S. Ashok

Peak Load Management in Electrolytic Process Industries

Electrolytic process, employed for manufacturing basic chemicals like caustic soda and chlorine, is highly energy intensive. Due to escalating costs of fossil fuels and capacity addition, the electricity cost has been increasing for the last few decades. Electricity intensive industries find it very difficult to cope up with higher electricity charges particularly with time-of-use (TOU) tariffs implemented by the utilities with the objective of flattening the load curve. Load management programs focusing on reduced electricity use at the time of utilitys peak demand, by strategic load shifting, is a viable option for industries to reduce their electricity cost. This paper presents an optimization model and formulation for load management for electrolytic process industries. The formulation utilizes mixed integer nonlinear programming (MINLP) technique for minimizing the electricity cost and reducing the peak demand, by rescheduling the loads, satisfying the industry constraints. The case study of a typical caustic-chlorine plant shows that a reduction of about 19% in the peak demand with a corresponding saving of about 3.9% in the electricity cost is possible with the optimal load scheduling under TOU tariff.

Optimal operation of industrial cogeneration for load management

This paper presents a generalized formulation to determine the optimal operating strategy of industrial cogeneration schemes. The model includes both electrical and thermal systems. All types of cogeneration equipment viz steam turbines, gas turbines, diesel generators, steam boilers, waste heat recovery boilers, and steam header configuration, with grid connection are separately represented in terms of their characteristics so that the model has the flexibility to be applicable for any industry. The model is multiperiod and nonlinear in nature and utilizes a Newton based algorithm for minimizing the total operating cost. Optimal operating strategies for different equipment combinations for a typical industrial configuration under different electricity tariff rates are determined using the proposed model. The results show that industrial cogeneration has a significant potential in reducing peak coincident demand. The optimal response of cogeneration plant reduces the peak coincident demand by 42.8 MW (71%) under flat tariff and 54 MW (90%) under TOU tariff. The industry gets 16% saving in the total operating cost with the optimal operation of the cogeneration plant. When power export is permitted to grid, it provides the utility a peak saving of 63.7 MW.

Optimal Operation of Biomass/Wind/PV Hybrid Energy System for Rural Areas

In this article, a hybrid energy system consisting of biomass, wind, solar photovoltaic (SPV), and battery is proposed. The sources are operated to deliver energy at optimum efficiency. An optimization model is developed to supply the available energy to the loads according to the priority. It is also proposed to maintain a fair level of energy storage to meet the peak load demand together with biomass, wind, and solar photovoltaic during low or no solar radiation periods or during low wind periodsA case study was completed using load data collected from three villages (300 km south of Chennai, India). Simulations carried out for a one-year period proved the effectiveness of the developed energy management system by satisfying the load demand, nonlinear seasonal variations, and equipment constraints. Also with the proposed energy management, it is found that the load demand is almost satisfied, there is less dumped energy, and the state of charge of the battery is at a reasonably good level. Economic analysis is also carried out and the cost of energy is found to be Rs. 4.20 (US

Load-management applications for the industrial sector

0.1095).

Optimal cool storage capacity for load management

The goal of any load-management program is to maintain, as nearly as possible, a constant level of load, thereby allowing the system load factor to approach 100%. The important benefits of load management are reduction in maximum demand, reduction in power loss, better equipment utilisation and saving through reduced maximum demand charges. Load shifting, one of the simplest methods of load management, is to reduce customer demand during the peak period by shifting the use of appliances and equipment to partial peak and off-peak periods. Here no loads are being switched off, but only shifted or rescheduled, and hence the total production is not affected. In this paper, a fully fledged program is developed for load shifting and the same has been tried with the actual load data collected from a typical fertiliser and chemical industry plant.

An Optimal Stand-Alone Biomass/Solar-PV/Pico-Hydel Hybrid Energy System for Remote Rural Area Electrification of Isolated Village in Western-Ghats Region of India

Cool storage is a load management strategy for air conditioning loads, which shifts peak load by storing cooling capacity during off peak period. It allows the customer’s electricity use for cooling to be shifted to off peak period, benefiting both the consumer and the utility. Reduction in peak demand and electricity cost depend on electricity tariff rates, operating strategy, cool storage capacity and climatic conditions. In this paper, a methodology is presented to determine the optimal chilled water storage (CWS) capacity and corresponding operating strategy for the air conditioning loads for different electricity tariffs. This model minimizes the total operating cost of the air conditioning plant by a trade-off between the cost involved for providing the storage and accessories and savings achieved under the specified electricity tariff. A case study for a typical office complex shows that a reduction of 38% in peak demand is possible by adopting the optimal CWS strategy under time of use (TOU) tariff. The corresponding saving in the operating cost for the consumer is 5.9%. The results show that under flat tariffs, the prevalent high consumer discount rates make cool storage unviable. This provides justification for utility intervention in cool storage demand side management (DSM) programs.

Wheeling power : a case study in India

Biomass based hybrid energy system is utilized for the electrification of villages, especially in developing countries like India. Hybrid Energy System (HES) components, feasibility study, and cost analysis are presented in this paper for a remote area Kakkavayal, a forest region in Kerala, India. A water stream at 25 m height has been identified at Kakkavayal by the Forest Department of Kerala. The village has been marked to study hourly measured meteorological and load data for a period of time. The performance of the proposed hybrid system is determined on hourly basis and optimum configuration, which can meet the energy demand with minimum cost using the hybrid system design tool HOMER. Parametric analysis indicates that with 2 kW solar PV, 15 kW pico-hydel, and 5 kW biomass gasifier generator together with five numbers of 12 V, 200 Ah of battery storage to meet the primary load demand of 56 kWh/d and 17 kWh/d (scaled annual average) of deferrable load. From the simulation, the cost of energy is found to be Rs 7.274 (US

Synchronised Phasor Measurement Unit

0.164) per kWhr. The cost of energy of the proposed HES is also compared with the diesel-based HES. It is found that economically, the proposed HES is a very good alternative for present pico-hydel/diesel system.

Operational Flexibility in Smart Grid through Cloud Computing

It has been observed that captive power plants installed in many industries in India are operating individually and are under-utilised. Maximum utilisation of these plants along with the economical consideration is possible by wheeling the power between the utilities. A case study was conducted to demonstrate to various industries in India that there are potential financial benefits from increased co-operation by wheeling the power.

An Optimal Hybrid Wind-biomass Gasifier System for Rural Areas

With the advent of real time Phasor Measurement Units (PMUs), synchronised phasor measurements are possible which allows monitoring of dynamic phenomena. PMU terminals installed in proper nodes of power systems enable increasing the transmission capacity. Also it improves the operational safety of the power system. The better measurement performance and system wide data for monitoring and presentation of power system dynamics provide the operator with real time phasor information for remedial actions. The design of a Synchronised Phasor Measurement Unit (PMU) based on a Digital Signal Processor is explained in this paper. The standard temporal reference of this system is generated with a signal of 1 pulse per second (1PPS) from a global positioning system (GPS). The algorithm used for the implementation of proposed system is Recursive Discrete Fourier Transform (DFT) algorithm. The simulation for the proposed algorithm in LabVIEW software is explained in this paper and the results obtained after simulation were also given. The developed Phasor Measurement Unit (PMU) provides phasor information (both magnitude and phase angle) of a given signal in real time. The information can be utilized to estimate and calculate the power system state.