Kankar Bhattacharya

Optimal investment planning for distributed generation in a competitive electricity market

This paper proposes a new heuristic approach for distributed generation (DG) capacity investment planning from the perspective of a distribution company (disco). Optimal sizing and siting decisions for DG capacity is obtained through a cost-benefit analysis approach based on a new optimization model. The model aims to minimize the discos investment and operating costs as well as payment toward loss compensation. Bus-wise cost-benefit analysis is carried out on an hourly basis for different forecasted peak demand and market price scenarios. This approach arrives at the optimal feasible DG capacity investment plan under competitive electricity market auction as well as fixed bilateral contract scenarios. The proposed heuristic method helps alleviate the use of binary variables in the optimization model thus easing the computational burden substantially.

Reactive Power as an Ancillary Service

This paper addresses the problem of reactive power procurement by an independent system operator (ISO) in deregulated electricity markets. A reactive bid structure is proposed in the context of a reactive power market. Based on the reactive power price offers and technical constraints involved in reactive power planning, a two-tier approach is developed to determine the most beneficial reactive power contracts for the ISO. The reactive capability of a generator and, therefore, the opportunity costs in providing reactive power is also included in the model. Uncertainty in reactive demand and in reactive bids of participating parties is incorporated through Monte Carlo simulations and the expected reactive power procurement plan for the ISO is hence determined. The CIGRÉ 32-bus network, approximately representing the Swedish system, is used for the studies.

Optimal Operation of Distribution Feeders in Smart Grids

This paper presents a generic and comprehensive distribution optimal power flow (DOPF) model that can be used by local distribution companies (LDCs) to integrate their distribution system feeders into a Smart Grid. The proposed three-phase DOPF framework incorporates detailed modeling of distribution system components and considers various operating objectives. Phase specific and voltage dependent modeling of customer loads in the three-phase DOPF model allows LDC operators to determine realistic operating strategies that can improve the overall feeder efficiency. The proposed distribution system operation objective is based on the minimization of the energy drawn from the substation while seeking to minimize the number of switching operations of load tap changers and capacitors. A novel method for solving the three-phase DOPF model by transforming the mixed-integer nonlinear programming problem to a nonlinear programming problem is proposed which reduces the computational burden and facilitates its practical implementation and application. Two practical case studies, including a real distribution feeder test case, are presented to demonstrate the features of the proposed methodology. The results illustrate the benefits of the proposed DOPF in terms of reducing energy losses while limiting the number of switching operations.

Towards a Competitive Market for Reactive Power

This paper presents the design of a competitive market for reactive power ancillary services. Generator reactive power capability characteristics are used to analyze the reactive power costs and subsequently to construct a bidding framework. The reactive power market is settled on uniform price auction, using a compromise programming approach based on a modified optimal power flow model. The paper examines market power issues in these markets and identifies locations where strategic market power advantages are present that need to be removed through investments in reactive power devices.

Optimal Operation of Residential Energy Hubs in Smart Grids

This paper presents mathematical optimization models of residential energy hubs which can be readily incorporated into automated decision making technologies in smart grids, and can be solved efficiently in a real-time frame to optimally control all major residential energy loads, storage and production components while properly considering the customer preferences and comfort level. Novel mathematical models for major household demand, i.e., fridge, freezer, dishwasher, washer and dryer, stove, water heater, hot tub, and pool pumps are formulated. Also, mathematical models of other components of a residential energy system including lighting, heating, and air-conditioning are developed, and generic models for solar PV panels and energy storage/generation devices are proposed. The developed mathematical models result in Mixed Integer Linear Programming (MILP) optimization problems with the objective functions of minimizing energy consumption, total cost of electricity and gas, emissions, peak load, and/or any combination of these objectives, while considering end-user preferences. Several realistic case studies are carried out to examine the performance of the mathematical model, and experimental tests are carried out to find practical procedures to determine the parameters of the model. The application of the proposed model to a real household in Ontario, Canada is presented for various objective functions. The simulation results show that savings of up to 20% on energy costs and 50% on peak demand can be achieved, while maintaining the household owners desired comfort levels.

Localized reactive power markets using the concept of voltage control areas

Summary form only given. In this paper, we present the design of a localized competitive market for reactive power ancillary services at the level of individual voltage-control areas. The concept of electrical distance has been used to identify the different voltage-control areas within a power system. The proposed reactive power market is settled on uniform price auction, using a modified optimal power-flow model. Uniform prices for various components of reactive power service are obtained for each voltage-control area. In the study cases described in the paper, we examine whether such a localized reactive power market is more desirable than a common system-wide reactive power market

Wind Farms as Reactive Power Ancillary Service Providers—Technical and Economic Issues

This paper examines the possibility of providing reactive power support to the grid from wind farms (WFs) as a part of the ancillary service provisions. Detailed analysis of the WF capability curve is carried out considering maximum hourly variation of wind power from the forecasted value. Different cost components are identified, and subsequently, a generalized reactive power cost model is developed for wind turbine generators that can help the independent system operator (ISO) in managing the system and the grid efficiently. Apart from the fixed cost and the cost of loss components, a new method is proposed to calculate the opportunity cost component for a WF considering hourly wind variations. The Cigre 32-bus test system is used to demonstrate a case study showing the implementation of the developed model in short-term system operations. A finding is that higher wind speed prediction errors (a site with high degree of wind fluctuations) may lead to increased payments to the WFs for this service, mainly due to the increased lost opportunity cost (LOC) component. In a demonstrated case, it is found that 2340

Optimal reactive power planning and its spot-pricing: an integrated approach

/h is paid to the WF as the LOC payment only, when the wind prediction error is 0.5 per unit (p.u.), whereas 54

System Stability Impact of Large-Scale and Distributed Solar Photovoltaic Generation: The Case of Ontario, Canada

/h is the expected total payment to the WF when the prediction error is 0.2 p.u. for its reactive power service.

A Generic Operations Framework for Discos in Retail Electricity Markets

The paper presents an integrated framework to analyze the issues of reactive power planning along with reactive power pricing. The planning problem involves optimal placement and sizing of capacitors in a network such that operating and investment costs are minimum. A simple bus-wise cost-benefit analysis (CBA) scheme is proposed which involves solving a modified optimal power flow problem (OPF) iteratively. The proposed CBA incorporates detailed hourly loading conditions at a bus and achieves a fairly accurate estimate of the benefits from capacitor placement. The formulation is directly handled by the well known MINOS code and is solved efficiently. It obviates the need to introduce integer variables and is thus suitable for large system applications. A two-part reactive power spot-pricing scheme is formulated, by which the investment and operational costs can be recovered by the utility. The proposed reactive power price has two parts-a fixed part to account for the investment costs of new capacitor at a bus and a variable spot price to account for the operating costs incurred in supplying the additional reactive power from generating units.