A Review of Demand Response Techniques in Smart Grids

Anam Malik (University of New South Wales, Australia); Jayashri Ravishankar (University of New South Wales, Australia)

The worldwide installation of renewable energy generators has rendered the conventional frequency regulation techniques insufficient. However, smart grid in the recent years has shown great potential in regulating frequency by changing end-user demand so as to match supply. A large and growing body of literature in the past has investigated load scheduling and frequency deviation as two separate problems and proposed centralized or decentralized control techniques for eliminating power mismatch, that result in complex computational tasks and huge economic burden. Much of the research thus far fails to account for factors such as random customer demand, storage devices and various load groups in a single control model. The paper reviews previously presented demand scheduling and frequency regulation techniques as well as gives future directions for introducing a new, improved demand control system.

16:40 Residential Energy Management in Smart Grid Considering Renewable Energy Sources and Vehicle-to-Grid Integration

Fady Melhem (Université de Technologie de Belfort-Montbéliard (UTBM) / Institut de Recherche Industrielle (IRI), Lebanon); Nazih Moubayed (CRSI, Faculty of Engineering, Lebanese University, Lebanon); Olivier Grunder (Université de Technologie de Belfort-Montbéliard (UTBM), France)

The Smart Grids, which refers to the next generation of electrical power systems, are very complex systems with few theoretical researches. It needs to consider all sides of power grid, making it more intelligent and flexible. This notion is presented as an answer to changes in the electricity market, aiming to manage the increased demand while ensuring a better quality of service and more safety. This paper presents an integration of the distributed energy resources in the smart gird in an urban context. The analysis takes into account the integration of renewable energy production such as photovoltaic systems and micro-wind turbine systems, battery storage and gridable vehicles that can provide power to the grid by discharging the battery. Consequently, a mixed integer linear programming is proposed to optimize the energy production and consumption systems as well as the charging and discharging time of electric vehicle among a residential consumer. Besides, several case studies are presented by varying significant factors through design of experiments with Taguchi method to find the optimal solution and to illustrate their influence in the complexity of the system.